Dissertations / Theses: 'Radio Resources Allocation'

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Weng, Lingfan. "Analysis and allocation of radio resources in cooperative wireless networks /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?ECED%202008%20WENG.

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Sharara, Mahdi. "Resource Allocation in Future Radio Access Networks." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG024.

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Cette thèse considère l'allocation des ressources radio et de calcul dans les futurs réseaux d'accès radio et plus précisément dans les réseaux Cloud-RAN (Cloud-Radio Access Networks) ainsi que les réseaux Open-RAN (Open-Radio Access Networks). Dans ces architectures, le traitement en bande de base de plusieurs stations de base est centralisé et virtualisé. Cela permet une meilleure optimisation du réseau et une réduction des dépenses d'investissement et d'exploitation. Dans la première partie de cette thèse, nous considérons un schéma de coordination entre les ordonnanceurs radio et de calcul. Dans le cas où les ressources de calcul ne sont pas suffisantes, l'ordonnanceur de calcul envoie un retour d'information à l'ordonnanceur radio pour mettre à jour les paramètres radio. Bien que cela réduise le débit radio de l'utilisateur, il garantit que la trame sera traitée au niveau de l'ordonnanceur de calcul. Nous modélisons ce schéma de coordination à l'aide de la programmation linéaire en nombres entiers (ILP) avec comme objectifs de maximiser le débit total ainsi que la satisfaction des utilisateurs. Les résultats montrent la capacité de ce schéma de coordination à améliorer différents paramètres, notamment la réduction du gaspillage de puissance de transmission. Ensuite, nous proposons des heuristiques à faible complexité et nous les testons dans un environnement de services multiples avec des exigences différentes. Dans la deuxième partie de cette thèse, nous considérons l'allocation conjointe des ressources radio et de calcul. Les ressources radio et de calcul sont allouées conjointement dans le but de minimiser la consommation énergétique. Le problème est modélisé à l'aide de la programmation linéaire mixte en nombres entiers (MILP), et est ensuite comparé à un autre problème MILP ayant comme objectif de maximiser le débit total. Les résultats montrent que l'allocation conjointe des ressources radio et de calcul est plus efficace que l'allocation séquentielle pour minimiser la consommation énergétique. Enfin, nous proposons un algorithme basé sur la théorie de matching (matching theory) à faible complexité qui pourra être une alternative pour résoudre le problème MILP à haute complexité. Dans la dernière partie de cette thèse, nous étudions l'utilisation des outils de l'apprentissage machine (machine learning). Tout d'abord, nous considérons un modèle d'apprentissage profond (deep learning) qui vise à apprendre comment résoudre le problème de coordination ILP, mais en un temps beaucoup plus court. Ensuite, nous considérons un modèle d'apprentissage par renforcement (reinforcement learning) qui vise à allouer des ressources de calcul aux utilisateurs afin de maximiser le profit de l'opérateur
This dissertation considers radio and computing resource allocation in future radio access networks and more precisely Cloud Radio Access Network (Cloud-RAN) and Open Radio Access Network (Open-RAN). In these architectures, the baseband processing of multiple base stations is centralized and virtualized. This permits better network optimization and allows for saving capital expenditure and operational expenditure. In the first part, we consider a coordination scheme between radio and computing schedulers. In case the computing resources are not sufficient, the computing scheduler sends feedback to the radio scheduler to update the radio parameters. While this reduces the radio throughput of the user, it guarantees that the frame will be processed at the computing scheduler level. We model this coordination scheme using Integer Linear Programming (ILP) with the objectives of maximizing the total throughput and users' satisfaction. The results demonstrate the ability of this scheme to improve different parameters, including the reduction of wasted transmission power. Then, we propose low-complexity heuristics, and we test them in an environment of multiple services with different requirements. In the second part, we consider the joint radio and computing resource allocation. Radio and computing resources are jointly allocated with the aim of minimizing energy consumption. The problem is modeled as a Mixed Integer Linear Programming Problem (MILP) and is compared to another MILP problem that maximizes the total throughput. The results demonstrate the ability of joint allocation to minimize energy consumption in comparison with the sequential allocation. Finally, we propose a low-complexity matching game-based algorithm that can be an alternative for solving the high-complexity MILP problem. In the last part, we investigate the usage of machine learning tools. First, we consider a deep learning model that aims to learn how to solve the coordination ILP problem, but with a much shorter time. Then, we consider a reinforcement learning model that aims to allocate computing resources for users to maximize the operator's profit

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Schimuneck, Matias Artur Klafke. "Adaptive Monte Carlo algorithm to global radio resources optimization in H-CRAN." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/169922.

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Até 2020 espera-se que as redes celulares aumentam em dez vezes a área de cobertura, suporte cem vezes mais equipamentos de usuários e eleve a capacidade da taxa de dados em mil vezes, comparada as redes celulares atuais. A densa implantação de pequenas células é considerada uma solução promissora para alcançar essas melhorias, uma vez que aproximar as antenas dos usuários proporciona maiores taxas de dados, devido à qualidade do sinal em curtas distâncias. No entanto, operar um grande número de antenas pode aumentar significativamente o consumo de energia da infraestrutura de rede. Além disso, a grande inserção de novos rádios pode ocasionar maior interferência espectral entre as células. Nesse cenário, a gestão dos recursos de rádio é essencial devido ao impacto na qualidade do serviço prestado aos usuários. Por exemplo, baixas potências de transmissão podem deixar usuários sem conexão, enquanto altas potências elevam a possibilidade de ocorrência de interferência. Além disso, a reutilização não planejada dos recursos de rádio causa a ocorrência de interferência, resultando em baixa capacidade de transmissão, enquanto a subutilização de recursos limita a capacidade total de transmissão de dados. Uma solução para controlar a potência de transmissão, atribuir os recursos de rádio e garantir o serviço aos usuários é essencial. Nesta dissertação, é proposto um algoritmo adaptativo de Monte Carlo para realizar alocação global de recursos de forma eficiente em termos de energia, para arquiteturas Heterogeneous Cloud Radio Access Network (H-CRAN), projetadas como futuras redes de quinta geração (5G). Uma solução eficiente para a alocação de recursos em cenários de alta e baixa densidade é proposta. Nossas contribuições são triplas: (i) proposta de uma abordagem global para o problema de atribuição de recursos de rádio na arquitetura HCRAN, cujo caráter estocástico garante uma amostragem geral de espaço de solução; (ii) uma comparação crítica entre nossa solução global e um modelo local; (iii) a demonstração de que, para cenários de alta densidade, a Eficiência Energética não é uma medida adequada para alocação eficiente, considerando a capacidade de transmissão, justiça e total de usuários atendidos. Além disso, a proposta é comparada em relação a três algoritmos de alocação de recursos de última geração para redes 5G.
Up until 2020 it is expected that cellular networks must raise the coverage area in 10-fold, support a 100-fold more user equipments, and increase the data rate capacity by a 1000-fold in comparison with current cellular networks. The dense deployment of small cells is considered a promising solution to reach such aggressive improvements, once it moves the antennas closer to the users, achieving higher data rates due to the signal quality at short distances. However, operating a massive number of antennas can significantly increase the energy consumption of the network infrastructure. Furthermore, the large insertion of new radios brings greater spectral interference between the cells. In this scenery, the optimal management of radio resources turn an exaction due to the impact on the quality of service provided to the users. For example, low transmission powers can leave users without connection, while high transmission powers can contribute to inter radios interference. Furthermore, the interference can be raised on the unplanned reuse of the radio resources, resulting in low data transmission per radio resource, as the under-reuse of radio resources limits the overall data transmission capacity. A solution to control the transmission power, assign the spectral radio resources, and ensure the service to the users is essential. In this thesis, we propose an Adaptive Monte Carlo algorithm to perform global energy efficient resource allocation for Heterogeneous Cloud Radio Access Network (HCRAN) architectures, which are forecast as future fifth-generation (5G) networks. We argue that our global proposal offers an efficient solution to the resource allocation for both high and low density scenarios. Our contributions are threefold: (i) the proposal of a global approach to the radio resource assignment problem in H-CRAN architecture, whose stochastic character ensures an overall solution space sampling; (ii) a critical comparison between our global solution and a local model; (iii) the demonstration that, for high density scenarios, Energy Efficiency is not a well suited metric for efficient allocation, considering data rate capacity, fairness, and served users. Moreover, we compare our proposal against three state-of-the-art resource allocation algorithms for 5G networks.

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Amer, Asmaa. "Resource Allocation in NOMA-based cellular networks." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG089.

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Cette thèse vise à optimiser l'allocation des ressources au sein des systèmes NOMA, en particulier les systèmes NOMA coopératifs en liaison descendante, dans des configurations de stations de base à antenne unique et à antennes multiples. L'objectif est de maximiser l'efficacité spectrale et énergétique, tout en proposant des schémas NOMA plus efficaces qui peuvent tirer parti des avantages du NOMA et répondre aux limitations des schémas actuellement considérés en termes de consommation d'énergie et de complexité des récepteurs. Dans la première contribution, un système NOMA coopératif basé sur le découpage du réseau est étudié pour accueillir à la fois des utilisateurs cellulaires et des paires de dispositifs à dispositifs (D2D) répondant aux exigences de communication mobile large bande améliorée (eMBB) et de communication ultra fiable à faible latence (URLLC). Le problème d'optimisation est formulé comme une maximisation du débit total avec trois variables d'optimisation : le regroupement des utilisateurs NOMA, l'admission sous-jacente des D2D et l'allocation des blocs de ressources. Le problème est décomposé en trois sous-problèmes. Une solution algorithmique séquentielle est proposée, commençant par le regroupement des utilisateurs, suivie de l'allocation des blocs de ressources, et enfin de l'admission des D2D. Les sous-problèmes de regroupement des utilisateurs et d'admission des D2D sont résolus à l'aide d'une solution de théorie de correspondance de type plusieurs-à-un à faible complexité. Le problème d'allocation des blocs de ressources est résolu par une approche heuristique. Dans la deuxième contribution, nous revisitons le compromis entre l'accès des utilisateurs et la complexité de l'annulation d'interférence successive (SIC) des récepteurs NOMA. À mesure que davantage d'utilisateurs partagent les mêmes ressources, l'interférence et la complexité de la SIC augmentent. Contrairement aux schémas NOMA conventionnels basés sur des paires, nous proposons un schéma NOMA coopératif chevauchant, où chaque utilisateur en bord de cellule peut partager des ressources avec plusieurs utilisateurs au centre de la cellule, même si les utilisateurs au centre de la cellule utilisent des ressources orthogonales entre eux. Cette approche améliore la connectivité des utilisateurs, renforce les performances des utilisateurs en bord de cellule et maintient une faible complexité de SIC. Le problème est formulé comme une maximisation de la satisfaction des Qualité de Service (QoS) des utilisateurs en bord de cellule et est résolu à l'aide d'un algorithme de théorie de correspondance de type plusieurs-à-plusieurs avec des stratégies d'échange et d'ajout/suppression. Dans la troisième contribution de la thèse, nous proposons un système hybride d'accès multiple par division spatiale (SDMA)/NOMA, pour s'adapter entre les utilisateurs accédant par NOMA et SDMA en fonction de leur consommation d'énergie. Dans le modèle de consommation d'énergie, contrairement à la littérature NOMA où la puissance est induite par les unités SIC au niveau du récepteur est négligée, nous introduisons un modèle de consommation d'énergie dynamique basé sur la puissance SIC. Le problème est formulé comme une maximisation de l'efficacité énergétique en optimisant la sélection du mode d'accès multiple, le beamforming de la station de base et l'allocation de puissance des utilisateurs. Cette approche empêche une surestimation de l'efficacité énergétique, entraînant une réduction de l'écart entre l'analyse théorique et la conception du système, ce qui est particulièrement critique pour les dispositifs NOMA contraints par l'énergie. Le problème est résolu en utilisant des approches d'approximation convexe successive (SCA), de programmation par différences convexes (DC) et de programmation semi-définie (SDP)
This thesis aims to optimize resources allocation within NOMA systems, particularly downlink cooperative NOMA systems, within single-antenna and multiple antenna base station (BS) configurations. This aims to maximize spectral and energy efficiency, and to propose more efficient NOMA schemes that can reap benefits of NOMA and address the limitations of currently considered NOMA schemes, in terms of power consumption and receiver complexity. In the first contribution, a network-slicing-based cooperative NOMA based system is investigated to accommodate both cellular users and device-to-device (D2D) pairs with enhanced mobile broadband (eMBB) and Ultra reliable low latency communication (URLLC) services requirements. The optimization problem is formulated as sum-throughput maximization with three optimization variables: NOMA-users clustering, underlying D2D- admission, and resource blocks (RBs) allocation. The problem is decoupled into three sub-problems. A sequential algorithmic solution is proposed, starting by users clustering, followed by RBs allocation, and finally D2D admission. The users clustering and D2D admission sub-problems are solved using low-complexity many-to-one matching theory solution. The RBs allocation problem is solved using heuristics approach. In the second contribution, we revisit the trade-off between user access and the successive interference cancellation (SIC) complexity of NOMA receivers. As more users share the same resources, interference and SIC complexity escalate. Unlike conventional pairing-based NOMA schemes, we propose an overlapping cooperative NOMA scheme where each cell-edge user can share resources with multiple cell-center users, even if cell-center users are using orthogonal resources between each other. This approach enhances user connectivity, improves cell-edge user performance, and maintains low SIC complexity. The problem is formulated as maximization of Quality-of-Service (QoS) satisfaction of cell-edge users, and is solved using a many-to-many matching theory algorithm with swapping and add/remove strategies. In the third thesis contribution, we propose a hybrid Space Division Multiple Access (SDMA)/NOMA system, to adapt the multiple access mode, either NOMA or SDMA, based on the power consumption. In the power consumption model, unlike NOMA literature, where power induced by SIC units at the receiver is overlooked, we introduce dynamic power consumption model based on the SIC power. The problem is formulated as maximizing energy efficiency by optimizing the multiple access mode selection, BS beamforming, and user power allocation. This approach prevents overestimation of energy efficiency, consequently, avoids gaps between its theoretical evaluation and practical system design, an aspect particularly critical for energy-constrained NOMA devices. The problem is solved using successive convex approximation (SCA), difference of convex (DC) programming and semidefinite programming (SDP) approaches

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Masmoudi, Raouia. "Télécommunications domotiques efficaces en termes de consommation d’énergie." Thesis, Cergy-Pontoise, 2015. http://www.theses.fr/2015CERG0791.

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Le spectre électromagnétique est une ressource limitée dont l'usage doit être optimisé. Plusieurs travaux actuels visent à améliorer l'utilisation des fréquences radio en exploitant les méthodes de traitement intelligent du signal : la radio cognitive. Cette thèse se place dans ce contexte. Concrètement, nous considérons un problème d'allocation conjointe de spectre et de puissance dans un système radio cognitif (CR) composé de plusieurs utilisateurs secondaires (SUs) et primaires (PUs). L'objectif est d'optimiser l'efficacité énergétique des SUs tout en garantissant des niveaux d'interférences maximales imposés par la présence des PUs. Nous analysons des métriques d'efficacité énergétique en utilisant un cadre unificateur basé sur des outils d'optimisation convexe multi-critères. Les métriquesque nous étudions sont : la maximisation de débit avec pénalité sur l'interférence créée, le ratio débit puissance totale et la minimisation de puissance sous contrainte de débit pour concevoir un système de communications efficace en termes de consommation. Nous approfondissons ensuite l'étude de la métrique de minimisation de puissances sous contraintes de débits minimaux aux SUs et d'interférences maximales aux PUs. Étant donné la nature opposée de ces contraintes, nous étudions d'abord la faisabilité du problème et nous proposons des conditions nécessaires et des conditions suffisantes pour l'existence d'une solution. Le défi principal réside dans la non-convexité du problème d'allocation conjointe de spectre et de puissance en raison du paramètre discret d'ordonnancement des SUs. Afin de surmonter ce challenge, nous utilisons une technique de relaxation de Lagrange pour résoudre un problème convexe. Nous prouvons que les solutions discrètes du problème relaxé sont les solutions du problème initial. Lorsqu'une solution existe, nous proposonsun algorithme itératif basé sur la méthode de sous-gradient pour calculer la solution optimale. Nous montrons que le scheduling optimal est plus efficace comparé avec d'autres allocations de spectre classiques (e.g. entrelacée, blockwise). Dans le cas particulier de deux bandes orthogonales et un SU unique, nous proposons une solution analytique qui ne nécessite pas d'algorithme itératif
The radio spectrum is a limited resource which must be used in an optimal way. Recent works in the literature aim to improve the use of radio frequencies by exploiting intelligent techniques from signal processing, such as the cognitive radio paradigm. In this thesis, we study a joint spectrum scheduling and power allocation problem in a Cognitive Radio (CR) system composed of several secondary users (SUs) and primary users (PUs). The objective is to optimize the energy efficiency of the SUs while guaranteeing that the interference created to the PUs is kept below a maximum tolerated level. We analyze energy efficiency metrics in wireless communications using a common unifying framework based on convex multi-criteria optimization tools, which includes the three of the most popular energyefficiency metrics in the literature : weighted difference between overall achievable rate and power consumption, the ratio between the overall rate and consumed power and overall consumed power under minimum rate constraint. Then, we further focus on the study of the opportunistic power minimization problem over several orthogonal frequency bands under constraints on the minimum Quality of Service (QoS) and maximum interference to the PUs. Given the opposing nature of these constraints, we first study the feasibility of the problem and we provide sufficient conditions and necessary conditions that guarantee the existence of a solution. The main challenge lies in the non-convexity of the joint spectrum and power allocation problem due to the discrete spectrum scheduling parameter of SUs. To overcome this issue, we use a Lagrangian relaxation technique to solve a convexproblem. We prove that the discrete solutions of the relaxed problem are the solutions of the initial problem. When a solution exists, we propose an iterative algorithm based on subgradient method to compute an optimal solution. We show that the optimal scheduling is more efficient compared to other conventional spectrum allocations (e.g. interlaced, blockwise). In the particular case of two orthogonal bands and an unique SU, we provide an analytical solution that does not require an iterative algorithm

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Suliman, I. M. (Isameldin Mohammed). "Performance analysis of cognitive radio networks and radio resource allocation." Doctoral thesis, Oulun yliopisto, 2016. http://urn.fi/urn:isbn:9789526212753.

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Abstract Cognitive radio (CR) is becoming a promising tool for solving the problem of the scarce radio resource and spectrum inefficiency. Spectrum sensing (signal detection) enables real-time detection of spectrum holes by unlicensed secondary users (SUs) in cognitive radio networks (CRNs). In this thesis, performance analysis of CRNs and radio resource allocation are considered. A continuous time Markov chain (CTMC) based analytical model taking into account all relevant elements as well as addressing the issue of the false alarm rate (FAR) associated with the continuous sensing is developed. In some cases, the PU can be modeled as time-slotted with constant state (transmitting or not) in each slot. In this case, assuming SU can synchronize to the slots, its intuitive to use beginning of a slot for sensing and rest (possibly) for communication. For this model, M/D/1 priority queueing scheme has been applied in this thesis to find waiting time and queue length for PU and SU. Multiple access among SUs in a time-slotted channel is considered next. A conventional method is e.g. using a channel access probability ψ in each slot similar to the slotted ALOHA. A radically new idea is introduced in this thesis: why not increase the false alarm probability PFA of each SU and use it as a multiple access method? A game theoretic approach to radio resource allocation for the downlink capacity providing fair resource sharing among mobile nodes located along a multihop link is presented. Furthermore, the problem of resource allocations in heterogeneous wireless networks is also studied. Finally, device-to-device (D2D) communication - with localized distribution, where users tend to gather around some areas (clusters/hot-spots) within the cell such as buildings is studied. Theoretical analysis with two dimensional clustering is presented including cases with correlated clusters. Correlation in cluster selection is shown to significantly improve performance
Tiivistelmä Kognitiivinen radio (CR) on nousemassa lupaavaksi työkaluksi niukkojen radioresurssien ja spektrin käytön tehottomuuden ratkaisemisessa. Spektrin nuuskiminen (signaalin ilmaisu) mahdollistaa spektriaukkojen reaaliaikaisen tunnistamisen toissijaisten käyttäjien (SU) toimesta kognitiivisissa radioverkoissa (CRN). Tässä väitöskirjassa painotus on CRN verkkojen suorituskykyanalyysissa ja radioresurssien hallinnassa. Työssä kehitetään jatkuva-aikaiseen Markov ketjuun (CTMC) perustuva analyyttinen malli joka ottaa huomioon kaikki olennaiset asiat mukaan lukien jatkuva-aikaiseen spektrin nuuskimiseen liittyvän väärien hälytysten tiheyden (FAR). Joissakin tapauksissa PU:ta voidaan mallintaa aikajaoteltuna siten että PU:n tila on vakio kussakin aikavälissä. Olettaen että SU voi synkronoitua aikaväleihin, on intuitiivista käyttää aikavälin alkua nuuskimiselle ja loppuosaa (mahdollisesti) viestintää varten. M/D/1:n ensisijaisuus-jonotus-suunnitelmaa soveltamalla tässä väitöskirjassa saadaan tuloksia odotusajalle ja jonon pituudelle sekä SU:lle että PU:lle. Seuraavaksi käsitellään monikäyttöä SU:den joukossa aikajaotellussa kanavassa. Tavanomainen menetelmä käyttää esimerkiksi kanavapääsytodennäköisyyttä ψ kussakin aikavälissä vastaten aikajaoteltua ALOHA protokollaa. Tässä väitöskirjassa esitetään radikaali uusi idea: miksei lisätä väärän hälytyksen todennäköisyyttä kussakin SU:ssa ja käytetä sitä moniliittymämenetelmänä? Työssä esitetään peliteoreettinen lähestymistapa radioresurssien allokointiin siten että resurssit jaetaan oikeudenmukaisesti monen yhteysvälin linkeissä. Lisäksi tutkitaan myös resursoinnin ongelmaa heterogeenisissa langattomissa verkoissa. Lopuksi tutkitaan laitteiden välistä suoraa viestintää (D2D) paikallisen jakauman kanssa, jossa käyttäjillä on tapana kasaantua solun sisällä esim. rakennuksiin. Esitetään teoreettinen analyysi kaksiulotteisella klusteroinnilla myös korreloitujen ryhmien kanssa. Osoitetaan että korrelaatio ryhmän valinnassa parantavaa merkittävästi suorituskykyä

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Ellingsæter, Brage Høyland. "Cognitive Radio: Interference Management and Resource Allocation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for elektronikk og telekommunikasjon, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11295.

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In this thesis the performance of different cognitive systems are analyzed in different environments and scenarios. The main scenarios are: one cognitive and one primary user, multiple cognitive users and channels and multiple cognitive and primary users. With primary users in the vicinity, cognitive systems are evaluated both when no degradation to primary user QoS is allowed and when some degradation is allowed, measured by an outage probability. In all scenarios involving one or more primary users, the performance is evaluated over two phases. In Phase 1 the channel is idle, i.e. the primary users are silent, and in Phase 2 the primary users are active on the channel. One of the questions in this thesis is how can cognitive users transmit simultaneously with the primary user in Phase 2. Schemes that show that this is possible is presented and evaluated and performance is compared to a standard cognitive system only transmitting when the channel is idle.In scenarios with multiple cognitive users and channels, power allocation schemes are reviewed. A novel power allocation algorithm presented in cite{burr}, called modified water filling in this thesis, is implemented and referenced against other well-known power allocation schemes.All implementation and simulations were done in MATLAB. It was assumed infinite processing power at all cognitive users, i.e. no processing delay, and perfect spectral sensing at all cognitive users. The results showed that the performance gain of cognitive system utilizing simultaneous transmission achieves only a slight performance gain over a standard cognitive system, when no degradation to primary user QoS is allowed. However, by allowing only a slight degradation in primary user QoS, the gain is significant and should be included in future work on cognitive radio as it shows a promising way to exploit spectra.

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Hashmi, Ziaul Hasan. "Dynamic resource allocation for cognitive radio systems." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/961.

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Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems. Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the network considers the fairness criterion. We study the dynamic spectrum sharing problem for device coordinated cognitive radio networks with respect to fairness. We propose a simple modified proportional fair algorithm for a dynamic spectrum sharing scenario with two constraints, time and utility. Utility is measured by the amount of data processed and time is measured as the duration of a slot. This algorithm could result in variable or fixed length time slots. We will discuss the several controls possible on the algorithm and the possible extension of this algorithm for multicarrier OFDM based CR systems. Traditional water-filling algorithm is inefficient for OFDM-CR networks due to the interaction with primary users (PU)s. We consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. We discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them. Finally we extend this model for interference-limited OFDM-CR systems.

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Wong, Chung Kit. "Resource allocation for multihop packet radio networks." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68059.

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This thesis focuses on the routing, power control and channel allocation of Packet Radio Network (PRnet) with multiple channels. The Nearest Forward with Progress (NFP) routing policy is known to achieve higher throughput in the single channel setting than the Most Forward with Progress (MFP) strategy. This observation motivates our work on the variant of the Shacham/King model in which MFR is replaced by NFP in a multi-channel case. The resulting network shows that the superiority of NFP relative to MFP persists. Another way to improve network performance is to control the network topology by restricting the set of possible paths. Pairwise Channel Assignment (PCA), which assigns the different channels to the restricted paths, is modified so as to expand its applicability and reduce its computational burden without significant loss of throughput. The performance evaluations are based on a combination of analysis and simulation.

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Ngo, Duy. "Radio resource allocation for wireless heterogeneous networks." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119622.

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By deploying small cells (i.e., femtocells) within the same service area of regular macrocells, a much higher area spectral efficiency, better indoor coverage, and significant mobile data offloading can be achieved at low cost. Because femtocells reuse the radio spectrum already assigned to macrocells in an uncoordinated fashion, new cell boundaries are created and the signal interference situation becomes far more unpredictable than in conventional networks. In this heterogeneous network setting, adaptive power allocation and dynamic spectrum access are needed to ensure a harmonized coexistence of network entities with diverse design specifications. Since femtocells are deployed by end users without any network planning, autonomous solutions are desirable to effectively control the severe intra-tier and cross-tier interferences. In this study, we develop and evaluate distributed radio resource allocation algorithms for wireless heterogeneous networks employing code-division multiple access (CDMA) and orthogonal frequency division multiple access (OFDMA). Requiring no central coordination, the devised solutions robustly protect the ongoing operation of all existing macrocell users, while optimally exploiting the residual network capacity for femtocells. In CDMA-based networks, we propose a dynamic pricing scheme combined with femtocell user admission control to indirectly manage the cross-tier interference. The proposed joint power and admission control algorithms can be locally executed at each link to offer a maximum utility to individual users. For the total network utility maximization, we develop joint Pareto-optimal power control and signal-to-interference-plus-noise ratio (SINR) assignment algorithms that can fairly share radio resources among users. Upon applying convex optimization methods, the minimum SINRs prescribed by macrocell users are effectively enforced, whereas the sum network utility is globally maximized. In OFDMA-based networks, to resolve the highly nonconvex and combinatorial problem of joint power and subchannel allocation, we propose a dynamic spectrum management scheme that alternatively optimizes the powers and assigns the subchannels. With the adopted successive convex approximation approach, the total throughput of all femtocells is maximized whilst the macrocell network capacity is always protected. In cognitive femtocells where femtocell users opportunistically access the spectrum licensed to macrocells, we apply Lagrangian duality to devise jointly optimal power and subchannel allocation algorithms. The distributed solutions are shown to achieve their global optimality with low complexity.
En déployant de petites cellules (dénommées les femtocells) au sein de la même zone de service que les cellules de tailles régulières (dénommées cellules macro), une efficacité spectrale zone beaucoup plus élevé, une meilleure couverture à l'intérieur, et d'importantes données mobiles de déchargement entre les deux cellules peuvent être réalisé tout en gardant faible coût. Vu que les femtocells réutilisent le spectre de fréquence déjà consacré à la cellule macro, auxquelles ils sont assignés, d'une manière non-coordonnée, de nouvelles limites de cellules sont créées et l'interférence devient beaucoup plus imprévisible que dans les réseaux traditionnels. Dans ce contexte réseau hétérogène, une allocation adaptative de puissance et des méthodes d'accès dynamiques au spectre sont nécessaires pour assurer une coexistence harmonisée des entités du réseau avec les nouvelles spécifications imposées par les femtocells. Depuis que les femtocells sont déployées par les terminaux sans aucune planification au préalable du réseau, des solutions qui s'adaptent automatiquement sont toujours désirable pour contrôler efficacement les sévères interférences entre les différents niveaux du réseau sans fil hétérogène.Dans cette étude, nous développons et évaluons des algorithmes distribués pour l'allocation de ressources radio dans les réseaux sans fil hétérogènes employant l accès multiple par répartition en code (CDMA) et Accès multiple par répartition en fréquence (OFDMA). En évitant une coordination centralisée, les solutions proposées protègent le fonctionnement de tous les utilisateurs de la cellule macro existantes, tout en exploitant de manière optimale la capacité résiduelle du réseau pour les utilisateurs du femtocells. Dans les réseaux CDMA, nous proposons un schéma de tarification dynamique associé à un contrôle d'admission des utilisateurs de la femtocell nous permettant de gérer indirectement l'interférence inter-niveaux (entre cellule macro et femtocell). Le contrôle simultané de la puissance et les algorithmes de contrôle d'admission proposés peut être exécuté localement sur chaque lien pour offrir un maximum d'utilité pour les utilisateurs individuels. Pour maximiser l'utilité totale du réseau, nous développons un algorithme de contrôle simultané de puissance basant sur l'optimalité de Pareto et le rapport signal sur interférence plus bruit (SINR) qui peut partager équitablement les ressources radio entre les utilisateurs. En appliquant d'une méthode d'optimisation, les SINR minimaux prescrits par les utilisateurs des cellules macro sont garantis, alors que le maximal global la somme de l'utilité du réseau est trouvé.Dans les réseaux OFDMA, afin de résoudre le problème non convexe et combinatoire de l'allocation conjointe de la puissance et des sous-porteuses, nous proposons un schéma alternatif de gestion dynamique du spectre qui optimise la distribution de puissance et des sous-porteuses. Avec l'approche par approximations successives convexe adoptée, le débit total de tous les femtocells est maximisé alors que la capacité du réseau de la cellule macro est toujours protégée. En femtocells cognitives où les utilisateurs du femtocell accèdent au spectre autorisé à la cellule macro d'une manière opportuniste, nous appliquons la dualité lagrangienne pour optimiser la distribution de la puissance et des sous-porteuses. Nous prouvons que les solutions distribuées proposées atteignent leur optimal global avec une faible complexité.

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Jin, Xin. "Resource allocation in multicarrier cognitive radio networks." Thesis, Evry, Institut national des télécommunications, 2014. http://www.theses.fr/2014TELE0014/document.

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Vu que la modulation multi-porteuses est largement utilisée dans les communications sans fil et la radio cognitive (CR pour “Cognitive Radio”) améliore l’utilisation des ressources radio et du spectre, nous nous concentrons sur les réseaux radio cognitifs (CR) pour faire progresser l’allocation des ressources, le routage, et l’ajustement de la puissance d’émission vers les récepteurs (synthèse de faisceaux ou beamforming) dans cette thèse. Nous étudions deux types de modulations multi-porteuses :Orthogonal Frequency-Division Multiplexing (OFDM) à base d’ondelettes (WOFDM pourWavelet OFDM) et OFDM dans sa forme classique ou traditionnelle (OFDM s’appuyant sur la transformation de Fourier pour partager les ressources). WOFDM adopte Wavelet Packet Modulation (WPM) pour obtenir des lobes secondaires beaucoup plus faibles dans la densité spectrale de puissance du signal transmis en comparaison à OFDM. WPM permet de surcroit à WOFDM de s’affranchir du Préfixe Cyclique (indispensable à OFDM) et d’exploiter l’égalisation pour combattre l’Interférence entre Symboles (ISI). Nous évaluons la performance de WOFDM sous différentes conditions du canal radio. Nous comparons la performance de WOFDM, qui s’appuie sur l’égalisation dans le domaine temporel, à celle de OFDM, qui requiert l’utilisation du Préfixe Cyclique et opère dans le domaine fréquentiel
In view of the wide usage of multicarrier modulation in wireless communications and the prominent contribution of Cognitive Radio (CR) to deal with critical shortage of spectrum resource, we focus on multicarrier based cognitive radio networks to investigate general resource allocation issues: subcarrier allocation, power allocation, routing, and beamforming in this thesis. We investigate two types of multicarrier modulation: Wavelet-based Orthogonal Frequency Division Multiplexing (WOFDM) and Fourier-based Orthogonal Frequency Division Multiplexing (OFDM). WOFDM adopts Wavelet Packet Modulation (WPM). Compared with fourier-based OFDM, wavelet-based OFDM achieves much lower side lobe in the transmitted signal. Wavelet-based OFDM excludes Cyclic Prefix (CP) which is used in fourier-based OFDM systems. Wavelet-based OFDM turns to exploit equalization to combat Inter-Symbol Interference (ISI). We evaluate the performance of WOFDM under different channel conditions. We compare the performance of wavelet-based OFDM using equalization in the time domain to that of fourier-based OFDM with CP and the equalization in the frequency domain

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12

Jin, Xin. "Resource allocation in multicarrier cognitive radio networks." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2014. http://www.theses.fr/2014TELE0014.

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Vu que la modulation multi-porteuses est largement utilisée dans les communications sans fil et la radio cognitive (CR pour “Cognitive Radio”) améliore l’utilisation des ressources radio et du spectre, nous nous concentrons sur les réseaux radio cognitifs (CR) pour faire progresser l’allocation des ressources, le routage, et l’ajustement de la puissance d’émission vers les récepteurs (synthèse de faisceaux ou beamforming) dans cette thèse. Nous étudions deux types de modulations multi-porteuses :Orthogonal Frequency-Division Multiplexing (OFDM) à base d’ondelettes (WOFDM pourWavelet OFDM) et OFDM dans sa forme classique ou traditionnelle (OFDM s’appuyant sur la transformation de Fourier pour partager les ressources). WOFDM adopte Wavelet Packet Modulation (WPM) pour obtenir des lobes secondaires beaucoup plus faibles dans la densité spectrale de puissance du signal transmis en comparaison à OFDM. WPM permet de surcroit à WOFDM de s’affranchir du Préfixe Cyclique (indispensable à OFDM) et d’exploiter l’égalisation pour combattre l’Interférence entre Symboles (ISI). Nous évaluons la performance de WOFDM sous différentes conditions du canal radio. Nous comparons la performance de WOFDM, qui s’appuie sur l’égalisation dans le domaine temporel, à celle de OFDM, qui requiert l’utilisation du Préfixe Cyclique et opère dans le domaine fréquentiel
In view of the wide usage of multicarrier modulation in wireless communications and the prominent contribution of Cognitive Radio (CR) to deal with critical shortage of spectrum resource, we focus on multicarrier based cognitive radio networks to investigate general resource allocation issues: subcarrier allocation, power allocation, routing, and beamforming in this thesis. We investigate two types of multicarrier modulation: Wavelet-based Orthogonal Frequency Division Multiplexing (WOFDM) and Fourier-based Orthogonal Frequency Division Multiplexing (OFDM). WOFDM adopts Wavelet Packet Modulation (WPM). Compared with fourier-based OFDM, wavelet-based OFDM achieves much lower side lobe in the transmitted signal. Wavelet-based OFDM excludes Cyclic Prefix (CP) which is used in fourier-based OFDM systems. Wavelet-based OFDM turns to exploit equalization to combat Inter-Symbol Interference (ISI). We evaluate the performance of WOFDM under different channel conditions. We compare the performance of wavelet-based OFDM using equalization in the time domain to that of fourier-based OFDM with CP and the equalization in the frequency domain

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13

Lessinnes, Mathieu. "Resource allocation for cooperative cognitive radios." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209352.

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Resource allocation consists in allocating spectrum and power on every link of a network, possibly under power and rate requirements. In the context of cognitive radios, almost 15 years of research produced an impressive amount of theoretical contributions, exploring a wide range of possibilities. However, despite the ever-growing list of imaginable scenarios, we observe in Chapter 2 that most of these studies are based on similar working hypotheses. Our first contribution is to challenge some of these hypotheses, and propose a novel resource allocation scheme. Sticking to realistic assumptions, we show how our scheme reduces both computational complexity and control traffic, compared to other state-of-the-art techniques.

Due to a majority of the abovementioned studies making some constraining assumptions, realistic system designs and experimental demonstrations are much more quiet and unharvested fields. In an effort to help this transition from theory to practice, our second contribution is a four-nodes cognitive network demonstrator, presented in Chapter 3. In particular, we aim at providing a modular platform available for further open collaboration: different options for spectrum sensing, resource allocation, synchronisation and others can be experimented on this demonstrator. As an example, we develop a simple protocol to show that our proposed resource allocation scheme is fully implementable, and that primary users can be avoided using our approach.

Chapter 4 aims at removing another working hypothesis made when developping our resource allocation scheme. Indeed, resource alloca- tion is traditionally a Media Access Control (MAC) layer problem. This means that when solving a resource allocation problem in a network, the routing paths are usually assumed to be known. Conversely, the routing problem, which is a network layer issue, usually assumes that the available capacities on each link of the network (which depend on resource allocation) are known. Nevertheless, these two problems are mathematically entangled, and a cross-layer allocation strategy can best decoupled approaches in several ways, as we discuss in Chapter 4. Accordingly, our third and last contribution is to develop such a cross-layer allocation scheme for the scenario proposed in previous chapters.

All conclusions are summarised in Chapter 5, which also points to a few tracks for future research.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

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Yoon, Suk-Un. "Dynamic Radio Resource Allocation in Wireless Sensor and Cognitive Radio Networks." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1259768264.

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Kibria, Mirza Golam. "Radio Resource Allocation Optimization for Cellular Wireless Networks." 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/189689.

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Zhang, Yonghong. "Resource allocation for OFDM-based cognitive radio systems." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2828.

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Cognitive radio (CR) is a novel wireless communication approach that may alleviate the looming spectrum-shortage crisis. Orthogonal frequency division multiplexing (OFDM) is an attractive modulation candidate for CR systems. In this thesis, we study resource allocation (RA) for OFDM-based CR systems using both aggressive and protective sharing. In aggressive sharing, cognitive radio users (CRUs) can share both non-active and active primary user (PU) bands. We develop a model that describes aggressive sharing, and formulate a corresponding multidimensional knapsack problem (MDKP). Low-complexity suboptimal RA algorithms are proposed for both single and multiple CRU systems. A simplified model is proposed which provides a faster suboptimal solution. Simulation results show that the proposed suboptimal solutions are close to optimal, and that aggressive sharing of the whole band can provide a substantial performance improvement over protective sharing, which makes use of only the non-active PU bands. Although aggressive sharing generally yields a higher spectrum-utilization efficiency than protective sharing, aggressive sharing may not be feasible in some situations. In such cases, sharing only non-active PU bands is more appropriate. When there are no fairness or quality of service (QoS) considerations among CRUs, both theoretical analysis and simulation results show that plain equal power allocation (PEPA) yields similar performance as optimal power allocation in a multiuser OFDM-based CR system. We propose a low-complexity discrete bit PEPA algorithm. To improve spectrum-utilization efficiency, while considering the time-varying nature of the available spectrum as well as the fading characteristics of wireless communication channels and providing QoS provisioning and fairness among users, this thesis introduces the following novel algorithms: (1) a distributed RA algorithm that provides both fairness and efficient spectrum usage for ad hoc systems; (2) a RA algorithm for non-real-time (NRT) services that maintains average user rates proportionally on the downlink of multiuser OFDM-based CR systems; and (3) cross-layer RA algorithms for the downlink of multiuser OFDM-based CR systems for both real-time (RT) services and mixed (RT and NRT) services. Simulation results show that the proposed algorithms provide satisfactory QoS to all supported services and perform better than existing algorithms designed for multiuser OFDM systems.

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Awoyemi, Babatunde Seun. "Resource allocation optimisation in heterogeneous cognitive radio networks." Thesis, University of Pretoria, 2017. http://hdl.handle.net/2263/61327.

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Cognitive radio networks (CRN) have been tipped as one of the most promising paradigms for next generation wireless communication, due primarily to its huge promise of mitigating the spectrum scarcity challenge. To help achieve this promise, CRN develop mechanisms that permit spectrum spaces to be allocated to, and used by more than one user, either simultaneously or opportunistically, under certain preconditions. However, because of various limitations associated with CRN, spectrum and other resources available for use in CRN are usually very scarce. Developing appropriate models that can efficiently utilise the scarce resources in a manner that is fair, among its numerous and diverse users, is required in order to achieve the utmost for CRN. 'Resource allocation (RA) in CRN' describes how such models can be developed and analysed. In developing appropriate RA models for CRN, factors that can limit the realisation of optimal solutions have to be identified and addressed; otherwise, the promised improvement in spectrum/resource utilisation would be seriously undermined. In this thesis, by a careful examination of relevant literature, the most critical limitations to RA optimisation in CRN are identified and studied, and appropriate solution models that address such limitations are investigated and proffered. One such problem, identified as a potential limitation to achieving optimality in its RA solutions, is the problem of heterogeneity in CRN. Although it is indeed the more realistic consideration, introducing heterogeneity into RA in CRN exacerbates the complex nature of RA problems. In the study, three broad classifications of heterogeneity, applicable to CRN, are identified; heterogeneous networks, channels and users. RA models that incorporate these heterogeneous considerations are then developed and analysed. By studying their structures, the complex RA problems are smartly reformulated as integer linear programming problems and solved using classical optimisation. This smart move makes it possible to achieve optimality in the RA solutions for heterogeneous CRN. Another serious limitation to achieving optimality in RA for CRN is the strictness in the level of permissible interference to the primary users (PUs) due to the activities of the secondary users (SUs). To mitigate this problem, the concept of cooperative diversity is investigated and employed. In the cooperative model, the SUs, by assisting each other in relaying their data, reduce their level of interference to PUs significantly, thus achieving greater results in the RA solutions. Furthermore, an iterative-based heuristic is developed that solves the RA optimisation problem timeously and efficiently, thereby minimising network complexity. Although results obtained from the heuristic are only suboptimal, the gains in terms of reduction in computations and time make the idea worthwhile, especially when considering large networks. The final problem identified and addressed is the limiting effect of long waiting time (delay) on the RA and overall productivity of CRN. To address this problem, queueing theory is investigated and employed. The queueing model developed and analysed helps to improve both the blocking probability as well as the system throughput, thus achieving significant improvement in the RA solutions for CRN. Since RA is an essential pivot on which the CRN's productivity revolves, this thesis, by providing viable solutions to the most debilitating problems in RA for CRN, stands out as an indispensable contribution to helping CRN realise its much-proclaimed promises.
Thesis (PhD)--University of Pretoria, 2017.
Electrical, Electronic and Computer Engineering
PhD
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Tsimba, Hilary Mutsawashe. "Queueing based resource allocation in cognitive radio networks." Diss., University of Pretoria, 2005. http://hdl.handle.net/2263/66250.

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With the increase in wireless technology devices and mobile users, wireless radio spectrum is coming under strain. Networks are becoming more and more congested and free usable spectrum is running out. This creates a resource allocation problem. The resource, wireless spectrum, needs to be allocated to users in a manner such that it is utilised efficiently and fairly. The objective of this research is to find a solution to the resource allocation problem in radio networks, i.e to increase the efficiency of spectrum utilisation by making maximum use of the spectrum that is currently available through taking advantage of co-existence and exploiting interference limits. The solution proposed entails adding more secondary users (SU) on a cognitive radio network (CRN) and having them transmit simultaneously with the primary user. A typical network layout was defined for the scenario. The interference temperature limit (ITL) was exploited to allow multiple SUs to share capacity. Weighting was applied to the SUs and was based on allowable transmission power under the ITL. Thus a more highly weighted SU will be allowed to transmit at more power. The weighting can be determined by some network-defined rule. Specific models that define the behaviour of the network were then developed using queuing theory, specifically weighted processor sharing techniques. Optimisation was finally applied to the models to maximize system performance. Convex optimization was deployed to minimize the length of the queue through the power allocation ratio. The system was simulated and results for the system performance obtained. Firstly, the performance of the proposed models under the processor-sharing techniques was determined and discussed, with explanations given. Then optimisation was applied to the processor-sharing results and the performance was measured. In addition, the system performance was compared to other existing solutions that were deemed closest to the proposed models.
Dissertation (MEng)--University of Pretoria, 2017.
Electrical, Electronic and Computer Engineering
MEng
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Batista, Rodrigo Lopes. "Radio resource allocation for coordinated multi-point systems." reponame:Repositório Institucional da UFC, 2011. http://www.repositorio.ufc.br/handle/riufc/10836.

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BATISTA. R. L. Radio resource allocation for coordinated multi-point systems. 2011 74 f. Dissertação (Mestrado em Engenharia de Teleinformática) - Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2011.
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The International Telecommunications Union (ITU) established through the International Mobile Telecommunications (IMT)-Advanced a set of requirements for high performance of 4th Generation (4G) communication systems and, with the aim of meeting such requirements, 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) is considering a set of enhancements, referred to as LTE-Advanced. In the LTE-Advanced context, Coordinated Multi-Point (CoMP) communication appears as a promising technology to boost system throughput and to allow for an efficient Radio Resource Allocation (RRA). CoMP systems promise very high performance in terms of spectral efficiency and coverage benefits when perfect Channel State Information (CSI) is available at the transmitter. However, perfect CSI is difficult to obtain in CoMP systems due to an increased number of channel parameters to be estimated at the receiver and to be fed back to the transmitter. So, the performance of such systems is compromised when the CSI is not perfectly known during CoMP processing, which is an important problem to be addressed. Space Division Multiple Access (SDMA) grouping algorithms are usually employed in order to find a suitable set of users for spatial multiplexing. The largest SDMA group is not always the best group in a given data transmission such that higher gains might be achieved by dynamically adjusting the SDMA group size. Besides, algorithms that balance the Signal to Interference-plus-Noise Ratio (SINR) among different links might ensure a certain level of link quality and so provide a more reliable communication for the scheduled users. This master thesis provides system-level analyses for RRA algorithms that exploit coordination in the downlink of CoMP systems to implement adaptive resource reuse and so improve system throughput. Herein, RRA strategies which consider dynamic SDMA grouping, joint precoding and power allocation for SINR balancing are studied in CoMP systems assuming imperfect CSI in order to obtain a better approximation with regard to the real-world implementations. It is shown through system-level analyses that quite high throughput gains are achieved through intelligent RRA. In conclusion, the results show that Sequential Removal Algorithms (SRAs) and SINR balancing provide system spectral efficiency gains. However, a critical degradation on the performance of these RRA strategies due to imperfect CSI is also shown.
A União Internacional para Telecomunicações (ITU) estabeleceu através da iniciativa para o Sistema Avançado Internacional de Telecomunicações Móveis (IMT-Advanced), um conjunto de requisitos de alto desempenho para os sistemas de comunicação de quarta geração (4G) e, com o objetivo de atender tais requisitos, a Evolução de Longo Prazo (LTE) do Projeto de Parceria para a Terceira Geração (3GPP) está considerando um conjunto de melhorias, referidas como LTE-Avançado. No contexto do LTE-Avançado, a comunicação multi-ponto coordenada (CoMP) aparece como uma tecnologia promissora para aumentar a vazão do sistema e permitir uma Alocação de Recursos de Rádio (RRA) eficiente. Os sistemas CoMP prometem alto desempenho em termos de eficiência espectral e benefícios de cobertura quando a Informação do Estado do Canal (CSI) perfeita está disponível no transmissor. No entanto, CSI perfeita é difícil de se obter em sistemas CoMP devido a um alto número de parâmetros de canal a serem estimados no receptor e enviados para o transmissor. Assim, o desempenho de tais sistemas é comprometido quando a CSI não é perfeitamente conhecida durante o processamento CoMP tal que esse é um problema importante a ser abordado. Algoritmos de agrupamento para Múltiplo Acesso por Divisão no Espaço (SDMA) geralmente são utilizados a fim de encontrar um conjunto adequado de usuários para multiplexação espacial. O maior grupo SDMA nem sempre é o melhor grupo em uma transmissão de dados tal que maiores ganhos podem ser obtidos ajustando dinamicamente o tamanho do grupo SDMA. Além disso, os algoritmos que balanceiam a Razão Sinal-Interferência mais Ruído (SINR) entre diferentes canais podem garantir um certo nível de qualidade de canal e assim proporcionar uma comunicação mais confiável para os usuários agrupados. Esta dissertação de mestrado fornece análises em nível sistêmico para algoritmos de RRA que exploram a coordenação no enlace direto de sistemas CoMP para implementar reuso adaptativo de recursos e assim melhorar o desempenho do sistema. São estudadas aqui estratégias de RRA em sistemas CoMP que consideram agrupamento SDMA dinâmico, precodificação e alocação de potência conjuntas para balanceamento de SINR, sendo assumida CSI imperfeita a fim de conseguir maior aproximação com relação às implementaçõs em cenários reais. É mostrado através de análises em nível sistêmico que ganhos de vazão bastante altos são alcançados através de RRA inteligente. Em conclusão, os resultados mostram que Algoritmos de Remoção Sequencial (SRAs) e de balanceamento de SINR proporcionam ganhos de eficiência espectral do sistema. No entanto, é também mostrada uma degradação crítica no desempenho dessas estratégias de RRA devido à CSI imperfeita.

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Claudino, Lucas dos Santos Araujo. "Cognitive radio : spectrum sensing and optimal resource allocation." Universidade Estadual de Londrina. Centro de Tecnologia e Urbanismo. Programa de Pós-Graduação em Engenharia Elétrica, 2018. http://www.bibliotecadigital.uel.br/document/?code=vtls000218384.

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Redes de Rádio Cognitivo constituem uma tecnologia recente que busca fazer o uso otimizado do espectro de frequências, que jáestá super-utilizado. Essa tecnologia oferece meios para portadores de licensa compartilhar sua banda de frequências com outros usuários para possibilitar o uso eficiente e também recerber certos benefícios em troca, como descontos ou aumento do tempo de validade da licensa. Dado que essa tecnologia é relativamente recente, os seus estudos estão ainda incompletos e precisam de uma pesquisa mais aprofundada. A fim de contribuir com a literatura, este trabalho trás importantes contrubuições para diferentes áreas do Rádio Cognitivo. Primeiramente, várias técnicas de sensoriamento espectral como Filtro Casado, Sensor de Energia, Sensor de Razão de Hadamard ou Sensor de Valor Absoluto de Covariância são analisados. Todos esses detectores são estudados e comparados de modo a oferecer ao leitor uma ampla visão sobre todas suas características, fraquezas e pontos fortes. Após esse estudo, o sensor mais promissor é escolhido para ser aplicado em um cenário realístico de transmissão sem fio. Escolheu-se o sensor de Razão de Hadamard, dado sua capacidade de prover altas taxas de detecção, baixa detecção errada ou alarme falso com um número necessário de amostras relativamente baixo. A segunda parte desta Dissertação é baseada em técnicas de otimização não linear que buscam maximizar a soma das capacidades de uma rede de rádio cognitivo. Uma MISO-CRN (Multiple-Input Multiple-Output Cognitive Radio Network) foi escolhida como arquitetura de aplicação e sua otimização foi divida em duas partes: cancelamento de interferência e alocação de potência. Essa técnica é conhecida como Zero Forcing-Water Filing, e alcança a capacidade máxima de transmissão sob certas configurações de sistema e canal. Além disso, esta pesquisa desenvolveu também uma aproximação prática para encontrar o número ótimo de usuários secundários ativos que proporcione a máxima capacidade da rede. Essa é uma ferramenta muito útil, uma vez que pode prover uma maneira simples de escolha do número permitido de usuários secundários para um certo cenário. Finalmente, técnicas de estimativa de canal aplicadas a redes de rádio cognitivo são estudadas. A transmissão completa em banda-base equivalente é descrita, a qual inclui a transmissão de sequência piloto, a estimativa da matriz de canal e uso dessa estimativa para gerar a matriz ótima de precodificação. Além disso, analisou-se o efeito da estimativa imperfeita do canal no sistema de transmissão com precodificação, na tentativa de se encontrar técnicas para superar esses problemas e melhorar o desempenho do sistema de comunicação com múltiplas antenas.
Cognitive Radio Network is a recent and emerging technology that aims to optimally use the already overcrowded frequency spectrum. This technology offers means for license-holders to share their spectrum bandwidth with other users, in order to make an efficient use of it and also receive some benefits, like payback or increase in license time. Once this is a recent technology, many studies are still incomplete and need furthers research. Ir order to contribute with the literature, this work brings some important research of a few different parts of Cognitive Radio. Firstly, various spectrum sensing techniques, such as Matched Filter, Energy Sensing, Hadamard Ratio Sensor or Covariance Absolute Value Detector are analyzed. All those sensors are studied and compared, in order to give a broad overview about its characteristics, strengths and weaknesses. After this study, the most promising detector is chosen to be applied into realistic wireless channels. The Hadamard Ratio Sonsor has been chosen, given its capacity of providing high detection rates, low miss detection or false alarm with a relatively low number of samples. The second part is based on non-linear optimization techniques and aims to maximize the sum capacity of a cognitive radio network. A MISO-CRN was chosen as target architecture, and the optimization was divided into two parts: power allocation and interference nulling. This technique is known as Zero Forcing-Water Filing strategy, which achieves maximum sum capacity under certain system and channel configurations. Also, this research came up with a practical approximation to find out the optimum number of active secondary users to achieve maximum capacity. This is a very useful tool, once it can provide an easy way of choosing the allowed number of SUs for a given configuration of number of antennas at the base station and link quality (related to signal to interference plus noise ratio). Finally, channel estimation techniques applied to cognitive radio networks are analyzed. A complete base-band transmission is described, which includes pilot sequence transmission, channel matrix estimation and optimal precoder matrix generation based on channel estimative. Also, the effect of imperfect channel estimation has been studied to provide means of developing techniques to overcome possible problems and enhance the MIMO communication performance

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21

Akter, Lutfa. "Modeling, forecasting and resource allocation in cognitive radio networks." Diss., Manhattan, Kan. : Kansas State University, 2010. http://hdl.handle.net/2097/3892.

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Dybdahl, Sigbjørn Hernes. "Radio Resource Allocation for Increased Capacity in Cellular Networks." Thesis, Norwegian University of Science and Technology, Department of Electronics and Telecommunications, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8777.

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Cellular networks are widely deployed for wireless communication, and as the number of users of these networks increase, so does the need for higher spectral efficiency. Clever measures have to be taken in order to increase throughput for wireless networks because of the scarcity of radio resources. Ever higher rates are demanded, but we also want to conserve a fair distribution of the available resources. Therefore, we consider the problem of joint power allocation and user scheduling, while achieving a desired level of fairness in wireless cellular systems. Dynamic resource allocation is employed for the full reuse networks simulated, in order to cope with inter-cell interference and to optimize spectrum efficiency. Binary power allocation is implemented and compared to the performance without power control, for minimum transmit power levels equal to 0 and greater than 0. We show that binary power control with individual power levels for each cell is optimal for two-cell networks. We also present an extension to the proportional fair scheduling for multi-cell networks, and analyze its performance for different cell sizes and time windows. Finally, we highlight the equality between multi-cell, multi-user and multi-carrier proportional fair scheduling. Simulation results show how power control and user scheduling increase throughput, reduce power consumption and achieve a desired level of fairness. Hence, we can obtain considerable gains for the network throughput through adaptive power allocation and multiuser diversity.

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23

Shan, Lin. "Adaptive Radio Resource Allocation and Scheduling for Wireless Networks." 京都大学 (Kyoto University), 2012. http://hdl.handle.net/2433/158064.

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24

Joshi, S. K. (Satya Krishna). "Radio resource allocation techniques for MISO downlink cellular networks." Doctoral thesis, Oulun yliopisto, 2018. http://urn.fi/urn:isbn:9789526217437.

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Abstract This thesis examines radio resource management techniques for multicell multi-input single-output (MISO) downlink networks. Specifically, the thesis focuses on developing linear transmit beamforming techniques by optimizing certain quality-of-service (QoS) features, including, spectral efficiency, fairness, and throughput. The problem of weighted sum-rate-maximization (WSRMax) has been identified as a central problem to many network optimization methods, and it is known to be NP-hard. An algorithm based on a branch and bound (BB) technique which globally solves the WSRMax problem with an optimality certificate is proposed. Novel bounding techniques via conic optimization are introduced and their efficiency is illustrated by numerical simulations. The proposed BB based algorithm is not limited to WSRMax only; it can be easily extended to maximize any system performance metric that can be expressed as a Lipschitz continuous and increasing function of the signal-to-interference-plus-noise (SINR) ratio. Beamforming techniques can provide higher spectral efficiency, only when the channel state information (CSI) of users is accurately known. However, in practice the CSI is not perfect. By using an ellipsoidal uncertainty model for CSI errors, both optimal and suboptimal robust beamforming techniques for the worst-case WSRMax problem are proposed. The optimal method is based on a BB technique. The suboptimal algorithm is derived using alternating optimization and sequential convex programming. Through a numerical example it is also shown how the proposed algorithms can be applied to a scenario with statistical channel errors. Next two decentralized algorithms for multicell MISO networks are proposed. The optimization problems considered are: P1) minimization of the total transmission power subject to minimum SINR constraints of each user, and P2) SINR balancing subject to the total transmit power constraint of the base stations. Problem P1 is of great interest for obtaining a transmission strategy with minimal transmission power that can guarantee QoS for users. In a system where the power constraint is a strict system restriction, problem P2 is useful in providing fairness among the users. Decentralized algorithms for both problems are derived by using a consensus based alternating direction method of multipliers. Finally, the problem of spectrum sharing between two wireless operators in a dynamic MISO network environment is investigated. The notion of a two-person bargaining problem is used to model the spectrum sharing problem, and it is cast as a stochastic optimization. For this problem, both centralized and distributed dynamic resource allocation algorithms are proposed. The proposed distributed algorithm is more suitable for sharing the spectrum between the operators, as it requires a lower signaling overhead, compared with centralized one. Numerical results show that the proposed distributed algorithm achieves almost the same performance as the centralized one
Tiivistelmä Tässä väitöskirjassa tarkastellaan monisoluisten laskevan siirtotien moniantennilähetystä käyttävien verkkojen radioresurssien hallintatekniikoita. Väitöskirjassa keskitytään erityisesti kehittämään lineaarisia siirron keilanmuodostustekniikoita optimoimalla tiettyjä palvelun laadun ominaisuuksia, kuten spektritehokkuutta, tasapuolisuutta ja välityskykyä. Painotetun summadatanopeuden maksimoinnin (WSRMax) ongelma on tunnistettu keskeiseksi monissa verkon optimointitavoissa ja sen tiedetään olevan NP-kova. Tässä työssä esitetään yleinen branch and bound (BB) -tekniikkaan perustuva algoritmi, joka ratkaisee WSRMax-ongelman globaalisti ja tuottaa todistuksen ratkaisun optimaalisuudesta. Samalla esitellään uusia conic-optimointia hyödyntäviä suorituskykyrajojen laskentatekniikoita, joiden tehokkuutta havainnollistetaan numeerisilla simuloinneilla. Ehdotettu BB-perusteinen algoritmi ei rajoitu pelkästään WSRMax-ongelmaan, vaan se voidaan helposti laajentaa maksimoimaan mikä tahansa järjestelmän suorituskykyarvo, joka voidaan ilmaista Lipschitz-jatkuvana ja signaali-(häiriö+kohina) -suhteen (SINR) kasvavana funktiona. Keilanmuodostustekniikat voivat tuottaa suuremman spektritehokkuuden vain, jos käyttäjien kanavien tilatiedot tiedetään tarkasti. Käytännössä kanavan tilatieto ei kuitenkaan ole täydellinen. Tässä väitöskirjassa ehdotetaan WSRMax-ongelman ääritapauksiin sekä optimaalinen että alioptimaalinen keilanmuodostustekniikka soveltaen tilatietovirheisiin ellipsoidista epävarmuusmallia. Optimaalinen tapa perustuu BB-tekniikkaan. Alioptimaalinen algoritmi johdetaan peräkkäistä konveksiohjelmointia käyttäen. Numeerisen esimerkin avulla näytetään, miten ehdotettuja algoritmeja voidaan soveltaa skenaarioon, jossa on tilastollisia kanavavirheitä. Seuraavaksi ehdotetaan kahta hajautettua algoritmia monisoluisiin moniantennilähetyksellä toimiviin verkkoihin. Tarkastelun kohteena olevat optimointiongelmat ovat: P1) lähetyksen kokonaistehon minimointi käyttäjäkohtaisten minimi-SINR-rajoitteiden mukaan ja P2) SINR:n tasapainottaminen tukiasemien kokonaislähetystehorajoitusten mukaisesti. Ongelma P1 on erittäin kiinnostava, kun pyritään kehittämään mahdollisimman pienen lähetystehon vaativa lähetysstrategia, joka pystyy takaamaan käyttäjien palvelun laadun. Ongelma P2 on hyödyllinen tiukasti tehorajoitetussa järjestelmässä, koska se tarjoaa tasapuolisuutta käyttäjien välillä. Molempien ongelmien hajautetut algoritmit johdetaan konsensusperusteisen vuorottelevan kertoimien suuntaustavan avulla. Lopuksi tarkastellaan kahden langattoman operaattorin välisen spektrinjaon ongelmaa dynaamisessa moniantennilähetystä käyttävässä verkkoympäristössä. Spektrinjako-ongelmaa mallinnetaan käyttämällä kahden osapuolen välistä neuvottelua stokastisen optimoinnin näkökulmasta. Tähän ongelmaan ehdotetaan ratkaisuksi sekä keskitettyä että hajautettua resurssien allokoinnin algoritmia. Hajautettu algoritmi sopii paremmin spektrin jakamiseen operaattorien välillä, koska se vaatii vähemmän kontrollisignalointia. Numeeriset tulokset osoittavat, että ehdotetulla hajautetulla algoritmilla saavutetaan lähes sama suorituskyky kuin keskitetyllä algoritmillakin

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Bansal, Gaurav. "Dynamic resource allocation for OFDM-based cognitive radio systems." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/33275.

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Cognitive radio (CR) is an emerging technology that would improve spectrum utilization by exploiting unused spectrum in dynamically changing environments. We investigate the design of link adaptation algorithms (e.g., adaptive power and bit loading) for orthogonal frequency division multiplexing (OFDM)-based CR systems. Different power and bit loading schemes can be designed for CR users which exploits the time varying nature of fading gains across the OFDM subcarriers. However, one of the challenges here is to ensure that the interference caused to the primary users (PUs) remains below the target interference threshold. Therefore, not only do we need to consider the fading gains, but also the spectral distance of the subcarriers from the PU's band. In this thesis, we propose an optimal power loading algorithm, assuming that the rate can be varied continuously, for an OFDM-based CR system. The downlink transmission capacity of the CR user is thereby maximized, while the interference introduced to the PU remains within a tolerable range. We investigate the case of discrete (or integer) rate adaptation. A sub-optimal scheme for integer bit loading is presented which approximates the optimal continuous rate value to a nearest integer. Next, we propose schemes that maximize the capacity of CR users when only imperfect channel state information (CSI) is available at the CR transmitter while guaranteeing the statistical interference constraint. Further, we propose resource allocation schemes for a multiuser scenario where power is loaded for CR users not only in the subcarriers where PU is not present (overlay fashion) but also in the subcarriers where PU is present (underlay fashion). Finally, for the scenarios where the link between CR source and destination might be weak and not reliable for communication, we employ relays and propose relay and power allocation schemes. Numerical results have been presented for all the proposed algorithms.

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Xiao, Lin. "Radio resource allocation in relay based OFDMA cellular networks." Thesis, Queen Mary, University of London, 2010. http://qmro.qmul.ac.uk/xmlui/handle/123456789/373.

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Adding relay stations (RS) between the base station (BS) and the mobile stations (MS) in a cellular system can extend network coverage, overcome multi-path fading and increase the capacity of the system. This thesis considers the radio resource allocation scheme in relay based cellular networks to ensure high-speed and reliable communication. The goal of this research is to investigate user fairness, system throughput and power consumption in wireless relay networks through considering how best to manage the radio resource. This thesis proposes a two-hop proportional fairness (THPF) scheduling scheme fair allocation, which is considered both in the first time subslot between direct link users and relay stations, and the second time subslot among relay link users. A load based relay selection algorithm is also proposed for a fair resource allocation. The transmission mode (direct transmission mode or relay transmission mode) of each user will be adjusted based on the load of the transmission node. Power allocation is very important for resource efficiency and system performance improvement and this thesis proposes a two-hop power allocation algorithm for energy efficiency, which adjusts the transmission power of the BS and RSs to make the data rate on the two hop links of one RS match each other. The power allocation problem of multiple cells with inter-cell interference is studied. A new multi-cell power allocation scheme is proposed from non-cooperative game theory; this coordinates the inter-cell interference and operates in a distributed manner. The utility function can be designed for throughput improvement and user fairness respectively. Finally, the proposed algorithms in this thesis are combined, and the system performance is evaluated. The joint radio resource allocation algorithm can achieve a very good tradeoff between throughput and user fairness, and also can significantly improve energy efficiency.

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27

Bilibashi, Denis <1986&gt. "Propagation modelling and resource allocation in mobile radio communications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10368/1/PhD%20Thesis%20Denis%20Bilibashi.pdf.

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Over the past years, ray tracing (RT) models popularity has been increasing. From the nineties, RT has been used for field prediction in environment such as indoor and urban environments. Nevertheless, with the advent of new technologies, the channel model has become decidedly more dynamic and to perform RT simulations at each discrete time instant become computationally expensive. In this thesis, a new dynamic ray tracing (DRT) approach is presented in which from a single ray tracing simulation at an initial time t0, through analytical formulas we are able to track the motion of the interaction points. The benefits that this approach bring are that Doppler frequencies and channel prediction can be derived at every time instant, without recurring to multiple RT runs and therefore shortening the computation time. DRT performance was studied on two case studies and the results shows the accuracy and the computational gain that derives from this approach. Another issue that has been addressed in this thesis is the licensed band exhaustion of some frequency bands. To deal with this problem, a novel unselfish spectrum leasing scheme in cognitive radio networks (CRNs) is proposed that offers an energy-efficient solution minimizing the environmental impact of the network. In addition, a network management architecture is introduced and resource allocation is proposed as a constrained sum energy efficiency maximization problem. System simulations demonstrate an increment in the energy efficiency of the primary users’ network compared with previously proposed algorithms.

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Lahad, Bachir. "Joint Uplink/Downlink Radio Resource Allocation in 5G HetNets." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG057.

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La croissance rapide du trafic de données sans fil et des services intensifs en bande passante (voix sur IP, streaming vidéo, live streaming, etc.) nécessite de trouver des solutions viables pour améliorer la qualité de service et maximiser les performances du réseau. Pour s'adapter à ces applications intensives en bande passante, les réseaux cellulaires hétérogènes (HetNets) ont été introduits dans le 3GPP comme l'une des principales caractéristiques pour répondre à ces exigences avancées.Maintenant, en raison de la différence de charges de trafic de liaison montante (UL) et de liaison descendante (DL) attendues dans les prochaines générations HetNets, il devient essentiel d'ajuster dynamiquement les ressources UL/DL. Pour soutenir cette nouvelle approche, le duplexage temporel (TDD) dynamique a été proposé. Néanmoins, l'importance d'UL se pose avec l'évolution des réseaux sociaux et des solutions cloud. Par conséquent, il est très intéressant d’introduire de nouvelles techniques qui atténuent les interférences de l’UL, améliorent les débits UL et DL et permettent également une meilleure utilisation des ressources radio en fournissant un équilibrage de charge adéquat entre UL et DL. Une telle caractéristique supplémentaire est le découplage accès UL/DL.Dans notre travail, nous développons d'abord un modèle TDD dans HetNets. Dans ce modèle, nous dérivons des expressions analytiques pour la distribution de l'emplacement du brouilleur considérant tous les scénarios d’interférences possibles qui pourraient se produire dans les réseaux basés sur TDD, tout en tenant compte de l'impact nocif de cette interférence.Basé sur ce dernier résultat, nous dérivons la fonction de distribution et de génération de moment (MGF) de l’interférence intercellulaire montante et descendante considérant un réseau composé d'une macro-cellule et d'une petite cellule. Nous nous appuyons sur les expressions dérivées pour analyser la capacité moyenne de la cellule de référence dans les transmissions en liaison montante et en liaison descendante.Deuxièmement, nous développons un modèle statistique conjoint TDD/découplage pour mettre en évidence les avantages que le mode d'accès de découplage peut apporter à un système basé sur HetNet TDD. L'introduction du mode de découplage nécessite une analyse approfondie de l’étude de comparaison avec le mode d'accès couplé UL/DL conventionnel. Par conséquent, nous dérivons les statistiques du signal d'interférence et du signal d'intérêt des deux modes, puis analysons leur impact sur le performance du système.Ce travail a été étendu pour inclure le déploiement de plusieurs petites cellules, où des aperçus supplémentaires sur les avantages du mode de découplage sont fournies en termes de gains de découplage UL et DL. Suite à la mise en œuvre du modèle développé, il est démontré que le cas de découplage apporte de plus grands avantages dans la liaison montante et maintient la même amélioration dans la liaison descendante pour diverses valeurs de décalage et, ainsi, améliore les performances globales du système lorsqu'il est associé avec une technologie TDD dynamique. Il est en outre démontré que notre réseau modélisé peut être optimisé en adoptant la combinaison optimale à la fois du facteur de décalage des petites cellules et de la distance entre les petites cellules.D'un autre côté, l'évaluation des avantages d'un TDD adaptatif et du découplage dans un système basé sur HetNet en fonction des charges de trafic variant dans le temps, nécessite de trouver un simulateur de niveau système où nous pouvons présenter le motif derrière l' adoption de découplage et de TDD dynamique. À partir des scénarios de simulation mise en œuvre, il est observé que l'algorithme adaptatif proposé apporte des améliorations de performances significatives dans le débit UL et DL par rapport à un certain nombre de schémas conventionnels, principalement dans les systèmes fortement chargés
The rapid growth in wireless data traffic and bandwidth intensive services (voice over IP, video streaming, livestreaming, etc.) necessitates finding viable solutions to improve service quality and maximize thenetwork performance. To accommodate these bandwidth intensive applications, heterogeneous cellular networks (HetNets) were introduced in 3GPP as one of the main features to meet these advanced requirements. Yet, because of the difference in uplink (UL) and downlink (DL) traffic loads expected in the next HetNetsgeneration, it becomes essential to dynamically adjust UL/DL resources. To support this newapproach, dynamic time-division duplexing (TDD) has been proposed. Nevertheless, the importance of UL arises along with the evolution of social networking and cloudsolutions. Therefore, it is of great interest to introduce novel techniques that mitigate ULinterferences, improve UL and DL throughputs and allow as well, a better use of radio resources byproviding adequate load balancing among UL and DL. Such an additional feature is the decoupledUL/DL access.In our work, we first develop a TDD model in HetNets. Under this model, we derive analytical expressions for the distribution of the interferer location considering all possible interference scenarios that could occur in TDD-based networks, while taking into account the harmful impact of interference.Based on the latter result, we derive the distribution and moment generating function (MGF) of the uplink and downlinkinter-cell interference considering a network consisting of one macro cell and one small cell. We build on the derivedexpressions to analyze the average capacity of the reference cell in both uplink and downlink transmissions.Second, we develop a joint TDD/decoupling statistical model to highlight the benefits thatthe decoupling access mode can bring to a HetNet TDD based system, in terms of UL and DL spectral efficiencies and throughputs. Introducing the decoupling mode necessitates a thoroughcomparison study with the conventional coupled UL/DL access mode. Therefore, we derive the statistics of the interference signal and the signal of interest of both modes and then analyze their impact on the system performance.This work was extended to include multiple small cells deployment, where more insight into the benefits of decoupling mode is provided in terms of UL and DL decoupling gains. Further to the implementation of the developed model, it is shown that the decoupling case brings greater benefits in the uplink and maintains the same improvement in the downlink for various offset values and thus, improves the overall system performance when being combined with a dynamic TDD technology. It is further shown that our modeled network can be optimized by adopting the optimal combination of both the small cell offset factor and the distance between small cells.On the other hand, evaluating the benefits of an adaptive TDD and decoupling in a HetNet based system according to time-variant traffic loads, necessitates findinga system level simulator where we can present the motivation and accurately assess the role of both decoupling and dynamic TDD techniques in the UL/DL optimization problem. From the applied simulation scenarios, it is observed that the proposed adaptive algorithm (dynamic TDD with decoupling policies) yields significant performance improvements in UL and DL throughput compared to a number of conventional schemes, mainly in dense HetNet deployment and in highly loaded systems

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Shaat, Musbah M. R. "Resource Management in Multicarrier Based Cognitive Radio Systems." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/81300.

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The ever-increasing growth of the wireless application and services affirms the importance of the effective usage of the limited radio spectrum. Existing spectrum management policies have led to significant spectrum under-utilization. Recent measurements showed that large range of the spectrum is sparsely used in both temporal and spatial manner. This conflict between the inefficient usage of the spectrum and the continuous evolution in the wireless communication calls upon the development of more flexible management policies. Cognitive radio (CR) with the dynamic spectrum access (DSA) is considered to be a key technology in making the best solution of this conflict by allowing a group of secondary users (SUs) to share the radio spectrum originally allocated to the primary user (PUs). The operation of CR should not negatively alter the performance of the PUs. Therefore, the interference control along with the highly dynamic nature of PUs activities open up new resource allocation problems in CR systems. The resource allocation algorithms should ensure an effective share of the temporarily available frequency bands and deliver the solutions in timely fashion to cope with quick changes in the network. In this dissertation, the resource management problem in multicarrier based CR systems is considered. The dissertation focuses on three main issues: 1) design of efficient resource allocation algorithms to allocate subcarriers and powers between SUs such that no harmful interference is introduced to PUs, 2) compare the spectral efficiency of using different multicarrier schemes in the CR physical layer, specifically, orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier (FBMC) schemes, 3) investigate the impact of the different constraints values on the overall performance of the CR system. Three different scenarios are considered in this dissertation, namely downlink transmission, uplink transmission, and relayed transmission. For every scenario, the optimal solution is examined and efficient sub-optimal algorithms are proposed to reduce the computational burden of obtaining the optimal solution. The suboptimal algorithms are developed by separate the subcarrier and power allocation into two steps in downlink and uplink scenarios. In the relayed scenario, dual decomposition technique is used to obtain an asymptotically optimal solution, and a joint heuristic algorithm is proposed to find the suboptimal solution. Numerical simulations show that the proposed suboptimal algorithms achieve a near optimal performance and perform better than the existing algorithms designed for cognitive and non-cognitive systems. Eventually, the ability of FBMC to overcome the OFDM drawbacks and achieve more spectral efficiency is verified which recommends the consideration of FBMC in the future CR systems.
El crecimiento continuo de las aplicaciones y servicios en sistemas inal´ambricos, indica la importancia y necesidad de una utilizaci´on eficaz del espectro radio. Las pol´ıticas actuales de gesti´on del espectro han conducido a una infrautilizaci´on del propio espectro radioel´ectrico. Recientes mediciones en diferentes entornos han mostrado que gran parte del espectro queda poco utilizado en sus ambas vertientes, la temporal, y la espacial. El permanente conflicto entre el uso ineficiente del espectro y la evoluci´on continua de los sistemas de comunicaci´on inal´ambrica, hace que sea urgente y necesario el desarrollo de esquemas de gesti´on del espectro m´as flexibles. Se considera el acceso din´amico (DSA) al espectro en los sistemas cognitivos como una tecnolog´ıa clave para resolver este conflicto al permitir que un grupo de usuarios secundarios (SUs) puedan compartir y acceder al espectro asignado inicialmente a uno o varios usuarios primarios (PUs). Las operaciones de comunicaci´on llevadas a cabo por los sistemas radio cognitivos no deben en ning´un caso alterar (interferir) los sistemas primarios. Por tanto, el control de la interferencia junto al gran dinamismo de los sistemas primarios implica nuevos retos en el control y asignaci´on de los recursos radio en los sistemas de comunicaci´on CR. Los algoritmos de gesti´on y asignaci´on de recursos (Radio Resource Management-RRM) deben garantizar una participaci´on efectiva de las bandas con frecuencias disponibles temporalmente, y ofrecer en cada momento oportunas soluciones para hacer frente a los distintos cambios r´apidos que influyen en la misma red. En esta tesis doctoral, se analiza el problema de la gesti´on de los recursos radio en sistemas multiportadoras CR, proponiendo varias soluciones para su uso eficaz y coexistencia con los PUs. La tesis en s´ı, se centra en tres l´ıneas principales: 1) el dise˜no de algoritmos eficientes de gesti´on de recursos para la asignaci´on de sub-portadoras y distribuci´on de la potencia en sistemas segundarios, evitando asi cualquier interferencia que pueda ser perjudicial para el funcionamiento normal de los usuarios de la red primaria, 2) analizar y comparar la eficiencia espectral alcanzada a la hora de utilizar diferentes esquema de transmisi´on multiportadora en la capa f´ısica del sistema CR, espec´ıficamente en sistemas basados en OFDM y los basados en banco de filtros multiportadoras (Filter bank Multicarrier-FBMC), 3) investigar el impacto de las diferentes limitaciones en el rendimiento total del sistema de CR. Los escenarios considerados en esta tesis son tres, es decir; modo de transmisi´on descendente (downlink), modo de transmisi´on ascendente (uplink), y el modo de transmisi´on ”Relay”. En cada escenario, la soluci´on ´optima es examinada y comparada con algoritmos sub- ´optimos que tienen como objetivo principal reducir la carga computacional. Los algoritmos sub-´optimos son llevados a cabo en dos fases mediante la separaci´on del propio proceso de distribuci´on de subportadoras y la asignaci´on de la potencia en los modos de comunicaci´on descendente (downlink), y ascendente (uplink). Para los entornos de tipo ”Relay”, se ha utilizado la t´ecnica de doble descomposici´on (dual decomposition) para obtener una soluci´on asint´oticamente ´optima. Adem´as, se ha desarrollado un algoritmo heur´ıstico para poder obtener la soluci´on ´optima con un reducido coste computacional. Los resultados obtenidos mediante simulaciones num´ericas muestran que los algoritmos sub-´optimos desarrollados logran acercarse a la soluci´on ´optima en cada uno de los entornos analizados, logrando as´ı un mayor rendimiento que los ya existentes y utilizados tanto en entornos cognitivos como no-cognitivos. Se puede comprobar en varios resultados obtenidos en la tesis la superioridad del esquema multiportadora FBMC sobre los sistemas basados en OFDM para los entornos cognitivos, causando una menor interferencia que el OFDM en los sistemas primarios, y logrando una mayor eficiencia espectral. Finalmente, en base a lo analizado en esta tesis, podemos recomendar al esquema multiportadora FBMC como una id´onea y potente forma de comunicaci´on para las futuras redes cognitivas.

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Dirani, Mariana. "Resource allocation and son based radio resource management in cellular and wireless networks." Paris 6, 2011. http://www.theses.fr/2011PA066480.

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La bonne gestion des ressources radio est un élément clé pour offrir une bonne Qualité de Service (QdS) pour les utilisateurs tout en assurant la meilleure gestion des ressources du réseau. Nous évaluons la performance de certaines fonctionnalités de gestion de ressources, à savoir l’ordonnancement et l'accès MAC et dans une deuxième étape nous proposons des méthodes de coordination de la puissance dans les liens ascendants et descendants des systèmes LTE. Nous proposons des mécanismes de coordination des interférences dans les systèmes LTE dans le cadre de l’auto-optimisation des réseaux (Self-Optimizing Networks). Le problème est modélisé par un système multi-agent effectuant un apprentissage par renforcement. La théorie de l’apprentissage de système d’inférence floue permet d’apprendre, à partir de l’expérience les décisions optimales correspondant à chaque état du système. La logique floue permet de gérer l’état continu du système. Chaque station de base est alors un agent responsable de modéliser son propre état et l’état des stations voisines et de calculer des récompenses tout au long du processus d’apprentissage afin d’apprendre la politique optimale de façon distribuée mais coopérative. Dans le sens descendant, le but est de décider la quantité de puissance allouée par spectre, dans un contexte de réutilisation totale du spectre. Dans le sens montant, nous proposons une optimisation dynamique du mécanisme de compensation partielle de puissance, Fractional Power Control, standardisé par le 3GPP. L’algorithme de gestion de puissance est adapté pour l’optimisation des performances dans ce contexte sujet à des variations très rapides et chaotiques.

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Qin, Tao. "Adaptive resource allocation for multiuser OFDM-based cognitive radio systems." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/32229.

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Major challenges in the design of next generation wireless communication systems include harsh propagation environments and scarce resources such as power and spectrum. Cognitive radio (CR) is a promising concept for improving the utilization of scarce radio spectrum resources. Orthogonal frequency division multiplexing (OFDM) is regarded as a technology which is well-matched for CR systems. Dynamic resource allocation is an important task in such systems. In this thesis, a novel fair multiuser resource allocation algorithm for OFDM CR systems is presented. Although not optimal, the algorithm has low computational complexity. The algorithm attempts to maximize the total transmit bit rate (system throughput) of a group of secondary (unlicensed or CR) users subject to (1) a total transmit power constraint for secondary users, (2) a maximum tolerable interference level which can be tolerated by primary (licensed) users. The algorithm is fair in the sense that it tries whenever possible to allocate bits to users who have not received their fair share of service. Simulation results show that the proposed algorithm achieves a performance close to optimal. The effect on system throughput of changing various system parameter values is also examined. A novel cost minimization algorithm for multiuser OFDM cognitive radio systems is also proposed. The objective is to minimize a cost function which takes into account the interference power experienced by the primary user as well as the base station transmit power for secondary users given minimum bit rate requirements for each secondary user. It is found that the proposed algorithm provides a performance which is fairly close to optimal. The influence of a relative weight parameter on the base station (BS) transmit power for secondary users and the primary user interference power is also discussed.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate

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32

Rahulamathavan, Yogachandran. "Mathematical optimization techniques for resource allocation in cognitive radio networks." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/8982.

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Introduction of data intensive multimedia and interactive services together with exponential growth of wireless applications have created a spectrum crisis. Many spectrum occupancy measurements, however, have shown that most of the allocated spectrum are used inefficiently indicating that radically new approaches are required for better utilization of spectrum. This motivates the concept of opportunistic spectrum sharing or the so-called cognitive radio technology that has great potential to improve spectrum utilization. This technology allows the secondary users to access the spectrum which is allocated to the licensed users in order to transmit their own signal without harmfully affecting the licensed users' communications. In this thesis, an optimal radio resource allocation algorithm is proposed for an OFDM based underlay cognitive radio networks. The proposed algorithm optimally allocates transmission power and OFDM subchannels to the users at the basestation in order to satisfy the quality of services and interference leakage constraints based on integer linear programming. To reduce the computational complexity, a novel recursive suboptimal algorithm is proposed based on a linear optimization framework. To exploit the spatial diversity, the proposed algorithms are extended to a MIMO-OFDM based cognitive radio network. Finally, a novel spatial multiplexing technique is developed to allocate resources in a cognitive radio network which consists of both the real time and the non-real users. Conditions required for convergence of the proposed algorithm are analytically derived. The performance of all these new algorithms are verified using MATLAB simulation results.

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Wu, Jiay. "Coverage-based cooperative radio resource allocation in mobile communication systems." Thesis, Queen Mary, University of London, 2012. http://qmro.qmul.ac.uk/xmlui/handle/123456789/3164.

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This thesis focuses on applying adaptive system level cooperative coverage to wireless communication networks and proposes an Adaptive Coverage System (ACS) for flexible and resilient radio coverage to handle time-varying geographic traffic distribution, providing better than conventional radio resource allocation results. The ACS utilises antenna arrays called Semi-Smart Antennas to shape cell coverage to alleviate cell overloading and balance loads as equally as possible among cells. Previously work in this field used a Bubble Oscillation Algorithm (BOA) to solve the load balancing problem in the ACS. Modification is made to the core algorithm to enhance its performance for its applications in WCDMA networks, to handle the impact of complex radio propagation environment. The work presented in this thesis then extends into tackling the problem from an optimisation problem point of view. It firstly examines the dynamics of user assignment in a network level and based on these findings, the possibility and approaches towards finding optimal coverage shapes for a mobile network are then presented, including problem formulation, algorithm design, and simulation results. This thesis investigates a system wide cooperative coverage approach to explore the potentials of adaptive coverage systems, has achieved sub-optimal radio resource allocation results, and provides an insight into general network-level radio resource allocation problems and their solutions.

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Jin, Fan. "Resource allocation for heterogeneous radio-frequency and visible-light networks." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/381300/.

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In recent years, mobile data traffic demands have been increased exponentially, and the conventional cellular systems can no longer support the capacity demands. A potential solution for meeting such demands may be Heterogeneous Network (HetNet) techniques. A HetNet may integrate diverse radio access technologies (RAT) such as UMTS Terrestrial Radio Access Networks (UTRAN), GSM/EDGE Radio Access and Network (GERAN), Wireless Local Area Network (WLAN) as well as possibly Visible Light Communication (VLC) networks. The improved channel gain of the HetNet techniques is achieved by employing the small cells and by reduced transmission distance. However, the deployment of HetNet techniques also impose several technical challenges, for example the interference management, handovers, resource management and modelling of HetNets. A HetNet relies on multiple types of access nodes in a wireless network. These access nodes can use either the same technology or different technologies. When the access nodes employ the same technology and use the same frequency band, a major problem is the Co-Channel-Interference (CCI) between these access nodes. We firstly investigate a Radio-Frequency (RF) based HetNet in Chapter 3, which is constituted by the macrocells and the femtocells. More explicitly, the impacts of femtocells on traditional macrocells are studied, when the macrocells are relying on Fractional Frequency Reuse (FFR). The design, performance analysis and optimization problems of this FFR aided two-tier HetNet is investigated. We found the advantage of FFR eroded in dense femtocell scenarios and the optimized network tends to become a Unity Frequency Reuse (UFR) aided system. In order to mitigate the cross-tier interference, we proposed a statics spectrum allocation scheme, namely Swapping Spectrum Access (SSA). Both the Outage Probability (OP) of femtocell Mobile Terminals (MTs) in cell centre region and that of the macrocell MTs in the cell edge region is reduced by the proposed SSA. The optimized network using our SSA is more robust to the detrimental impact of femtocells. Another constitution of a HetNet may rely on integrating different technologies of wireless communication networks. We focus on our attentions on a HetNet composing by a RF femtocell and a VLC network in Chapter 4 and 5. An important component of this architecture is its Resource Management (RM). We investigate the Resource Allocation (RA) problems, under the diverse quality of service (QoS) requirements in terms of data rate, fairness and the statistical delay requirements. Two types of MTs, multi-homing MTs and multi-mode MTs are considered, where multi-homing MTs have the capability of aggregating resources from different networks, while the multi-mode MTs always select a single network for their connection. We proposed a sub-optimal decentralized method for solving the RA problems of both the multi-homing MTs and multi-mode MTs. The simulation results confirm the conceived method is capable of satisfying the QoS requirements. Furthermore, we employ more sophisticated transmission strategies for the VLC network and study their performance in Chapter 5. Again, the RA problems of the HetNet relying on different transmission strategies are investigated.

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Yaqot, Abdullah [Verfasser]. "Adaptive Precoding and Resource Allocation in Cognitive Radio Networks / Abdullah Yaqot." Kiel : Universitätsbibliothek Kiel, 2017. http://d-nb.info/1140790838/34.

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36

Lazaro, de Barrio Oscar. "Dynamic radio resource management algorithms and traffic models for emerging mobile communication systems." Thesis, University of Strathclyde, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248855.

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37

Shatila, Hazem Sarwat. "Adaptive Radio Resource Management in Cognitive Radio Communications using Fuzzy Reasoning." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/26618.

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As wireless technologies evolve, novel innovations and concepts are required to dynamically and automatically alter various radio parameters in accordance with the radio environment. These innovations open the door for cognitive radio (CR), a new concept in telecommunications. CR makes its decisions using an inference engine, which can learn and adapt to changes in radio conditions. Fuzzy logic (FL) is the proposed decision-making algorithm for controlling the CRâ s inference engine. Fuzzy logic is well-suited for vague environments in which incomplete and heterogeneous information is present. In our proposed approach, FL is used to alter various radio parameters according to experience gained from different environmental conditions. FL requires a set of decision-making rules, which can vary according to radio conditions, but anomalies rise among these rules, causing degradation in the CRâ s performance. In such cases, the CR requires a method for eliminating such anomalies. In our model, we used a method based on the Dempster-Shafer (DS) theory of belief to accomplish this task. Through extensive simulation results and vast case studies, the use of the DS theory indeed improved the CRâ s decision-making capability. Using FL and the DS theory of belief is considered a vital module in the automation of various radio parameters for coping with the dynamic wireless environment. To demonstrate the FL inference engine, we propose a CR version of WiMAX, which we call CogMAX, to control different radio resources. Some of the physical parameters that can be altered for better results and performance are the physical layer parameters such as channel estimation technique, the number of subcarriers used for channel estimation, the modulation technique, and the code rate.
Ph. D.

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38

Hu, Juncheng. "Resource allocation and optimization techniques in wireless relay networks." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/13587.

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Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks.

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39

Wang, Rui. "Energy-efficient LTE transmission techniques : introducing Green Radio from resource allocation perspective." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/9596.

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Energy consumption has recently become a key issue from both environmental and economic considerations. A typical mobile phone network in the UK may consume approximately 40-50 MW, contributing a significant proportion of the total energy consumed by the information technology industry. With the worldwide growth in the number of mobile subscribers, the associated carbon emissions and growing energy costs are becoming a significant operational expense, leading to the need for energy reduction. The Mobile VCE Green Radio Project has been launched, which targets to achieve 100x energy reduction of the current wireless networks by 2020. In this thesis, energy-efficient resource allocation strategies have been investigated taking the LTE system as an example. Firstly, theoretical analysis of energy-efficient design in cellular environments is provided according to the Shannon Theory. Based on a two-link scenario the performance of simultaneous transmission and orthogonal transmission for network power minimization under the specified rate constraints is investigated. It is found that simultaneous transmission consumes less power than orthogonal transmission close to the base station, but much more power in the cell-edge area. Also, simulation results suggest that the energy-efficient switching margins between these two schemes are dominated by the sum total of their required data rates. New definitions of power-utility and fairness metrics are further proposed, following by the design of weighted resource allocation approaches based on efficiency-fairness trade-offs. Apart from energy-efficient multiple access between different links, the energy used by individual base stations can also be reduced. For example, deploying sleep modes is an effective approach to reduce radio base station operational energy consumption. By periodically switching off the base station transmission, or using fewer transmit antennas, the energy consumption of base station hardware may decrease. By delivering less control signalling overhead, the radio frequency energy consumption can also be reduced. Simulation results suggest that up to 90% energy reduction can be obtained in low traffic conditions by employing time-domain optimization in each radio frame. The optimum on/off duty cycle is derived, enabling the energy consumption of the base station to scale with traffic loads. In the spatial-domain, an antenna selection criterion is proposed, indicating the most energy-efficient antenna configuration with the knowledge of users’ locations and quality of service requirements. Without time-domain sleep modes, using fewer transmit antennas could outperform full antenna transmission. However, with time-domain sleep modes, using all available antennas is generally the most energy-efficient choice.

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40

Johnstone-Yellin, Tamara Lee. "Effects of resource availability on sex allocation in herbivores." Pullman, Wash. : Washington State University, 2010. http://www.dissertations.wsu.edu/Dissertations/Spring2010/T_Johnstone-Yellin_042310.pdf.

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41

Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066549/document.

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Le Cloud Radio Access Network (C-RAN) est une future direction dans les réseaux de communications sans fils pour déployer des systèmes cellulaires 4G et renforcer la migration des opérateurs vers la nouvelle génération 5G. En comparaison avec l'architecture traditionnelle des stations de base distribuées, l'architecture C-RAN apporte un lot d'avantages à l'opérateur: meilleure utilisation des ressources radio, flexibilité du réseau, minimisation de la puissance consommée et amenuisement des coûts de déploiement. Dans cette thèse, nous adressons le problème d'allocation dynamique des ressources et minimisation de la puissance des communications à liaison descendante dans le C-RAN. Notre recherche vise à allouer les ressources radio à des flux dynamiques d'utilisateurs, tout en trouvant les meilleures combinaisons entre points d'accès et unités de calculs, pour satisfaire la demande de trafic. Il s'agit en outre, d'un problème d'optimisation non linéaire et NP-difficile, comprenant plusieurs contraintes relatives aux demandes de ressources des utilisateurs, gestion d'interférences, capacités fixes des unités de calcul dans le Cloud et des liaisons de transport ainsi que la limitation de la puissance transmise maximale. Afin de surmonter la complexité inhérente à cette problématique du C-RAN, nous présentons différentes approches pour l'allocation dynamique des ressources en trois principales contributions. Les résultats de nos simulations prouvent l'efficacité de nos méthodes, comparé à celles existantes dans la littérature, en termes de taux de débit de satisfaction, nombre d'antennes actives, puissance consommée dans le Cloud, résilience et coût opérationnel du C-RAN
Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost

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42

Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network." Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066549.

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Le Cloud Radio Access Network (C-RAN) est une future direction dans les réseaux de communications sans fils pour déployer des systèmes cellulaires 4G et renforcer la migration des opérateurs vers la nouvelle génération 5G. En comparaison avec l'architecture traditionnelle des stations de base distribuées, l'architecture C-RAN apporte un lot d'avantages à l'opérateur: meilleure utilisation des ressources radio, flexibilité du réseau, minimisation de la puissance consommée et amenuisement des coûts de déploiement. Dans cette thèse, nous adressons le problème d'allocation dynamique des ressources et minimisation de la puissance des communications à liaison descendante dans le C-RAN. Notre recherche vise à allouer les ressources radio à des flux dynamiques d'utilisateurs, tout en trouvant les meilleures combinaisons entre points d'accès et unités de calculs, pour satisfaire la demande de trafic. Il s'agit en outre, d'un problème d'optimisation non linéaire et NP-difficile, comprenant plusieurs contraintes relatives aux demandes de ressources des utilisateurs, gestion d'interférences, capacités fixes des unités de calcul dans le Cloud et des liaisons de transport ainsi que la limitation de la puissance transmise maximale. Afin de surmonter la complexité inhérente à cette problématique du C-RAN, nous présentons différentes approches pour l'allocation dynamique des ressources en trois principales contributions. Les résultats de nos simulations prouvent l'efficacité de nos méthodes, comparé à celles existantes dans la littérature, en termes de taux de débit de satisfaction, nombre d'antennes actives, puissance consommée dans le Cloud, résilience et coût opérationnel du C-RAN
Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost

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43

Saad, Joe. "Evolution of mobile networks architecture and optimization of radio resource management." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG005.

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Avec les réseaux de cinquième génération (5G), plusieurs services hétérogènes sont supportés: le service enhanced Mobile BroadBand (eMBB) caractérisé par ses débits élevés, le service Ultra-Reliable Low-Latency Communications (URLLC) nécessitant une faible latence et le service massive Machine-Type Communications (mMTC) privilégiant une importante densité de connexions.Grâce au slicing, la coexistence de ces services sur le même réseau est possible. Le slicing divise le réseau en sous-réseaux logiques et isolés dont chaque partie est dénommée slice et attribuée à une catégorie de services.De plus, le Radio Access Network (RAN) est le lieu d'une transformation visant à désintégrer ses composants grâce à des organismes de normalisation comme l'alliance Open-RAN (O-RAN). Cette évolution apporte plusieurs avantages pour les opérateurs comme l'introduction de l'intelligence artificielle au niveau des contrôleurs.Dans ce contexte de slicing et d'évolution du RAN, l'optimisation des ressources radio est un défi majeur pour un opérateur mobile afin d'assurer la qualité de service des différents slices à partir d'algorithmes efficaces. Par conséquent, dans cette thèse, l'objectif est de proposer plusieurs algorithmes d'allocation de ressources radio en identifiant les indicateurs de performance nécessaires pour la prise de décisions. De plus, les différentes approches proposées sont comparées entre elles et à celles de l'état de l'art, y compris l'approche standard. Aussi, pour la plupart des solutions proposées, leur emplacement dans l'architecture O-RAN est discuté.Notre premier algorithme est basé sur le Dynamic Weighted Fair Queuing (DWFQ) dans un contexte multi-slice et multi-Virtual Operator (VO). Le but est de déterminer la portion de ressources attribuée à chaque VO dans chaque slice en utilisant la théorie des jeux.Dans la suite, on s'intéresse à la gestion des ressources radio au niveau d'un même opérateur. Pour cela, une deuxième approche se focalise sur l'allocation des ressources radio entre deux slices hétérogènes: eMBB et URLLC. Deux approches, centralisée basée sur le Deep-Q Networks (DQN) et distribuée basée sur un jeu non-coopératif, traitent ce problème où l'allocation des ressources se fait grâce à l'ingénierie de trafic.Dans la troisième contribution, on ajoute l'aspect numérologie (espacement entre sous-porteuses) au problème précédent avec l'étude de trois slices: eMBB, URLLC et mMTC. Pour cela, on divise la bande de l'opérateur en plusieurs Bandwidth Parts (BWPs) dont chacune est associée à une numérologie ce qui provoque l'Inter-Numerology Interference (INI). Par suite, on propose un algorithme à trois étages dont le premier étage utilise la théorie des jeux pour choisir la BWP qui servira les utilisateurs URLLC. Le deuxième étage utilise une heuristique pour déterminer la portion de ressources radio dédiée à chaque BWP. Le troisième étage utilise le DQN pour dimensionner une bande de garde entre les BWPs utilisant des numérologies différentes afin de réduire l'INI.Pour la suite, on garde toujours l'aspect multi-numérologies dans le problème mais on s'intéresse plutôt aux utilisateurs connectés simultanément à plusieurs slices. Pour ces utilisateurs, une latence additionnelle est générée à cause du BWP switching qui est nécessaire pour récupérer les ressources de chaque slice. Pour cela, notre quatrième contribution propose trois mécanismes innovants de BWP switching qui permettent de réduire la latence globale due à cet effet.Pour la dernière contribution, l'efficacité énergétique de ces utilisateurs est étudiée en proposant un algorithme qui sélectionne entre la configuration "single numerology" (une seule BWP pour tous les slices) et "multi-numerology" (BWP différente pour chaque slice) en se basant sur plusieurs facteurs comme le niveau de batterie. Cette sélection se fait à travers deux approches, centralisée basée sur un problème d'optimisation et distribuée basée sur la théorie des jeux
With Fifth Generation (5G) Networks, multiple heterogeneous services are supported such as the enhanced Mobile BroadBand (eMBB) service characterized by high throughput demand, the Ultra-Reliable Low-Latency Communications (URLLC) service requiring a low latency and the massive Machine-Type Communications (mMTC) service favoring a high density of connected devices.Thanks to slicing, these services can coexist on the same infrastructure. Slicing divides the network into multiple isolated logical networks named slices where each slice is attributed to a category of services.Furthermore, standardization bodies such as the Open-RAN alliance (O-RAN) focus on the evolution of the Radio Access Network (RAN) architecture including RAN components disaggregation. This evolution brings in many advantages for the operator such as the introduction of artificial intelligence at the level of the controllers.In this context of RAN evolution and slicing, the radio resource optimization is an important challenge for the mobile network operator to ensure Quality of Service (QoS) satisfaction for the different slices through efficient algorithms. Therefore, in this thesis, the objective is to propose various radio resource allocation algorithms based on the identification of the necessary Key Performance Indicators (KPIs) to take the appropriate decisions. Additionally, the proposed approaches are compared against each other and against other approaches from the state-of-the-art. Also, solutions implementation in an O-RAN compliant architecture is discussed.Our first algorithm is based on Dynamic Weighted Fair Queuing (DWFQ) in a multi-slice and multi-Virtual Operator (VO) context. The aim of this algorithm is to determine the resource portion that will be attributed to each VO in each slice using game theory.Next, we focus on the radio resource management at the level of a single operator. Therefore, the second contribution focuses on the radio resource allocation between two heterogeneous slices: eMBB and URLLC. Two approaches solve this problem where the radio resource allocation is based on traffic engineering. The first approach is a centralized one based on Deep-Q Networks (DQN) and the second is a distributed one based on a non-cooperative game.In our third contribution, we add the numerology (subcarrier spacing) aspect to the previous problem, while considering three slices: eMBB, URLLC and mMTC. For this reason, we divide the total band into multiple Bandwidth Parts (BWPs) each linked to a numerology. This causes a new type of interference called Inter-Numerology Interference (INI). Therefore, we propose a three-level algorithm where the first level uses game theory to choose the BWP that will serve the URLLC users. The second level uses heuristics to determine the portion of radio resources attributed to each BWP. The third level uses DQN to dimension the guard bands between the BWPs using different numerologies to reduce the INI effect.Subsequently, the multi-numerology aspect is retained in the problem, while considering multiple slices per user. For these users, an additional latency is induced due to BWP switching. The latter is necessary in order to retrieve the data of each slice. For this reason, our fourth contribution proposes three innovative BWP switching schemes that help to reduce the overall latency.As for our final contribution, we focus on the energy efficiency aspect of such users by proposing an algorithm that selects the most suitable BWP configuration: single numerology (a single BWP for all slices) or multi-numerology (different BWP for each slice) while taking into account multiple factors such as the battery level. This selection is done thanks to two approaches: a centralized one based on an optimization problem and a distributed one based on game theory

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Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.

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La densification de réseau à l'aide de petites cellules massivement déployées sur les zones macro-cellules, représente une solution prometteuse pour les réseaux mobiles 5G avenir pour faire face à l'augmentation du trafic mobile. Afin de simplifier la gestion de l'hétérogène du réseau d'accès radio (Radio Access Network RAN) qui résulte du déploiement massif de petites cellules, des recherches récentes et des études industrielles ont favorisé la conception de nouvelles architectures de RAN centralisés appelés comme Cloud-RAN (C-RAN), ou RAN virtuel (V-RAN), en incorporant les avantages du cloud computing et Network Functions Virtualization (NFV). Le projet de DynaRoC vise l'élaboration d'un cadre théorique de l'orchestration de ressources pour les C-RAN et dériver les limites de performance fondamentaux ainsi que les arbitrages entre les différents paramètres du système, et la conception de mécanismes d'orchestration de ressources dynamiques sur la base des conclusions théoriques à atteindre un équilibre de performance souhaité, en tenant compte des différents défis de conception. Le doctorant va étudier les mécanismes d'optimisation des ressources novatrices pour favoriser le déploiement de C-RAN, améliorer leur performance exploitant la technologie Network Functions Virtualization
Network densification using small cells massively deployed over the macro-cell areas, represents a promising solution for future 5G mobile networks to cope with mobile traffic increase. In order to simplify the management of the heterogeneous Radio Access Network (RAN) that results from the massive deployment of small cells, recent research and industrial studies have promoted the design of novel centralized RAN architectures termed as Cloud-RAN (C-RAN), or Virtual RAN (V-RAN), by incorporating the benefits of cloud computing and Network Functions Virtualization (NFV). The DynaRoC project aims at (1) developing a theoretical framework of resource orchestration for C-RAN and deriving the fundamental performance limits as well as the tradeoffs among various system parameters, and (2) designing dynamic resource orchestration mechanisms based on the theoretical findings to achieve a desired performance balance, by taking into account various design challenges. The PhD student will investigate innovative resource optimization mechanisms to foster the deployment of C-RANs, improving their performance exploiting the enabling Network Functions Virtualization technology

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Al-Khasib, Tariq. "Resource allocation and optimization for multiple-user legacy and cognitive radio systems." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/24588.

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The rapid transition towards user mobility and the increased demand it carries for bandwidth and data rates has been the driver for significant advancements in research and development in wireless communications in the last decade. These advancements materialized through enhancements to the well established legacy systems and conceptual innovations with great potential. Not far from that, in this thesis, we consider a diverse set of tools and techniques that facilitate efficient utilization of system resources in legacy and Cognitive Radio (CR) systems without hindering the integrity and robustness of the system design. First, we introduce the concept of service differentiation at the receiver, which can be realized by means of a new multiple-user Multiple-Input Multiple-Output (MIMO) detector based on the well known V-BLAST algorithm. We devise the DiffSIC algorithm that is able to differentiate between users in service based on their priorities or imminent needs. DiffSIC achieves its goal by determining the optimal order of detection, at the receiver, that best fits the users' profiles. Second, we propose a channel allocation technique for the transmitter of MIMO multiple-user access systems which enhances the system capacity without aggravating the complexity of the receiver. In particular, we allow users to share resources to take full advantage of the degrees of freedom available in the system. Moreover, we show how to realize these enhancements using simple, yet powerful, modulation and detection techniques. Next, we propose new robust system designs for MIMO CR systems under the inevitable reality of imperfect channel state information at the CR transmitter. We apply innovative tools from optimization theory to efficiently and effectively solve design problems that involve multiple secondary users operating over multiple frequency carriers. At last, we observe the effect of primary users' activity on the stability of, and quality of service provided by, CR systems sharing the same frequency resource with the primary system. We propose admission control mechanisms to limit the effect of primary users' activity on the frequency of system outages at the CR system. We also devise pragmatic eviction control measures to overcome periods of system infeasibility with a minimally disruptive approach.

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Mohamed, Yazan Adnan Ahmad. "A novel resource allocation scheme for ad hoc radio local area networks." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267608.

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Fang, Jennifer Catherine. "Radio resource allocation for multi-hop wireless networks using cross-layer optimization /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3167834.

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Khabaz, Sehla. "Radio Resource Allocation in C-V2X : From LTE-V2X to 5G-V2X." Electronic Thesis or Diss., Sorbonne université, 2022. https://theses.hal.science/tel-03922955.

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Les réseaux véhiculaires ont connu un vrai progrès technologique dans le domaine de la recherche scientifique au cours des dernières décennies. L’intégration des technologies de communications sans fil dans le domaine du transport a abouti à l’émergence d’un nouveau paradigme, à savoir les communications Vehicle-to-Everything (V2X). Ce dernier signifie les communications entre véhicules et tout autre objet. L’objectif primordial des communications véhiculaires, est d’assurer la sécurité routière à travers l’échange des messages périodiques entre les véhicules et entre les véhicules et d’autres participants, tels que les unités de bord de route ou les piétons. La technologie C-V2X (Cellular-Vehicle-to-Everything) est une technologie émergente pour les réseaux véhiculaires standardisée par la 3GPP, dans laquelle les communications véhiculaires se basent sur les réseaux cellulaires. Le LTE-V2X est la première technologie C-V2X, suivie par la 5G-V2X. Les mécanismes d’allocation des ressources jouent un rôle important dans les performances des communications V2X. Pour cette raison, les algorithmes d’allocation des ressources proposés pour la technologie C-V2X doivent fortement répondre aux exigences des applications véhiculaires. Cependant, les applications liées à la sécurité routière sont les applications véhiculaires les plus critiques en termes de fiabilité et en termes de temps de latence. Pour cette raison, dans la première partie de cette thèse, nous proposons un algorithme d’allocation des ressources en LTE-V2X qui se base sur la technique du "clustering". Cet algorithme, nommé MIRD (Maximum Inter-Centoid Reuse Distance), vise à améliorer la fiabilité des communications véhiculaires de type sécurité routière. Dans la deuxième partie de cette thèse, nous abordons l’allocation des ressources radio dans la technologie 5G-V2X. Avant d’entamer le processus d’allocation des ressources radio en 5G-V2X, nous nous intéressons d’abord en premier lieu à la flexibilité de la trame radio de la 5G en concentrant notre intérêt sur le concept de numérologie. À cette fin, nous étudions d’abord l’impact du choix de la numérologie sur les performances des applications véhiculaires. Par le biais de simulations, nous avons abouti à prouver que le choix de la numérologie appropriée est un compromis entre les exigences des applications véhiculaires, les interférences inter-porteuses et les interférences inter-symboles. En deuxième lieu, nous proposons un algorithme d’allocation des ressources en considérant à la fois le trafic de sécurité routière et celui non lié à la sécurité routière. Dans cet algorithme, nommé PSRA-MN (Priority and Satisfaction-based Resource Allocation with Mixed Numerology), nous procédons d’abord au choix de la numérologie appropriée en tenant en compte les conditions du canal radio et la vitesse du véhicule. Ensuite, nous appliquons une politique de priorisation en faveur du trafic lié à la sécurité routière afin de garantir les ressources demandées par ce type de trafic. Puis, les ressources restantes sont allouées de manière optimale aux véhicules dont le trafic est non lié à la sécurité routière afin de maximiser le taux de satisfaction moyen de ces véhicules. L’algorithme PSRA-MN est validé par des simulations. Les résultats obtenus montrent que cet algorithme permet d’atteindre de meilleures performances en comparaison avec les algorithmes traditionnels, tel que le MAX-C/I, en termes de taux d’allocation moyen, de taux de satisfaction moyen, et de temps de latence moyen
Vehicular networks have attracted a lot of research attention in the last decades. The main goal of vehicular communication is to ensure road safety by enabling the periodic communications between vehicles and between vehicles and other participants, such as roadside units. Cellular-Vehicle-to-Everything (C-V2X) is a leading technology for vehicular networks. LTE-V2X is the first C-V2X technology, followed by 5G-V2X, and in both, resource allocation mechanisms play an important role in their performance. The resource allocation algorithms proposed in C-V2X must meet the requirements of V2X applications. Certainly, the safety-related applications are the most critical and time-constrained V2X applications. For this reason, in the first part of this thesis, we propose a clustering-based resource allocation algorithm for safety V2V communications, the Maximum Inter-Centroids Reuse Distance (MIRD), which aims to improve the reliability of safety V2V communications. In the second part of this thesis, we address resource allocation in 5G-V2X technology. Before performing resource allocation in 5G-V2X, we first consider the flexibility of the NR frame structure of 5G by focusing our interest on the 5G numerology concept. Therefore, we first investigate the impact of 5G numerologies on V2X application performance. Through simulations, we showed that choosing the appropriate numerology is a trade-off between V2X applications requirements, Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI). Next, we propose a new resource allocation algorithm, namely the Priority and Satisfaction-based Resource Allocation in Mixed Numerology (PSRA-MN). In the PSRA-MN algorithm, we first select the appropriate numerology considering the channel conditions and the vehicle speed. Then, we apply a prioritization policy in favor of the safety-related traffic to ensure the required resources for the safety-related traffic, and the remaining resources after the safety allocation are optimally allocated to the non-safety vehicles so that the average satisfaction rate is maximized. The proposed PSRA-MN algorithm is validated by simulations. The obtained results show that PSRA-MN outperforms the traditional resource allocation algorithms in terms of average allocation rate, average satisfaction rate and average delay

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49

Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.

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Abstract:

La densification de réseau à l'aide de petites cellules massivement déployées sur les zones macro-cellules, représente une solution prometteuse pour les réseaux mobiles 5G avenir pour faire face à l'augmentation du trafic mobile. Afin de simplifier la gestion de l'hétérogène du réseau d'accès radio (Radio Access Network RAN) qui résulte du déploiement massif de petites cellules, des recherches récentes et des études industrielles ont favorisé la conception de nouvelles architectures de RAN centralisés appelés comme Cloud-RAN (C-RAN), ou RAN virtuel (V-RAN), en incorporant les avantages du cloud computing et Network Functions Virtualization (NFV). Le projet de DynaRoC vise l'élaboration d'un cadre théorique de l'orchestration de ressources pour les C-RAN et dériver les limites de performance fondamentaux ainsi que les arbitrages entre les différents paramètres du système, et la conception de mécanismes d'orchestration de ressources dynamiques sur la base des conclusions théoriques à atteindre un équilibre de performance souhaité, en tenant compte des différents défis de conception. Le doctorant va étudier les mécanismes d'optimisation des ressources novatrices pour favoriser le déploiement de C-RAN, améliorer leur performance exploitant la technologie Network Functions Virtualization
Network densification using small cells massively deployed over the macro-cell areas, represents a promising solution for future 5G mobile networks to cope with mobile traffic increase. In order to simplify the management of the heterogeneous Radio Access Network (RAN) that results from the massive deployment of small cells, recent research and industrial studies have promoted the design of novel centralized RAN architectures termed as Cloud-RAN (C-RAN), or Virtual RAN (V-RAN), by incorporating the benefits of cloud computing and Network Functions Virtualization (NFV). The DynaRoC project aims at (1) developing a theoretical framework of resource orchestration for C-RAN and deriving the fundamental performance limits as well as the tradeoffs among various system parameters, and (2) designing dynamic resource orchestration mechanisms based on the theoretical findings to achieve a desired performance balance, by taking into account various design challenges. The PhD student will investigate innovative resource optimization mechanisms to foster the deployment of C-RANs, improving their performance exploiting the enabling Network Functions Virtualization technology

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Hasan, Monowar. "Radio Resource Management for Relay-Aided Device-to-Device Communication." IEEE, 2013. http://hdl.handle.net/1993/30531.

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In this thesis, performance of relay-assisted Device-to-device (D2D) communication is investigated where D2D traffic is carried through relay nodes. I develop resource management schemes to maximize end-to-end rate as well as conversing rate requirements for cellular and D2D UEs under total power constraint. I also develop a low-complexity distributed solution using the concept of message passing. Considering the uncertainties in wireless links (e.g., when interference from other relay nodes and the link gains are not exactly known), I extend the formulation using robust resource allocation techniques. In addition, a distributed solution approach using stable matching is developed to allocate radio resources in an efficient and computationally inexpensive way under the bounded channel uncertainties. Numerical results show that, there is a distance threshold beyond which relay-assisted D2D communication significantly improves network performance at the cost of small increase in end-to-end delay when compared to conventional approach.

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Dissertations / Theses on the topic 'Radio Resources Allocation'

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