Dissertations / Theses on the topic 'Allocation des ressources radios'
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Enderle, Nicolas. "Allocation de ressources radios pour les services paquets dans l'umts." Paris, ENST, 2003. http://www.theses.fr/2003ENST0004.
Full textIn this thesis, we study scheduling policies on the umts radio interface for packet-switched services like web browsing. Moreover, we analyse the interaction between resource allocation algorithms and protocols involved in end-to-end data transmission like tcp (transmission control protocol) and rlc (radio link control). First, we model the radio resource consumption induced by active users. We then introduce a new factor : the total interference factor the radio efficiency factor. It represents the cost in radio resource per unit of throughput in order to serve a given user. Then, by formulating the resource allocation problem as an optimization problem of users' satisfaction, we present an optimal solution based on the ratio user satisfaction/radio efficiency. Thanks to these results, we build a dynamic allocation algorithm and compare our solution with existing ones from the litterature. The impact of tcp and rlc protocols is taken into account in this study
Enderlé, Nicolas. "Allocation de ressources radios pour les services paquets dans l'UMTS /." Paris : École nationale supérieure des télécommunications, 2003. http://catalogue.bnf.fr/ark:/12148/cb39085229r.
Full textNasreddine, Jad. "Allocation de ressources radios dans les systèmes UMTS à duplexage temporel." Rennes 1, 2005. http://www.theses.fr/2005REN1S009.
Full textVivier, Emmanuelle. "Allocation de ressources radios dans les réseaux cellulaires paquets de 2. 5 et 3ème génération." Paris, CNAM, 2004. http://www.theses.fr/2004CNAM0477.
Full textOur work focuses on the sharing of the system’s radio resources between all active users in a packet-switching network. In the part dedicated to GPRS, all the possible resources repartitions are enumerated. The optimal allocation of the system’s resources, depending on users requests, is identified by an exhaustive search. We propose a faster process, requiring less computation and yet leading to the determination of the same optimal allocation. The second part focuses on UMTS. Real-time constrained communications are served with the highest priority and non real-time constrained services use the leftover capacity. We propose allocation algorithms that maximize the aggregate uplink and downlink throughputs, or the number of simultaneously served flows, with standardized spreading factor values for actual UMTS networks. Those algorithms’ performances are compared with the optimal ones that provide theoretical bounds only and do not yield to standardized spreading factor values
Allouch, Mahdi Mariem. "Gestion intelligente des ressources radios dans les réseaux véhiculaires de la 4G vers la 5G." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG061.
Full textVehicular networks are a class of mobile networks allowing vehicles to communicate with each other in the context of high spatial mobility, as well as with cellular networks and communication networks deployed on the road infrastructure. In order to support Level 5 autonomous vehicle communications, these networks need to provide a QoS that addresses the time-critical constraints of communications while ensuring a high level of integrity of the data exchanged. The LTE technology, used in cellular mobile networks with a strict QoS, has been selected by 3GPP (Release 14) for communication in vehicular networks under the reference LTE-V2X/ cellular V2X. Release 14 introduces two modes (3,4) of LTE communication specifically designed for V2V communication. In mode 3, radio channel selection is managed by the eNodeB base station. In Mode 4, vehicles select their radio resources autonomously regardless of any cellular network coverage. In the literature, different resource allocation algorithms for modes 3 and 4 have been proposed.In the first part of the thesis, we focus on mode 3 addressing the requirements of monitoring level 5 autonomous vehicles through the infrastructure deployed on the road and in the Cloud. An exhaustive study of the existing proposals in the literature shows that the majority of the proposed solutions only deal with periodic messages (non-safety e.g. CAM) while ensuring a minimum of security. Therefore, we introduced aperiodic messages (safety ex. DENM) which are generated in critical situations (accident, traffic jam). We proposed a resource allocation policy based on a priority system with a strict guarantee of minimum capacity for critical applications and a dynamic sharing of the remaining capacity with other applications. We also proposed a new resource reuse technique for both types of messages (critical and less critical) that allows efficient use of network capacity while satisfying the requirements of critical applications without affecting less critical applications.LTE-V technology presents an important step towards the V2X/5G network. This 5G network offers, through URLLC, high integrity and low latency for real-time critical applications. Furthermore, with the concept of "Network Slicing", the functional architecture of the 5G network offers the portability of the vehicular network with its services alongside other service networks within the 5G mobile network. We have chosen to integrate the 5G vehicular network architecture in the same slice at the access network level which allows to benefit from the statistical gain in terms of radio resources utilization. We focused on the MAC and physical NR layers. We studied the dynamic allocation of radio resources between critical URLLC communications and streaming communications carried in the same Slice. The scheduler used for resource allocation is specified to dynamically manage spectral resources between critical URLLC flows and streaming flows exchanged between vehicles and application servers. We proposed several statistical models of exchanged flows and analyzed by simulation the QoS offered in the access network to critical/streaming flows. We have also proposed a quasi-exact Markovian analytical model of the MAC/Physical layer traversal of the URLLC flow with the objective of dimensioning an admission control mechanism (CAC) of the critical flows in the slice and to guarantee the QoS required by these flows
LE, BRIS LOIC. "Allocation de ressources radio dans les reseaux cellulaires." Paris 7, 1999. http://www.theses.fr/1999PA077136.
Full textMaaz, Bilal. "Allocation des ressources radio dans les réseaux sans fil de la 5 G." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLV010/document.
Full textMobile communication is considered as one of the building blocks of smart cities, where citizens should be able to benefit from telecommunications services, wherever they are, whenever they want, and in a secure and non-costly way. This can be done by dense deployment of the latest generation of mobile broadband networks. However, this dense deployment will lead to higher energy consumption, and thus more gas emission and pollution. Therefore, it is crucial from environmental point of view to propose solution reducing energy consumption. In this thesis, we introduce dynamic resource management methods that increase throughput and energy efficiency, and thus reduce pollution. In this framework, we are targeting green multi-cell networks where increased energy efficiency must take into account the increased demand of data by mobile users. This increase, which is exponential in terms of throughput, pushed operators to use the entire frequency spectrum in all cells of the latest generation of mobile networks. As a result, Inter-Cellular Interference (ICI) became preponderant and degraded the performance of users, particularly those with poor radio conditions. In this thesis, we focus on the techniques of power control on the downlink direction, which is considered as one of the key methods of Inter-Cell Interference Coordination (ICIC) while focusing on energy efficient methods. We propose centralized and decentralized methods for this problem of power allocation: centralized methods through convex optimization, and decentralized methods based on non-cooperative game theory. Furthermore, we propose a power control heuristic which has the advantage of being stable and based on signaling messages already existing in the system. The power control problem has a relevant impact on the allocation of radio resources and on the association of mobile users with their servicing Base Station. Therefore, in the second part of the thesis, we formulated a global problem encompassing power control, radio resources allocation, and control of users’ association to a base station. These three sub-problems are treated iteratively until the convergence to the overall solution. In particular, we propose three algorithms for the user association problem: a centralized algorithm, a semi-distributed algorithm and finally a fully distributed algorithm based on reinforcement learning. In addition, for power allocation we implement centralized solutions and distributed solutions. The proof of convergence for the various algorithms is established and the in-depth simulations allow us to evaluate and compare quantitatively the performance, the energy efficiency, and the convergence time of the proposed algorithms
Sharara, Mahdi. "Resource Allocation in Future Radio Access Networks." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG024.
Full textThis 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
Abgrall, Cédric. "Allocation de ressources dans les réseaux sans fil denses." Phd thesis, Télécom ParisTech, 2010. http://pastel.archives-ouvertes.fr/pastel-00581776.
Full textAbgrall, Cédric. "Allocation de ressources dans les réseaux sans fil denses." Phd thesis, Paris, Télécom ParisTech, 2010. https://pastel.hal.science/pastel-00581776.
Full textThis PhD thesis focuses on interference mitigation techniques for wireless communication networks to limit detrimental effects of in-band interference. First, we consider cooperative communication systems and study the trade-off between cooperation benefits and increased level of interference. Cooperation in wireless networks is like a crowded cocktail party with a cacophony of conversations all around. The more people repeat the same information, the more likely you understand it. However, neighbour repeaters act as interferers which harm your understanding. We propose to coordinate and adapt the activation of cooperation and the resource allocation of neighbour cells to time, frequency and space variations of communication context. Second, we propose to classify interference a destination senses on a given frequency band by differentiating three regimes of interference: noisy, intermediate and very strong. This classifier ensures an adaptive and effective processing of in-band interference adapted to time-varying nature of channel. Then, we combine this classifier with QoS constraints to derive centralized and distributed algorithms for power allocation. Both approaches aim at allocating the minimal transmit power vector while meeting QoS requirements of each user, whatever the communication scenario may be. Our simulations show how an adaptive handling of in-band interference may notably reduce the power budget without affecting transmission reliability
Zayen, Bassem. "Stratégies d'accès et d'allocations des ressources pour la radio cognitive." Paris, Télécom ParisTech, 2010. https://pastel.hal.science/pastel-00576459.
Full textCognitive radio is a promising technique for efficient spectrum utilization. It must dynamically monitors activity in the primary spectrum and adapts its transmission to available spectral resources. The blind spectrum sensing and resource allocation in cognitive radio are being addressed in this thesis. The aim of the first part of this research has been to investigate whether model selection or signal space dimension estimation and information theoretic distance measures could be used to improve spectrum detection performance in a blind way and low signal to noise region. Through a thorough research effort, two novel spectrum sensing algorithms based on distribution analysis and dimension estimation of the primary user received signal were proposed and analyzed. The second part of this thesis presents and analyzes two user selection strategies based on outage probability. One explored the idea of combining multi-user diversity gains with spectral sharing techniques to maximize the secondary users sum rate while maintaining the outage probability of the primary user not degraded with a distributed manner, the other treat the beamforming problem in the context of cognitive radio using multiuser MIMO secondary user system and proposes a user selection strategy based on outage probability
Bouallegue, Kaïs. "Contribution à la radio intelligente à forte mobilité : adaptation spectrale et allocation dynamique des ressources." Thesis, Valenciennes, 2017. http://www.theses.fr/2017VALE0023.
Full textThe main objectives of railway operators are to increase safety, reduce operating and maintenance costs, increase attractiveness and profit by offering new services to customers. These objectives will be achieved through a huge increase of data fluxes between existing infrastructure and the technologies currently used on the train. Spectral efficiency, optimization of radio resources, interoperability and reliability of communications are major elements for railway applications. These constraints and the sporadic use of available frequency bands have gave rise to cognitive radio. Cognitive radio is an emerging technology that improves the performance of existing radio systems by integrating artificial intelligence with software radio. A cognitive radio system is defined by its ability to be aware of its radio environment. Indeed, to optimize as much as possible the available spectral opportunities, the cognitive radio device must be able to transmit on free bands while performing a spectrum sensing to not interfere with users having priority on the band and to detect other vacant frequencies. As part of this thesis, we propose to focus on the problem of spectrum detection in a highly mobile environment. Some constraints should be considered, such as speed. Added to this, there are regulatory constraints on detection criteria, such as the IEEE 802.22 WRAN standard, which stipulates that detection of a priority user must be performed at -21 dB within a period of 2 seconds. The objective is therefore to design an intelligent radio terminal in the physical and regulatory conditions of transmission in a railway environment
Bouton, Eric. "Algorithmes d'allocation de ressources pour des systèmes à interférence." Paris, Télécom ParisTech, 2010. http://www.theses.fr/2010ENST0002.
Full textInterference is a phenomenon that is present in many communication systems and is often a serious hindrance to their development. An intelligent management of this phenomenon is thus necessary to limit its negative impact. In this thesis, we addressed three issues related to its presence. In the first part, in order to boost transmission rates in impulse radio ultra-wide band systems, we propose to assign multiple time-hopping codes to the same user. This generates a new type of interference associated with the additional codes allocated to the user of interest. Since the benefit of this type of strategy is not straightforward, we study the impact of our proposition on the system's performance. In the second part, we tackle the problem of optimizing the outage probability of multiple-antenna systems in a slow fading Rician channel. We propose to optimize this probability in the context of N transmit antennas and one single receive antenna, when the signal-to-noise ratio is high, and improve it when there are multiple antennas both at the transmitter and at the receiver. In the last part, we study the problem of power allocation in a Gaussian interference channel. Based on a new approximate expression of this channel's capacity and using an OFDM modulation, we propose to develop a new power allocation algorithm that improves the achievable rates region, compared with a uniform allocation and classic dynamic spectrum management techniques
Nguyen, Thanh-Son-Lam. "Wireless Resource Allocation in 5G-NR V2V Communications." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG052.
Full textThis doctoral dissertation explores the enhancement of wireless resource allocation in Vehicle-to-Everything (V2X) communications, as specified by the 3GPP Release 16 standard. The specific area of our research is the NR-V2X Sidelink communication, also known as the New Radio-Vehicles to Vehicles (NR-V2V) communication. Our goal is to formulate a novel optimization protocol that not only guarantees high-quality services (QoS) but also outperforms existing methodologies in NR-V2V communication.Initially, we introduce Adaptive Physical Configuration (APC), a search-based algorithm designed to identify the optimal physical layer configuration within a set of environmental factors, specifically tailored for a broadcast communication scheme. Following this, we evolve APC into a Radio Aware variant (RA-APC), broadening its scope by incorporating unicast communication and establishing a more flexible structure for PHY resources. In the final phase, we further refine RA-APC by integrating a machine learning algorithm, specifically a decision tree. This integration uncovers patterns within the input factors, thereby augmenting both the accuracy and efficiency of the allocation optimization process
Mharsi, Niezi. "Cloud-Radio Access Networks : design, optimization and algorithms." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT043/document.
Full textCloud Radio Access Network (C-RAN) has been proposed as a promising architecture to meet the exponential growth in data traffic demands and to overcome the challenges of next generation mobile networks (5G). The main concept of C-RAN is to decouple the BaseBand Units (BBU) and the Remote Radio Heads (RRH), and place the BBUs in common edge data centers (BBU pools) for centralized processing. This gives a number of benefits in terms of cost savings, network capacity improvement and resource utilization gains. However, network operators need to investigate scalable and cost-efficient algorithms for resource allocation problems to enable and facilitate the deployment of C-RAN architecture. Most of these problems are very complex and thus very hard to solve. Hence, we use combinatorial optimization which provides powerful tools to efficiently address these problems.One of the key issues in the deployment of C-RAN is finding the optimal assignment of RRHs (or antennas) to edge data centers (BBUs) when jointly optimizing the fronthaul latency and resource consumption. We model this problem by a mathematical formulation based on an Integer Linear Programming (ILP) approach to provide the optimal strategies for the RRH-BBU assignment problem and we propose also low-complexity heuristic algorithms to rapidly reach good solutions for large problem instances. The optimal RRH-BBU assignment reduces the expected latency and offers resource utilization gains. Such gains can only be achieved when reducing the inter-cell interference caused by the dense deployment of cell sites. We propose an exact mathematical formulation based on Branch-and-Cut methods that enables to consolidate and re-optimize the antennas radii in order to jointly minimize inter-cell interference and guarantee a full network coverage in C-RAN. In addition to the increase of inter-cell interference, the high density of cells in C-RAN increases the amount of baseband processing as well as the amount of data traffic demands between antennas and centralized data centers when strong latency requirements on fronthaul network should be met. Therefore, we discuss in the third part of this thesis how to determine the optimal placement of BBU functions when considering 3GPP split option to find optimal tradeoffs between benefits of centralization in C-RAN and transport requirements. We propose exact and heuristic algorithms based on combinatorial optimization techniques to rapidly provide optimal or near-optimal solutions even for large network sizes
Jin, Xin. "Resource allocation in multicarrier cognitive radio networks." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2014. http://www.theses.fr/2014TELE0014.
Full textIn 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
Jin, Xin. "Resource allocation in multicarrier cognitive radio networks." Thesis, Evry, Institut national des télécommunications, 2014. http://www.theses.fr/2014TELE0014/document.
Full textIn 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
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.
Full textCloud 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
Ul, Hassan Naveed. "Conception multi-couche dans les systèmes OFDMA et MIMO-OFDMA." Paris 11, 2010. http://www.theses.fr/2010PA112022.
Full textThe majority of the work on dynamic resource allocation in OFDMA and MIMO-OFDMA systems either consider delay sensitive traffic where packet delay constraints are D=1 or the delay tolerant traffic with D=∞. These are two extreme cases and does not exist in practice because the delay constraints of all the practical service types are in the range of 1
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.
Full textCloud 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
Lebreton, Aurélien. "Allocation dynamique de ressources basée sur un multiplexage radio-fréquence pour les futurs réseaux d'accès optique passifs." Thesis, Lorient, 2015. http://www.theses.fr/2015LORIS381.
Full textThis thesis is part of the growing capacity of passive optical access networks. The works done during this thesis are based on the fact that current technologies, employing time division multiplexing, will reach their limits in the coming years and will no longer respond to changes in high bitrates requirements. The study of problems encountered during the current deployments led us to propose another form of multiplexing more suitable for bitrates requested by users: the FDM/FDMA PON, frequency division multiplexing. The work done in this thesis aim to demonstrate the feasibility of a such architecture in the laboratory. The objectives are to determine the achievable capacity, whether for the downlink (from central office to user) or the uplink (subscriber to central), but also to achieve a theoretical study to highlight the limitations of this solution. Algorithms for dynamic allocation of resources have been developed and validated experimentally to determine the total capacity of each link. The architecture using two distinct wavelengths (one for the downlink and one for the uplink) achieves a capacity of 40Gbps for the downlink and 20Gbps for the uplink by using FDM/FDMA PON. Finally, a hybrid architecture using a single wavelength to transport both uplink and downlink data has been explored and achieves a symmetrical capacity of 25Gbps
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.
Full textVehicular 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
Denis, Juwendo. "Resource Allocation Frameworks for Multi-carrier-based Cognitive Radio Networks with full and Statistical CSI." Electronic Thesis or Diss., Paris, CNAM, 2016. http://www.theses.fr/2016CNAM1069.
Full textThe ubiquity and proliferation of wireless technology and services considerably lead to a sharp increase in the number of individuals requiring access to wireless networks in recent decades. The growing number of mobile subscribers results into a dramatic increasing request for more radio spectrum. Consequently, underutilized yet scarce radio spectrum becomes overwhelmingly crowded. Therefore, the advent of new radio resource management paradigm capable of switching from static licensed spectrum management to dynamic spectrum access is of great importance. Cognitive radio (CR) emerged as a promising technology capable of enhancing the radio spectrum by permitting unlicensed users known as secondary users to coexist with primary users. Meanwhile, multi-carrier modulations that can efficiently overcome the detrimental effect of multipath fading in a wireless channel are very appealing for the physical layer of cognitive radio networks. However, the lack of cooperation between primary and secondary users may lead to asynchronous transmission and consequently result into inter-carrier interferences. Judicious resource allocation frameworks need to be designed in order to maintain the coexistence between primary and secondary users. Guaranteeing secondary users' quality of service (QoS), while ensuring that interferences generated to the primary users are tolerable, poses significant challenges for the design of wireless cognitive radio networks. This dissertation focuses on resource, i.e. subcarrier and power, allocation for multi-carrier-based downlink cognitive radio networks under perfect or statistical channel state information (CSI) with secondary users interact either cooperatively or competitively. Firstly, the problem of margin adaptive and energy-efficiency optimization are investigated considering perfect CSI at the secondary users' side. Secondly, assuming statistical CSI available at the secondary users, we address the problem of utility maximization under primary and secondary outage constraints. We provide some near-optimal resource allocation schemes to tackle the aforementioned problems. The findings and proposed frameworks can eventually be used for performance assessment and design of practical cognitive radio networks
Ezzaouia, Mahdi. "Allocation de ressource opportuniste dans les réseaux sans fil multicellulaires." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2018. http://www.theses.fr/2018IMTA0098/document.
Full textThe exponential growth of traffic in mobile networks is accompanied by an increase in its heterogeneity, both in space and over time. This thesis deals with scheduling algorithms adapted to highly concentrated and time-varying traffic zones. We propose a spectrum borrowing mechanism from an under-loaded cell to an overloaded one combined with a reactive intra-cellular scheduling algorithm. We are also interested in the Cloud Radio Access Network architecture that separates the Radio Head(RRH) from the Baseband Unit (BBU). The BBU is connected to the RRU according to two modes. The first one is called a one-to-one association and consists in allocating the resource units of the BBU radio frame to a single RRH. In the second mode which is called multiple association, a BBU can handle multiple RRHs. We propose a hybrid association mode in which the resource units of each frame are divided into two slices. The first one constitutes an unshared slice and is allocated to central users according to the one-to-one association in order to increase the throughput, especially at high traffic load. The second slice contains a quantity of resource units that are shared by a group of RRHs belonging to the same BBU. This common slice is configured according to the multiple association mode and is allocated to the edge and mobile users. We show that the hybrid mode reduces the inter-cell interferences, decreases the number of inter-BBU handovers and improves the energy consumption
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.
Full textWith 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
Dirani, Mariana. "Resource allocation and son based radio resource management in cellular and wireless networks." Paris 6, 2011. http://www.theses.fr/2011PA066480.
Full textHuang, Fan. "Allocation des ressources fondée sur la qualité du canal pour la voie descendante des systèmes LTE." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLS250/document.
Full textThis research takes place in the context of Private Mobile Radio networks evolution which aims at designing a new LTE based PMR technology dedicated to public security services. As the frequency bands dedicated to this service is scarce and the need of public safety forces is different, we have revisited the Resource Allocation problem in this thesis with two main objectives: designing new allocation algorithms which outperform the spectrum efficiency and serving fairly the users instead of maximizing the global network throughput.This thesis proposes new Resource Block (RB) allocation strategies in LTE downlink systems. Instead of the well-known resource allocation algorithms, which work on the condition that the RB capacity is already estimated, our RB allocation schemes can improve the potential of the channel capacity, using Beamforming cooperation and game-theoretical problems1. With the MIMO (Multiple-Input-Multiple-output) antennas, the Beamforming technique improves the received signal in order to increase the SINR (Signal-to-Interference-plus-Noise-Ratio), but the improved signal may also influence the inter-cell interference in the neighbouring cells. As inter-cell interference is the main interference in the OFDMA system, a smart scheduling can choose UEs (User Equipment) in adjacent cells to control interference increment caused by Beamforming.In traditional methods, the scheduler allocates RBs to UEs depending on the RB capacities and other parameters, the system then applies the Beamforming technique to these chosen UEs. After the Beamforming, the RB capacity varies but the scheduler keeps the same allocation.Our scheme allocates the RBs and chooses Beamforming vectors at the same time to enhance the performance of the Beamforming technique. It increases the average throughput by increasing the RB’s average capacity. Because more parameters are taken into account, the complexity also increases exponentially. In the thesis we find an iterative method to reduce the complexity. From the simulations, our iterative method also has good performance and improves more than 10% of throughput on the cell edge.2. In contrast to the performance first algorithms, game theoretic allocation schemes maximize the UEs’ utility function from the economical point of view. The NBS (Nash Bargaining Solution) offers a Pareto optimal solution for the utility function.The traditional NBS allocation in an OFDMA system is to optimize the subcarrier allocation at each time slot, but in the OFDMA system, the subcarriers are composed of Resource Blocks (RB) in time series. We propose an RB NBS approach, which is more efficient than the existing subcarrier NBS allocation scheme.We analyze the fast-fading channels and compare them without the path-loss influence. Because of the great path-loss in cell edge, the edge UE always has lower RB capacity than the cell center UE. Our idea is to bring in a compensating factor to overcome this path-loss influence, and the compensating factors are carefully chosen to maximize the NBS function. However, the computation of these factors has a high complexity and we develop four approximated solutions which give same performance and accuracy. The performance evaluation confirms that our method and its approximated solutions are able to spread resources fairly over the entire cell
Gakhar, Kamal. "Ingénierie de la QoS sur une plaque radio mixte IEEE 802. 16/ IEEE 802. 11e." Télécom Bretagne, 2007. http://www.theses.fr/2007TELB0048.
Full textDenis, Juwendo. "Resource Allocation Frameworks for Multi-carrier-based Cognitive Radio Networks with full and Statistical CSI." Thesis, Paris, CNAM, 2016. http://www.theses.fr/2016CNAM1069/document.
Full textThe ubiquity and proliferation of wireless technology and services considerably lead to a sharp increase in the number of individuals requiring access to wireless networks in recent decades. The growing number of mobile subscribers results into a dramatic increasing request for more radio spectrum. Consequently, underutilized yet scarce radio spectrum becomes overwhelmingly crowded. Therefore, the advent of new radio resource management paradigm capable of switching from static licensed spectrum management to dynamic spectrum access is of great importance. Cognitive radio (CR) emerged as a promising technology capable of enhancing the radio spectrum by permitting unlicensed users known as secondary users to coexist with primary users. Meanwhile, multi-carrier modulations that can efficiently overcome the detrimental effect of multipath fading in a wireless channel are very appealing for the physical layer of cognitive radio networks. However, the lack of cooperation between primary and secondary users may lead to asynchronous transmission and consequently result into inter-carrier interferences. Judicious resource allocation frameworks need to be designed in order to maintain the coexistence between primary and secondary users. Guaranteeing secondary users' quality of service (QoS), while ensuring that interferences generated to the primary users are tolerable, poses significant challenges for the design of wireless cognitive radio networks. This dissertation focuses on resource, i.e. subcarrier and power, allocation for multi-carrier-based downlink cognitive radio networks under perfect or statistical channel state information (CSI) with secondary users interact either cooperatively or competitively. Firstly, the problem of margin adaptive and energy-efficiency optimization are investigated considering perfect CSI at the secondary users' side. Secondly, assuming statistical CSI available at the secondary users, we address the problem of utility maximization under primary and secondary outage constraints. We provide some near-optimal resource allocation schemes to tackle the aforementioned problems. The findings and proposed frameworks can eventually be used for performance assessment and design of practical cognitive radio networks
Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.
Full textNetwork 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
Dandachi, Ghina. "Multihoming in heterogeneous wireless networks." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0014.
Full textFifth generation mobile networks (5G) are being designed to introduce new services that require extreme broadband data rates and utlra-reliable latency. 5G will be a paradigm shift that includes heterogeneous networks with densification, virtualized radio access networks, mm-wave carrier frequencies, and very high device densities. However, unlike the previous generations, it will be a holistic network, tying any new 5G air interface and spectrum with the currently existing LTE and WiFi. In this context, we focus on new resource allocation strategies that are able to take advantage of multihoming in dual access settings. We model such algorithms at the flow level and analyze their performance in terms of flow throughput, system stability and fairness between different classes of users. We first focus on multihoming in LTE/WiFi heterogeneous networks. We consider network centric allocations where a central scheduler performs local and global proportional fairness (PF) allocations for different classes of users, single-homed and multihomed users. By comparison with a reference model without multihoming, we show that both strategies improve system performance and stability, at the expense of more complexity for the global PF. We also investigate user centric allocation strategies where multihomed users decide the split of a file using either peak rate maximization or network assisted strategy. We show that the latter strategy maximizes the average throughput in the whole network. We also show that network centric strategies achieve higher data rates than the user centric ones. Then, we focus on Virtual Radio Access Networks (V-RAN) and particularly on multi-resource allocation therein. We investigate the feasibility of virtualization without decreasing neither users performance, nor system's stability. We consider a 5G heterogeneous network composed of LTE and mm-wave cells in order to study how high frequency networks can increase system's capacity. We show that network virtualization is feasible without performance loss when using the dominant resource fairness strategy (DRF). We propose a two-phase allocation (TPA) strategy which achieves a higher fairness index than DRF and a higher system stability than PF. We also show significant gains brought by mm-wave instead of WiFi. Eventually, we consider energy efficiency and compare DRF and TPA strategies with a Dinklebach based energy efficient strategy. Our results show that the energy efficient strategy slightly outperforms DRF and TPA at low to medium load in terms of higher average throughput with comparable power consumption, while it outperforms them at high load in terms of power consumption. In this case of high load, DRF outperforms TPA and the energy efficient strategy in terms of average throughput. As for Jain's fairness index, TPA achieves the highest one
Ibrahimi, Khalil. "Gestion des ressources des réseaux mobiles de nouvelle génération par rapport à la mobilité des utilisateurs." Phd thesis, Université d'Avignon, 2009. http://tel.archives-ouvertes.fr/tel-00453644.
Full textBezzina, Amira. "Interference and Resource Management in Wireless Urban Networks." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS579.
Full textData traffic has been witnessing an incessant growth especially in urban wireless networks. Thus, operators need to provide high quality services with good coverage and low costs. Two interesting solutions can be considered to overcome this issue: the deployment of Multi-Radio Multi-Channel Wireless Mesh Networks or Smallcell deployment. New resource allocation and interference management schemes adapted for networks are proposed in this thesis. For MR-MC WMNs, we propose a new interference-aware game-theoretic algorithm called IGCA to manage the limited number of channels in order to alleviate the "a priori" interference between mesh routers by using a potential game. In the second part of this research work, we focus on resource allocation and power control problems in dense smallcell networks. Our ultimate goals are to alleviate the interference in downlink communications and make an efficient spectrum reuse when the urban mobile network is quite congested. The key idea is to find a trade-off between minimizing the transmit power of cells and maximizing the resource allocation with respect to an SINR threshold. To do so, we first propose a resource and power allocation algorithm called TCRPA that considers only smallcell users' demands. We formulate the optimization problem as a MILP and solve it using a cluster-based approach. Second, we extend this work to consider macro-users demands aside with the small-users ones in the defined optimization problem. We propose, TORPA, a new semi-centralized scheme, to solve the expanded MILP. Our simulation results show that our proposals succeed to meet our expectations
Oueis, Jad. "Radio access and core functionalities in self-deployable mobile networks." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEI095/document.
Full textSelf-deployable mobile networks are a novel family of cellular networks, that can be rapidly deployed, easily installed, and operated on demand, anywhere, anytime. They target diverse use cases and provide network services when the classical network fails, is not suitable, or simply does not exist: when the network saturates during crowded events, when first responders need private broadband communication in disaster-relief and mission-critical situations, or when there is no infrastructure in areas with low population density. These networks are challenging a long-standing vision of cellular networks by eliminating the physical separation between the radio access network (RAN) and the core network (CN). In addition to providing RAN functionalities, such as radio signal processing and radio resource management, a base station can also provide those of the CN, such as session management and routing, in addition to housing application servers. As a result, a base station with no backhaul connection to a traditional CN can provide local services to users in its vicinity. To cover larger areas, several base stations must interconnect. With the CN functions co-located with the RAN, the links interconnecting the BSs form the backhaul network. Being setup by the BSs, potentially in an ad hoc manner, the latter may have a limited bandwidth. In this thesis, we build on the properties distinguishing self-deployable networks to revisit classical RAN problems but in the self-deployable context, and address the novel challenges created by the core network architecture. Starting with the RAN configuration, we propose an algorithm that sets a frequency and power allocation scheme. The latter outperforms conventional frequency reuse schemes in terms of the achieved user throughput and is robust facing variations in the number of users and their distribution in the network. Once the RAN is configured, we move to the CN organization, and address both centralized and distributed CN functions placements. For the centralized placement, building on the shortages of state of the art metrics, we propose a novel centrality metric that places the functions in a way that maximizes the traffic that can be exchanged in the network. For the distributed placement, we evaluate the number of needed instances of the CN functions and their optimal placement, considering the impact on the backhaul bandwidth. We further highlight the advantages of distributing CN functions, from a backhaul point of view. Accordingly, we tackle the user attachment problem to determine the CN instances serving each user when the former are distributed. Finally, with the network ready to operate, and users starting to arrive, we tackle the user association problem. We propose a novel network-aware association policy adapted to self-deployable networks, that outperforms a traditional RAN-based policy. It jointly accounts for the downlink, the uplink, the backhaul and the user throughput request
Dandachi, Ghina. "Multihoming in heterogeneous wireless networks." Thesis, Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0014/document.
Full textFifth generation mobile networks (5G) are being designed to introduce new services that require extreme broadband data rates and utlra-reliable latency. 5G will be a paradigm shift that includes heterogeneous networks with densification, virtualized radio access networks, mm-wave carrier frequencies, and very high device densities. However, unlike the previous generations, it will be a holistic network, tying any new 5G air interface and spectrum with the currently existing LTE and WiFi. In this context, we focus on new resource allocation strategies that are able to take advantage of multihoming in dual access settings. We model such algorithms at the flow level and analyze their performance in terms of flow throughput, system stability and fairness between different classes of users. We first focus on multihoming in LTE/WiFi heterogeneous networks. We consider network centric allocations where a central scheduler performs local and global proportional fairness (PF) allocations for different classes of users, single-homed and multihomed users. By comparison with a reference model without multihoming, we show that both strategies improve system performance and stability, at the expense of more complexity for the global PF. We also investigate user centric allocation strategies where multihomed users decide the split of a file using either peak rate maximization or network assisted strategy. We show that the latter strategy maximizes the average throughput in the whole network. We also show that network centric strategies achieve higher data rates than the user centric ones. Then, we focus on Virtual Radio Access Networks (V-RAN) and particularly on multi-resource allocation therein. We investigate the feasibility of virtualization without decreasing neither users performance, nor system's stability. We consider a 5G heterogeneous network composed of LTE and mm-wave cells in order to study how high frequency networks can increase system's capacity. We show that network virtualization is feasible without performance loss when using the dominant resource fairness strategy (DRF). We propose a two-phase allocation (TPA) strategy which achieves a higher fairness index than DRF and a higher system stability than PF. We also show significant gains brought by mm-wave instead of WiFi. Eventually, we consider energy efficiency and compare DRF and TPA strategies with a Dinklebach based energy efficient strategy. Our results show that the energy efficient strategy slightly outperforms DRF and TPA at low to medium load in terms of higher average throughput with comparable power consumption, while it outperforms them at high load in terms of power consumption. In this case of high load, DRF outperforms TPA and the energy efficient strategy in terms of average throughput. As for Jain's fairness index, TPA achieves the highest one
Oueis, Jessica. "Gestion conjointe de ressources de communication et de calcul pour les réseaux sans fils à base de cloud." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM007/document.
Full textMobile Edge Cloud brings the cloud closer to mobile users by moving the cloud computational efforts from the internet to the mobile edge. We adopt a local mobile edge cloud computing architecture, where small cells are empowered with computational and storage capacities. Mobile users’ offloaded computational tasks are executed at the cloud-enabled small cells. We propose the concept of small cells clustering for mobile edge computing, where small cells cooperate in order to execute offloaded computational tasks. A first contribution of this thesis is the design of a multi-parameter computation offloading decision algorithm, SM-POD. The proposed algorithm consists of a series of low complexity successive and nested classifications of computational tasks at the mobile side, leading to local computation, or offloading to the cloud. To reach the offloading decision, SM-POD jointly considers computational tasks, handsets, and communication channel parameters. In the second part of this thesis, we tackle the problem of small cell clusters set up for mobile edge cloud computing for both single-user and multi-user cases. The clustering problem is formulated as an optimization that jointly optimizes the computational and communication resource allocation, and the computational load distribution on the small cells participating in the computation cluster. We propose a cluster sparsification strategy, where we trade cluster latency for higher system energy efficiency. In the multi-user case, the optimization problem is not convex. In order to compute a clustering solution, we propose a convex reformulation of the problem, and we prove that both problems are equivalent. With the goal of finding a lower complexity clustering solution, we propose two heuristic small cells clustering algorithms. The first algorithm is based on resource allocation on the serving small cells where tasks are received, as a first step. Then, in a second step, unserved tasks are sent to a small cell managing unit (SCM) that sets up computational clusters for the execution of these tasks. The main idea of this algorithm is task scheduling at both serving small cells, and SCM sides for higher resource allocation efficiency. The second proposed heuristic is an iterative approach in which serving small cells compute their desired clusters, without considering the presence of other users, and send their cluster parameters to the SCM. SCM then checks for excess of resource allocation at any of the network small cells. SCM reports any load excess to serving small cells that re-distribute this load on less loaded small cells. In the final part of this thesis, we propose the concept of computation caching for edge cloud computing. With the aim of reducing the edge cloud computing latency and energy consumption, we propose caching popular computational tasks for preventing their re-execution. Our contribution here is two-fold: first, we propose a caching algorithm that is based on requests popularity, computation size, required computational capacity, and small cells connectivity. This algorithm identifies requests that, if cached and downloaded instead of being re-computed, will increase the computation caching energy and latency savings. Second, we propose a method for setting up a search small cells cluster for finding a cached copy of the requests computation. The clustering policy exploits the relationship between tasks popularity and their probability of being cached, in order to identify possible locations of the cached copy. The proposed method reduces the search cluster size while guaranteeing a minimum cache hit probability
El, Amine Ali. "Radio resource allocation in 5G cellular networks powered by the smart grid and renewable energies." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2019. http://www.theses.fr/2019IMTA0167/document.
Full textWe live in the digital era where the Internet has become an essential part of our daily lives. With more than 750 million connected households and over 6.8 billion mobile subscribers, mobile networks are dominating the Information and Communication Technology (ICT) sector with more than 75%. The trend is of further increase and appears to have no signs of slowing down in the near future due to the ongoing new services and applications. However, this radical surge of ICT devices and services has pushed corresponding energy consumption and its footprint on the environment to grow at a staggering rate consuming more than 5% of the world’s electrical energy and releasing into the atmosphere about 2% of the global CO2 emissions. Since base stations, the core elements to provide internet access, consume most of the energy in cellular networks, it is essential to study new strategies and architectures in order to deter this energy crunch. This thesis focuses on the crucial role of energy in the design and operation of future cellular networks. We consider different and complementary approaches and parameters, including energy efficiency techniques (i.e., radio resource management and sleep schemes), renewable energy sources, Smart Grid and tools from machine learning to bring down the energy consumption of these complex networks while guaranteeing a certain quality of service adapted to 5G use cases
Aroua, Sabrine. "Spectrum resource assignment in cognitive radio sensor networks for smart grids." Thesis, La Rochelle, 2018. http://www.theses.fr/2018LAROS007/document.
Full textWith the advances in wireless communication technologies, cognitive radio sensor networks (CRSNs) stand as an efficient spectrum solution in the development of intelligent electrical power networks, the smart grids. The cognitive radio (CR) technology provides the sensors with the ability to use the temporally available licensed spectrum in order to escape the unlicensed spectrum resource scarcity problem. In this context, several challenging communication issues face the CRSN deployment for smart grids such as the coexistence of different electrical applications and the heterogeneous opportunities to access available licensed channels between smart grid sensors. The work conducted in this thesis focuses on spectrum resource allocations for CRSNs in smart grids. We concentrate our efforts on the development of new spectrum resource sharing paradigms for CRSNs in smart grids. The developed solutions focus on distributed and balanced spectrum sharing among smart grid sensors and on eventual CRSN deployment scenarios in smart grid areas. All along the thesis, channels are assigned without relying on a predefined common control channel (CCC) to exchange control messages before each spectrum access trial. All along the thesis, channels are assigned without relying on a predefined common control channel (CCC) to exchange control messages before each spectrum access trial. Performance evaluation of the different proposed channel assignment solutions shows their ability to achieve a distributed and fair opportunistic spectrum assignment in a way to consider different smart grid system characteristics
Guo, Jianding. "Theoretical research on graph coloring : Application to resource allocation in device-to-device 4G radio system (LTE)." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCA007/document.
Full textGraph coloring problem is a famous NP-complete problem, which has extensive applications. In the thesis, new exact graph coloring algorithms are researched from a graph structure point of view. Based on Total solutions Exact graph Coloring algorithm (TexaCol) which is capable of getting all coloring solution subsets for each subgraph, two other exact algorithms, Partial best solutions Exact graph Coloring algorithm (PexaCol) and All best solutions Exact graph Coloring algorithm (AexaCol), are presented to get multiple best solutions. These two algorithms utilize the backtracking method, in which they only choose the best solution subset each step to continue the coloring until partial or all best solutions are obtained. The result analysis shows that PexaCol and AexaCol can deal with larger graphs than TexaCol and especially, AexaCol runs much faster than TexaCol and the solver Gurobi to get all best solutions.Device-to-Device (D2D) is a promising technique for the future mobile networks, such as 5th generation wireless systems (5G), and the resource allocation is one of the most crucial problems for its performance. In order to efficiently allocate radio resource for D2D links in Long-Term Evolution (LTE) system, a systematic resource allocation scheme is proposed based on D2D clusters, including the inter-cluster resource allocation and the intra-cluster resource allocation. With the cluster interference range, the inter-cluster resource allocation problem is formulated as a dynamic graph coloring problem, and a dynamic graph coloring algorithm is designed based on PexaCol. This algorithm is able to allocate radio resource to clusters while they are dynamically generated and deleted. The numerical analysis results show that this algorithm has good performance in resource utilization, runtime and scalability.For the intra-cluster resource allocation problem, a topology-based resource allocation method is designed naturally combining power allocation with Resource Block (RB) allocation. To simplify this associated optimization problem, a local optimal method is proposed, in which the best topology is chosen each step achieving the maximal throughput with the minimum number of assigned RBs. With respect to this method, four algorithms are presented: static greedy, static PexaCol, dynamic PexaCol and dynamic PexaCol approximate. Result analysis shows that for small-scale clusters, static PexaCol and dynamic PexaCol are capable of getting a maximal optimization index by locally choosing the best topology for each node while static greedy and dynamic PexaCol approximate are able to get the suboptimal solution for the local optimization with much lower complexity. For large-scale clusters, giving certain treating sequences, the dynamic PexaCol approximate performs better than static greedy regarding the optimization index within an acceptable runtime
Ta, Duc-Tuyen. "Channel Surveillance Strategy and Interference Reduction in Future Wireless Networks." Electronic Thesis or Diss., Paris, ENST, 2018. http://www.theses.fr/2018ENST0039.
Full textThe wireless revolution is creating a huge demand for accessing to the radio frequency spectrum with the explosion of the number of connected devices and the large diversity of use cases and requirements. However, the conflict between the spectrum scarcity and the spectrum underutilization leads to significant inefficiencies of wireless communications and impedes the deployment of new applications.Recently, Cognitive Radio (CR) has emerged as a promising technology to address to alleviate the spectrum scarcity and better utilize the spectrum resources by enabling the network users to detect and exploit the spectrum opportunities. The successful deployment of CR networks, however, depends not only on the efficient exploitation of the spectrum opportunities but also on the self-coexistence mechanisms between cognitive users (SUs). The objective of this thesis, therefore, is to provide a systematic study of self-coexistence mechanisms for the cognitive users in both centralized and distributed CR network architecture, which directly address the unaddressed technical challenges of the threat caused by the misbehaving users in the centralized infrastructure networks and the resource allocation issues in the distributed infrastructure networks
Santi, Nina. "Prédiction des besoins pour la gestion de serveurs mobiles en périphérie." Electronic Thesis or Diss., Université de Lille (2022-....), 2023. http://www.theses.fr/2023ULILB050.
Full textMulti-access Edge computing is an emerging paradigm within the Internet of Things (IoT) that complements Cloud computing. This paradigm proposes the implementation of computing servers located close to users, reducing the pressure and costs of local network infrastructure. This proximity to users is giving rise to new use cases, such as the deployment of mobile servers mounted on drones or robots, offering a cheaper, more energy-efficient and flexible alternative to fixed infrastructures for one-off or exceptional events. However, this approach also raises new challenges for the deployment and allocation of resources in terms of time and space, which are often battery-dependent.In this thesis, we propose predictive tools and algorithms for making decisions about the allocation of fixed and mobile resources, in terms of both time and space, within dynamic environments. We provide rich and reproducible datasets that reflect the heterogeneity inherent in Internet of Things (IoT) applications, while exhibiting a high rate of contention and interference. To achieve this, we are using the FIT-IoT Lab, an open testbed dedicated to the IoT, and we are making all the code available in an open manner. In addition, we have developed a tool for generating IoT traces in an automated and reproducible way. We use these datasets to train machine learning algorithms based on regression techniques to evaluate their ability to predict the throughput of IoT applications. In a similar approach, we have also trained and analysed a neural network of the temporal transformer type to predict several Quality of Service (QoS) metrics. In order to take into account the mobility of resources, we are generating IoT traces integrating mobile access points embedded in TurtleBot robots. These traces, which incorporate mobility, are used to validate and test a federated learning framework based on parsimonious temporal transformers. Finally, we propose a decentralised algorithm for predicting human population density by region, based on the use of a particle filter. We test and validate this algorithm using the Webots simulator in the context of servers embedded in robots, and the ns-3 simulator for the network part
Pottier, Antony. "Méthodes décentralisées d'allocation des ressources dans le canal d'interférence acoustique sous-marin." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2018. http://www.theses.fr/2018IMTA0095/document.
Full textUnderwater acoustic waves are used by many systems and biologic organisms to communicate, navigate or infer information about the environment. Future developments of human maritime activities imply an increase of the number of active acoustic sources in the oceans. The underwater environment is therefore shared by many heterogeneous sources (sonars, modems, marine mammals, ...) competing involuntarily for using the physical resources offered by the communication channel.The goal of this thesis is to provide solutions allowing autonomous and decentralized adaptation of the transmission strategies of underwater acoustic communication systems, according to the environment. To some extent, this work deals with topics that are closely related to what has motivated the first researches on cognitive radio systems. However, the specific properties of the underwater environment, the heterogeneity of interfering acoustic sources, and the absence of communication standards rise new difficulties
Masmoudi, Raouia. "Télécommunications domotiques efficaces en termes de consommation d’énergie." Thesis, Cergy-Pontoise, 2015. http://www.theses.fr/2015CERG0791.
Full textThe 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
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.
Full textDue 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
Hasan, Cengis. "Optimisation de l'allocation de ressources dans les réseaux celluaires : une approche efficace en énergie." Phd thesis, INSA de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-00942967.
Full textDunat, Jean-Christophe. "Allocation opportuniste de spectre pour les radios cognitives." Phd thesis, Paris : École nationale supérieure des télécommunications, 2006. http://catalogue.bnf.fr/ark:/12148/cb40978484c.
Full textOuni, Anis. "Optimisation de la capacité et de la consommation énergétique dans les réseaux maillés sans fil." Phd thesis, INSA de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-01001979.
Full textKataria, Amit. "Cognitive radios spectrum sensing issues /." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/5047.
Full textThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on March 28, 2008) Includes bibliographical references.
Haouari, Lobna. "MODELISATION ET SIMULATION DE L’INTRODUCTION DE TECHNOLOGIES RFID DANS DES SYSTEMES DE CONFIGURATION A LA DEMANDE." Thesis, Saint-Etienne, EMSE, 2012. http://www.theses.fr/2012EMSE0680/document.
Full textRadio Frequency IDentification allows quick and secure identification of objects. In mass customisation systems, RFID technologies can be peculiarly efficient, because they are able to support the complex flows of information which characterize these systems.In this study, we focus on RFID technologies effects on configuration to order (CTO) systems.We base the research on an existing case in order to obtain reliable information directly usable by decision makers. The rarity of studies offering quantitative, detailed and real case based measures makes the originality of this thesis.RFID technology implementation's effect is analysed by a discrete event simulation approach and is presented in two levels:The first level relates direct changes brought about by RFID (e.g. faster execution of the many checks due to the wide range of products, reduced workload for resources…). These changes have an impact on system's performance in terms of lead time, late orders' rate, etc.The second level is axed on deeper changes occurring due to the increased product visibility and the ease of collecting large amounts of data with an RFID technology.These changes mainly focus on the dynamic allocation of workload. Reconsidering of processes and proposing changes deeper than the simple direct technology impact is a breakthrough, in this study, because of the lack of publications highlighting this benefit adequately.In conclusion, RFID contribution in CTO systems and, extensively, in assembly to order systems may be undeniable. Moreover, beyond the direct technology impact, rethinking how the system works by exploiting the deeper potential of technology can increase profits
Ouni, Anis. "Optimisation de la capacité et de la consommation énergétique dans les réseaux maillés sans fil." Phd thesis, INSA de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-00921216.
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