Tesi sul tema "Future Cellular and IoT Networks"

Les défis posés par le nombre croissant d'appareils connectés, la forte consommation d'énergie et l'impact environnemental dans les réseaux sans fil d'aujourd'hui et de demain retiennent de plus en plus l'attention. De nouvelles technologies telles que le cloud mobile de périphérie (Mobile Edge Computing) ont vu le jour pour rapprocher les services en nuage des appareils et remédier à leurs limitations en matière de calcul. Le fait de doter ces appareils et les nœuds du réseau de capacités de récolte d'énergie (Energy Harvesting) est également prometteur pour permettre de consommer de l'énergie à partir de sources durables et respectueuses de l'environnement. En outre, l'accès multiple non orthogonal (Non-Orthogonal Multiple Access) est une technique essentielle pour améliorer l'efficacité spectral mobile. Avec l'aide des progrès de l'intelligence artificielle, en particulier des modèles d'apprentissage par renforcement (Reinforcement Learning), le travail de thèse porte sur la conception de politiques qui optimisent conjointement l'ordonnancement et la décharge de calcul pour les appareils dotés de capacités EH, les communications compatibles avec le NOMA et l'accès MEC. En outre, lorsque le nombre d'appareils augmente et que la complexité du système s'accroît, le regroupement NOMA est effectué et l'apprentissage fédéré (Federated Learning) est utilisé pour produire des politiques RL de manière distribuée. Les résultats de la thèse valident la performance des politiques RL proposées, ainsi que l'intérêt de l'utilisation de la technique NOMA
The challenges posed by the increasing number of connected devices, high energy consumption, and environmental impact in today's and future wireless networks are gaining more attention. New technologies like Mobile Edge Computing (MEC) have emerged to bring cloud services closer to the devices and address their computation limitations. Enabling these devices and the network nodes with Energy Harvesting (EH) capabilities is also promising to allow for consuming energy from sustainable and environmentally friendly sources. In addition, Non-Orthogonal Multiple Access (NOMA) is a pivotal technique to achieve enhanced mobile broadband. Aided by the advancement of Artificial Intelligence, especially Reinforcement Learning (RL) models, the thesis work revolves around devising policies that jointly optimize scheduling and computational offloading for devices with EH capabilities, NOMA-enabled communications, and MEC access. Moreover, when the number of devices increases and so does the system complexity, NOMA clustering is performed and Federated Learning is used to produce RL policies in a distributed way. The thesis results validate the performance of the proposed RL-based policies, as well as the interest of using NOMA technique

Cellular networks are multi-user communication systems that consist of three basic elements: interference, cooperation, and feedback. A fundamental goal of multi-user systems research is to find out the capacity limit and its achievability of a general model that consists of many senders, receivers, and intermediate nodes. In the past 60 years, a huge amount of research efforts have been paid towards five special problems of multi-user systems: multiple-access channel, broadcast channel, relay channel, crosstalk channel, and feedback channel. Although most of those problems have not received a satisfactory answer yet, rapid development of cellular networks have motivated communication-theoretic research about cooperation in those special channels. The primary objective of this thesis is to study the cooperation theory in relay and crosstalk channels. The overall organisation of this thesis is based on our new vision about cooperative behaviour in communication networks. This new vision indicates that cooperative behaviour in relay and crosstalk networks can be classified into three groups, namely. Postman, Host, and Synergy. The classification is based on how a cooperative node utilises the multi-user side information such as channel quality information (CQI), codebook, message, in various communication scenarios. Specifically, major contributions of this thesis are summarised as follows. The Postman describes cooperative behaviour in relay networks, where a cooperative node offers cooperation by delivering other's message to its desired destination. Our first work in this category is about doubly differential cooperative relaying scheme proposed for mobile communication over rapidly time-varying channel. It is shown that the proposed scheme can enjoy full cooperative diversity-gain without need of full channel state information. The other work in this category is about adaptive bit-power allocation for orthogonal frequency-division multiplexing (OFDM)-based relay networks. Provided full knowledge of CQI, a number of sub-optimum approaches have been proposed to improve the power efficiency through multi-link optimisation. The Host describes cooperative behaviour in cognitive interference networks, where a primary user offers cooperation to a secondary user by opening its own spectrum and sharing knowledge of side information. The work in this category is about overlay and underlay cognitive radio channels, where the primary user broadcasts its private codebook and knowledge of CQI, so that the secondary user can perceive the primary user's message and interference state. Capacity theorem of two-user Gaussian cognitive interference channels have been carefully investigated, based on which power allocation and spectrum access approaches have been proposed in terms of power and spectrum efficiency. The Synergy describes cooperative behaviour in crosstalk channels. A typical example is the cooperative bit-power allocation between two individual transmitter-receiver pairs. One cooperative behaviour is sharing of codebook and CQI between two transmitter-receiver pairs. The purpose of sharing is to maximize their common profit and to allow an optimal treatment of mutual interference. Provided full knowledge of multi-user CQI at transmitters, two transmitter-receiver pairs first perform iterative rate-adaptation to maximize the sum-rate, and then employ proportional fairness for rate allocation.

This PhD thesis focuses on developing novel self organising functionalities in wireless cellular systems. Since the root cause of suboptimal performance in wireless cellular system is the mismatch between its semi-static design and its dynamically changing environment, the main objective of self organising functionalities is to counter measure the effect of this mismatch. Towards this end, we classify wireless cellular system dynamics based on their time scale into three main classes - short, medium and long term dynamics and develop self organising solution suitable for each class. Through investigation of case studies of self organising systems in nature, we first identify the desirable characteristics of self organising systems. By building on these case studies we propose a general framework called Biomimmetic Self Organising Framework (BSOF), for designing adaptive solution in engineering system that bear characteristics of self organisation. First major contribution of this thesis consists of a novel solution to cope with short term dynamics e.g. pop up hot spots. This solution optimizes antenna tilts in distributed manner for system wide spectral efficiency optimization in face of heterogeneous user geographical distributions. The solution is developed analytically by applying BSOF and its performance is evaluated against centralised fixed tilting benchmarks through system level simulations. Results show a 30% improvement in average spectral efficiency along with advantages of a self organising distributed solution i.e. very low signalling overhead, agility and scalability. Second major contribution in this thesis provides a novel solution to cope with medium term dynamics e.g. uneven traffic load among cells. This solution optimises cell load through cell coverage adaptation in distributed manner in order to minimise system wide average call blocking. The analytical framework behind this solution is developed by following the steps of BSOF. The Numerical results show 280% reduction in average blocking probability compared to no load balancing in place. The performance of this distributed solution is also compared against a bench mark of centrafised control based load balancing algorithm. Results show that a performance very close to the centralised solution can be obtained with proposed distributed solution, with added advantages of a distributed solution. Our final major contribution aims for providing a self organising functionality for long term dynamics e.g. demographical and socio economical changes. First we develop a novel framework for long term performance characterisation of wireless system in terms of three key performance indicators i.e. capacity, quality of service and energy efficiency. Then, by following the steps of BSOF, we develop a novel solution for self organisation of frequency reuse and deployment architecture for joint optimization of spectral efficiency, fairness and energy efficiency.

The rapid growth in mobile communications due to the exponential demand for wireless access is causing the distribution and maintenance of cellular networks to become more complex, expensive and time consuming. Lately, extensive research and standardisation work has been focused on the novel paradigm of self-organising network (SON). SON is an automated technology that allows the planning, deployment, operation, optimisation and healing of the network to become faster and easier by reducing the human involvement in network operational tasks, while optimising the network coverage, capacity and quality of service. However, these SON autonomous features cannot be achieved with the current drive test coverage assessment approach due to its lack of automaticity which results in huge delays and cost. Minimization of drive test (MDT) has recently been standardized by 3GPP as a key self- organising network (SON) feature. MDT allows coverage to be estimated at the base station using user equipment (UE) measurement reports with the objective to eliminate the need for drive tests. However, most MDT based coverage estimation methods recently proposed in literature assume that UE position is known at the base station with 100% accuracy, an assumption that does not hold in reality. In this work, we develop a novel and accurate analytical model that allows the quantification of error in MDT based autonomous coverage estimation (ACE) as a function of error in UE as well as base station (user deployed cell) positioning. We first consider a circular cell with an omnidirectional antenna and then we use a three-sectored cell and see how the system is going to be affected by the UE and the base station (user deployed cell) geographical location information errors. Our model also allows characterization of error in ACE as function of standard deviation of shadowing in addition to the path-loss.

Les technologies sans fil sont d'une importance capitale pour les sociétés d'aujourd'hui et les futurs réseaux de communication de 6ème génération sont appelés à relever nombre de défis sociétaux et technologiques. Si les infrastructures de communication ont un impact environnemental croissant qu'il est essentiel de réduire, les technologies numériques ont également un rôle à jouer dans la réduction de l'impact de tous les secteurs de l'économie. À cette fin, les réseaux du futurs devront non seulement permettre un transfert d'informations plus efficace, mais aussi répondre aux besoins croissants de capacité d'échange de données. C'est notamment le rôle des cas d'utilisation de l'internet des objets, où un nombre massif de capteurs permet de superviser des systèmes complexes. Ces cas d'utilisation sont associés à de nombreuses contraintes telles que des ressources énergétiques et une complexité limitées. Par conséquent, une couche physique - chargée de la transmission de l'information entre les nœuds du réseau - efficace et peu complexe est absolument cruciale. Dans cette optique, l'utilisation de techniques d'intelligence artificielle est pertinente. D'une part, le cadre mathématique des réseaux neuronaux permet des implémentations matérielles génériques efficaces et peu coûteuses. D'autre part, l'application de procédures d'apprentissage permet d'améliorer les performances de certains algorithmes. Dans ce travail, nous nous intéressons à l'utilisation des réseaux de neurones et de l'apprentissage automatique pour le traitement numérique du signal dans le contexte des réseaux 6G-IoT. En premier lieu, nous nous intéressons à la transcription sous forme de réseaux de neurones de certains algorithmes d'égalisation, de démodulation et de décodage issus de la littérature des communications numériques. Dans un second temps, nous nous intéressons à l'application de mécanismes d'apprentissage sur ces structures de réseaux de neurones afin d'en améliorer les performances. Un décodeur de codes linéaires en bloc est proposé et permet la découverte à l'aveugle d'un schéma de décodage dont les performances sont au moins équivalentes à celles du décodeur de référence. Enfin, une structure de bout en bout est présentée, permettant l'apprentissage conjoint d'un schéma de codage/décodage avec des performances et une complexité comparables aux solutions état de l'art
Wireless technologies are of paramount importance to today's societies and future 6th generation communication networks are expected to address many societal and technological challenges. While communications infrastructures have a growing environmental impact that needs to be reduced, digital technologies also have a role to play in reducing the impact of all sectors of the economy. To this end, the future networks will not only have to enable more efficient information transfer, but also meet the growing need for data exchange capacity. This is particularly the role of the Internet of Things use cases, where a massive number of sensors allow to monitor complex systems. These use cases are associated with many constraints such as limited energy resources and complexity. Therefore, an efficient and low-complexity physical layer - responsible for the transmission of information between the network nodes - is absolutely crucial. In this regard, the use of artificial intelligence techniques is relevant. On the one hand, the mathematical framework of neural networks allows for efficient and low-cost generic hardware implementations. On the other hand, the application of learning procedures can improve the performance of certain algorithms. In this work, we are interested in the use of neural networks and machine learning for digital signal processing in the context of 6G-IoT networks. First, we are interested in the transcription of certain equalisation, demodulation and decoding algorithms from the digital communications literature into neural networks. Secondly, we are interested in the application of learning mechanisms on these neural network structures in order to improve their performance. A linear block decoder is proposed which allows the blind discovery of a decoding scheme whose performance is at least equivalent to that of the reference decoder. Finally, an end-to-end structure is presented, allowing joint learning of an encoding/decoding scheme with performance and complexity comparable to state-of-the-art solutions

The demand for mobile wireless network resources is constantly on the rise, pushing for new communication technologies that are able to support unprecedented rates. In this thesis we address the issue by considering advanced interference management techniques to exploit the available resources more efficiently under relaxed channel state information (CSI) assumptions. While the initial studies focus on current half-duplex (HD) technology, we then move on to full-duplex (FD) communication due to its inherent potential to improve spectral efficiency. Work in this thesis is divided into four main parts as follows. In the first part, we focus on the two-cell two-user-per-cell interference broadcast channel (IBC) and consider the use of topological interference management (TIM) to manage inter-cell interference in an alternating connectivity scenario. Within this context we derive novel outer bounds on the achievable degrees of freedom (DoF) for different system configurations, namely, single-input single-output (SISO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) systems. Additionally, we propose new transmission schemes based on joint coding across states that exploit global topological information at the transmitter to increase achievable DoF. Results show that when a single state has a probability of occurrence equal to one, the derived bounds are tight with up to a twofold increase in achievable DoF for the best case scenario. Additionally, when all alternating connectivity states are equiprobable: the SISO system gains 11/16 DoF, achieving 96:4% of the derived outer bound; while the MISO/MIMO scenario has a gain of 1/2 DoF, achieving the outer bound itself. In the second part, we consider a general G-cell K-user-per-cell MIMO IBC and analyse the performance of linear interference alignment (IA) under imperfect CSI. Having imperfect channel knowledge impacts the effectiveness of the IA beamformers, and leads to a significant amount of residual leakage interference. Understanding the extent of this impact is a fundamental step towards obtaining a performance characterisation that is more relevant to practical scenarios. The CSI error model used is highly versatile, allowing the error to be treated either as a function of the signal-to-noise ratio (SNR) or as independent of it. Based on this error model, we derive a novel upper bound on the asymptotic mean sum rate loss and quantify the DoF loss due to imperfect CSI. Furthermore, we propose a new version of the maximum signal-to-interference plus noise ratio (Max-SINR) algorithm which takes into account statistical knowledge of the CSI error in order to improve performance over the naive counterpart in the presence of CSI mismatch. In the third part, we shift our attention to FD systems and consider weighted sum rate (WSR) maximisation for multi-user multi-cell networks where FD base-stations (BSs) communicate with HD downlink (DL) and uplink (UL) users. Since WSR problems are non-convex we transform them into weighted minimum mean squared error (WMMSE) ones that are proven to converge. Our analysis is first carried out for perfect CSI and then expanded to cater for imperfect CSI under two types of error models, namely, a norm-bounded error model and a stochastic error model. Additionally, we propose an algorithm that maximises the total DL rate subject to each UL user achieving a desired target rate. Results show that the use of FD BSs provides significant gains in achievable rate over the use of HD BSs, with a gain of 1:92 for the best case scenario under perfect CSI. They also demonstrate the robust performance of the imperfect CSI designs, and confirm that FD outperforms HD even under CSI mismatch conditions. Finally, the fourth part considers the use of linear IA to manage interference in a multi-user multi-cell network with FD BSs and HD users under imperfect CSI. The number of interference links present in such a system is considerably greater than that present in the HD network counterpart; thus, understanding the impact of residual leakage interference on performance is even more important for FD enabled networks. Using the same generalised CSI error model from the second part, we study the performance of IA by characterising the sum rate and DoF losses incurred due to imperfect CSI. Additionally, we propose two novel IA algorithms applicable to this network; the first one is based on minimising the mean squared error (MMSE), while the second is based on Max-SINR. The proposed algorithms exploit statistical knowledge of the CSI error variance in order to improve performance. Moreover, they are shown to be equivalent under certain conditions, even though the MMSE based one has lower computational complexity. Furthermore for the multi-cell case, we also derive the proper condition for IA feasibility.

The rapid growth of wireless communications and upcoming requirements of 5G networks are driving interest in the areas from wireless transceivers to sensor nodes. One of the most vital components of the wireless transmitter is the radio frequency power amplifier. A large-signal device model of the transistor is an essential part of the power amplifier design process. Despite the significant developments in large-signal modelling, the models for commercially available devices from the manufacturers are still under continuous development and often lack accuracy. One of the main objectives of this thesis is the validation and extension of an analytic approach as an alternative to conventional large-signal modelling for power amplifier designing. The first contribution is the derivation of new analytical expressions based on the equivalent circuit model, including the extrinsic parasitic elements introduced by the package, to calculate the optimum source and load impedances and to predict the performance of a radio frequency power amplifier. These expressions allow to evaluate the effects of a package on the optimum impedance values and performance. The second contribution is establishing the accuracy of the analytic approach. Harmonic balance simulation is used as the first benchmark to evaluate the method at various bias points and frequencies. The validity of the analytic approach is demonstrated at a frequency of 3.25 GHz for gallium nitride based high power devices with measurement of prototype radio frequency power amplifier designed for the impedance values obtained from the analytic expressions. The third contribution is extending the analytic approach to determine the optimum impedance values for different criteria of maximum gain, linearity and efficiency. The analytic expressions are utilized to gain an understanding of the relationship among the device performance, the elements of devices and package models and I-V characteristics. The wireless sensor networks are essential elements for the realization of the Internet of Things. Sensor nodes, which are the fundamental building blocks of these networks, have to be energy efficient and able to produce energy to reduce the maintenance cost and to prolong their lifetime. The second main aim of the thesis is designing and implementing an ultra-low power autonomous wireless sensor node that harvests the indoor light energy. The forth contribution of this thesis includes a comprehensive comparison of six different solar cell technologies under a controlled light intensity, carried out to determine the best option for indoor light energy harvesting. The power consumption of the node is reduced by selecting the appropriate hardware and implementing a wake-up receiver to reduce the active and idle mode currents. The low power consumption coupled with light energy harvesting significantly prolong the operating lifetime of the node.

Internet of Things (IoT) has come in reality to improve our living quality. Automation is embraced in all the possible business verticals that have diverse communication needs ranged from static devices’ sporadic transmission to mobile devices’ every minute transmission. Despite, there are many technologies available today to support IoT services; cellular systems can play a vital role for IoT services, like wearables, vehicular, and industrial IoT, rollout which have either mobility or security concern.  IoT services generated traffic are foreseen as a sporadic-bursty traffic. As the cellular networks are designed to serve continuous data traffic, the existing system’s access control mechanism cannot efficiently conform to the burstiness of traffic. This limits the scope of the network scalability in terms of simultaneous serving devices’ capacity. Also, this bursty pattern can extensively increase the rate of network’s congestion incident. In this thesis, we focus on these underlying challenges to support a large number of heterogeneous IoT services with existing services over the same radio network. An important question for supporting IoT services over cellular networks is how detrimental are the effects of IoT services on other services of cellular networks. This dissertation seeks to answer this with quantitative results to indicate the real constraints of existing networks. An important conclusion is that existing cellular system is incompetent to support the bursty arrival of massive IoT devices in terms of radio networks’ access control plane’s scalability. Therefore, this dissertation presents solutions to overcome the identified limitations of access control planes. To improve the performance of the access control plane, we incorporate a vertical core network controlled group management scheme that can assure the operator’s granular control over capillary gateways. Besides, this introduces a unique handover opportunity between cellular and capillary network vertices. Then, we present a simple but efficient initial access mechanism to overcome the initial access collision at the very early stage. Finally, we show the impact of access collision and retransmission on the initial access resource dimensioning.We present a practical traffic model that is realistic for the traffic scenario for mixed-traffic. Our presented results and analysis depict the trade-offs between access rate, retransmission and resource allocation over time and frequency.Our results reveal that with proposed schemes of the cellular system’s access control plane can be scalable and resilient to accommodate a large number of IoT devices without incurring extra delay or need of resources to the system.

QC 20170928

Future fifth generation (5G) cellular networks have to cope with the expected ten-fold increase in mobile data traffic between 2015 and 2021. To achieve this goal, new technologies are being considered, including massive multiple-input multiple-output (MIMO) systems and millimeter-wave (mmWave) communications. Massive MIMO involves the use of large antenna array sizes at the base station, while mmWave communications employ frequencies between 30 and 300 GHz. In this thesis we study the impact of these technologies on the performance of channel estimators. Our results show that the characteristics of the propagation channel at mmWave frequencies improve the channel estimation performance in comparison with current, low frequency-based, cellular networks. Furthermore, we demonstrate the existence of an optimal angular spread of the multipath clusters, which can be used to maximize the capacity of mmWave networks. We also propose efficient noise variance estimators, which can be employed as an input to existing channel estimators.

The next generation wireless networks i.e. 5G aim to provide multi-Gbps data traffic, in order to satisfy the increasing demand for high-definition video, among other high data rate services, as well as the exponential growth in mobile subscribers. To achieve this dramatic increase in data rates, current research is focused on improving the capacity of current 4G network standards, based on Long Term Evolution (LTE), before radical changes are exploited which could include acquiring additional/new spectrum. The LTE network has a reuse factor of one; hence neighbouring cells/sectors use the same spectrum, therefore making the cell edge users vulnerable to inter-cell interference. In addition, wireless transmission is commonly hindered by fading and pathloss. In this direction, this thesis focuses on improving the performance of cell edge users in LTE and LTE-Advanced (LTE-A) networks by initially implementing a new Coordinated Multi-Point (CoMP) algorithm to mitigate cell edge user interference. Subsequently Device-to-Device (D2D) communication is investigated as the enabling technology for maximising Resource Block (RB) utilisation in current 4G and emerging 5G networks. It is demonstrated that the application, as an extension to the above, of novel power control algorithms, to reduce the required D2D TX power, and multihop transmission for relaying D2D traffic, can further enhance network performance. To be able to develop the aforementioned technologies and evaluate the performance of new algorithms in emerging network scenarios, a beyond-the-state-of-the-art LTE system-level simulator (SLS) was implemented. The new simulator includes Multiple-Input Multiple-Output (MIMO) antenna functionalities, comprehensive channel models (such as Wireless World initiative New Radio II i.e. WINNER II) and adaptive modulation and coding schemes to accurately emulate the LTE and LTE-A network standards. Additionally, a novel interference modelling scheme using the 'wrap around' technique was proposed and implemented that maintained the topology of flat surfaced maps, allowing for use with cell planning tools while obtaining accurate and timely results in the SLS compared to the few existing platforms. For the proposed CoMP algorithm, the adaptive beamforming technique was employed to reduce interference on the cell edge UEs by applying Coordinated Scheduling (CoSH) between cooperating cells. Simulation results show up to 2-fold improvement in terms of throughput, and also shows SINR gain for the cell edge UEs in the cooperating cells. Furthermore, D2D communication underlaying the LTE network (and future generation of wireless networks) was investigated. The technology exploits the proximity of users in a network to achieve higher data rates with maximum RB utilisation (as the technology reuses the cellular RB simultaneously), while taking some load off the Evolved Node B (eNB) i.e. by direct communication between User Equipment (UE). Simulation results show that the proximity and transmission power of D2D transmission yields high performance gains for a D2D receiver, which was demonstrated to be better than that of cellular UEs with better channel conditions or in close proximity to the eNB in the network. The impact of interference from the simultaneous transmission however impedes the achievable data rates of cellular UEs in the network, especially at the cell edge. Thus, a power control algorithm was proposed to mitigate the impact of interference in the hybrid network (network consisting of both cellular and D2D UEs). It was implemented by setting a minimum SINR threshold so that the cellular UEs achieve a minimum performance, and equally a maximum SINR threshold to establish fairness for the D2D transmission as well. Simulation results show an increase in the cell edge throughput and notable improvement in the overall SINR distribution of UEs in the hybrid network. Additionally, multihop transmission for D2D UEs was investigated in the hybrid network: traditionally, the scheme is implemented to relay cellular traffic in a homogenous network. Contrary to most current studies where D2D UEs are employed to relay cellular traffic, the use of idle nodes to relay D2D traffic was implemented uniquely in this thesis. Simulation results show improvement in D2D receiver throughput with multihop transmission, which was significantly better than that of the same UEs performance with equivalent distance between the D2D pair when using single hop transmission.

This thesis focuses on the study of Heterogeneous Networks (HetNets), analyzing the system performance and the allocation of available resources, such as serving BSs, spectrum, power supply and storage. Specifically, four main research focuses are included. The first focus is load balancing problem in HetNets. First, a factor graph model is developed to represent the user association problem and decompose the network-wide objective into local utility functions. Then, a distributed belief propagation (BP) algorithm is proposed to find out the optimal user association. Furthermore, several properties of the factor graph relevant to the performance of the BP algorithm are analyzed using stochastic geometry. The second focus is inter-cell interference in HetNets. To mitigate the inter-cell interference and maximizing the system sum rate, a BP algorithm to jointly optimize the user association, sub-channel assignment and power allocation is proposed. Importantly, a novel factor graph model is developed that not only decomposes the network-wide objective but also transforms the constraints into local functions. The third focus is probabilistic small-cell caching in HetNets, where each SBS caches a subset of the popular content with a specific caching probability. The theoretical results of the successful download probability (SDP) are derived using stochastic geometry theory, i.e., the probability that users can successfully download required content from SBSs. Importantly, I optimize the caching probabilities in two network architectures by maximizing the SDP. The fourth focus is cooperative inter-working of LTE and wireless fidelity (Wi-Fi). A new framework is proposed that considers both systems, downlink and uplink transmissions, and interference in both time and spatial domains. Based on this framework, I theoretically study the performance of a large-scale Wi-Fi network, and the network performance of several inter-working strategies.

Historically mobile Radio Access Networks (RANs) were optimised initially to maximise coverage and subsequently to improve capacity, user data rates and quality of service. However, the recent exponential growth in the volume of transmitted data coupled with the ever increasing energy costs has highlighted the need to optimise futuristic RANs from an energy efficiency perspective. This research study postulated the utilisation of radio resource management approaches to improve the energy efficiency of modern RANs, with a particular emphasis on the radio frequency energy performance. The research study yielded the following major outcomes. First, there was notable positive correlation between user channel quality improvements and the energy efficiency of RANs. Second, channel quality aware packet schedulers were more energy efficient than channel quality ignorant packet schedulers. Third, energy aware scheduling metrics coupled with power control algorithms can be utilised to optimise and refine the energy efficiency performance of the rate adaptive frequency domain packet scheduling. Fourth, the dynamic temporal and spatial traffic load characteristics, in the radio access network, present energy saving opportunities through collaborative and cooperative Inter-Cell Interference (ICI) management among neighbouring base stations. While the results presented in this thesis pertain to radio frequency and/or radio head energy consumption, the improved energy efficiency could be leveraged by increasing the inter site distance between base stations subsequently reducing the density of base stations in any given geographical area thus reducing the energy consumption of the RANs as a whole. The benefits of energy efficient RANs are twofold, i.e. reduction in the amount of CO2 emission and lower operating expenditure (OPEX).

The fifth generation of wireless technology (5G) is positioned to address the demands and business contexts of 2020 and beyond. It is expected to enable a fully mobile and connected society, related to the significant growth in connectivity and volume of traffic that will be required in the near future. In this context, the millimeter wave (mmWave) spectrum is rapidly emerging as a key enabler of the 5G performance demands, thanks to the large available bandwidth at such high frequencies. Communication at mmWaves, however, suffers from severe path and penetration loss, requires the maintenance of directional transmissions and calls for the definition of new control operations for both cellular and vehicular networks. Among all the challenges that will be faced, in this thesis we (i) focus on the design of mobility management strategies for devices in idle and connected mode, (ii) investigate how to deploy mmWave networking architectures, (iii) validate the potential of the mmWave technology as a means to foster the automotive revolution towards connected and autonomous transportation systems, (iv) study the most promising options to broadcast vehicular sensory observations in an efficient way, and (v) envision how 5G technologies can evolve into 6G to address the needs of the future digital society. Among other results, we demonstrate the importance of combining multiple radio technologies into a single solution that is more robust and efficient than any individual approach, discuss the trade-offs of mobility management in 3GPP NR, and evaluate practical strategies for assigning value of information in 5G networks.

Dans le domaine des futurs réseaux sans fil 6G, l'intégration de la périphérie intelligente grâce à l'avènement de l'IA représente un bond en avant considérable, promettant des avancées révolutionnaires en matière de communication sans fil. Cette intégration favorise une synergie harmonieuse, capitalisant sur le potentiel collectif de ces technologies transformatrices. Au cœur de cette intégration se trouve le rôle de l'apprentissage fédéré, un paradigme d'apprentissage décentralisé qui préserve la confidentialité des données tout en exploitant l'intelligence collective des appareils interconnectés. Dans la première partie de la thèse, nous nous attaquons au problème de l'hétérogénéité statistique dans l'apprentissage fédéré, qui découle des distributions de données divergentes entre les ensembles de données des dispositifs. Plutôt que d'entraîner un modèle unique conventionnel, qui donne souvent de mauvais résultats avec des données non identifiées, nous proposons un ensemble de règles centrées sur l'utilisateur qui produisent des modèles personnalisés adaptés aux objectifs de chaque utilisateur. Pour atténuer la surcharge de communication prohibitive associée à l'apprentissage d'un modèle personnalisé distinct pour chaque utilisateur, les utilisateurs sont répartis en groupes sur la base de la similarité de leurs objectifs. Cela permet l'apprentissage collectif de modèles personnalisés spécifiques à la cohorte. En conséquence, le nombre total de modèles personnalisés formés est réduit. Cette réduction diminue la consommation de ressources sans fil nécessaires à la transmission des mises à jour de modèles sur des canaux sans fil à bande passante limitée. Dans la deuxième partie, nous nous concentrons sur l'intégration des dispositifs à distance de l'IdO dans la périphérie intelligente en exploitant les véhicules aériens sans pilote en tant qu'orchestrateur d'apprentissage fédéré. Alors que des études antérieures ont largement exploré le potentiel des drones en tant que stations de base volantes ou relais dans les réseaux sans fil, leur utilisation pour faciliter l'apprentissage de modèles est encore un domaine de recherche relativement nouveau. Dans ce contexte, nous tirons parti de la mobilité des drones pour contourner les conditions de canal défavorables dans les zones rurales et établir des terrains d'apprentissage pour les dispositifs IoT distants. Cependant, les déploiements de drones posent des défis en termes de planification et de conception de trajectoires. À cette fin, une optimisation conjointe de la trajectoire du drone, de l'ordonnancement du dispositif et de la performance d'apprentissage est formulée et résolue à l'aide de techniques d'optimisation convexe et de la théorie des graphes. Dans la troisième partie de cette thèse, nous jetons un regard critique sur la surcharge de communication imposée par l'apprentissage fédéré sur les réseaux sans fil. Bien que les techniques de compression telles que la quantification et la sparsification des mises à jour de modèles soient largement utilisées, elles permettent souvent d'obtenir une efficacité de communication au prix d'une réduction de la performance du modèle. Pour surmonter cette limitation, nous utilisons des réseaux aléatoires sur-paramétrés pour approximer les réseaux cibles par l'élagage des paramètres plutôt que par l'optimisation directe. Il a été démontré que cette approche ne nécessite pas la transmission de plus d'un seul bit d'information par paramètre du modèle. Nous montrons que les méthodes SoTA ne parviennent pas à tirer parti de tous les avantages possibles en termes d'efficacité de la communication en utilisant cette approche. Nous proposons une fonction de perte régularisée qui prend en compte l'entropie des mises à jour transmises, ce qui se traduit par des améliorations notables de l'efficacité de la communication et de la mémoire lors de l'apprentissage fédéré sur des dispositifs périphériques, sans sacrifier la précision
In the realm of future 6G wireless networks, integrating the intelligent edge through the advent of AI signifies a momentous leap forward, promising revolutionary advancements in wireless communication. This integration fosters a harmonious synergy, capitalizing on the collective potential of these transformative technologies. Central to this integration is the role of federated learning, a decentralized learning paradigm that upholds data privacy while harnessing the collective intelligence of interconnected devices. By embracing federated learning, 6G networks can unlock a myriad of benefits for both wireless networks and edge devices. On one hand, wireless networks gain the ability to exploit data-driven solutions, surpassing the limitations of traditional model-driven approaches. Particularly, leveraging real-time data insights will empower 6G networks to adapt, optimize performance, and enhance network efficiency dynamically. On the other hand, edge devices benefit from personalized experiences and tailored solutions, catered to their specific requirements. Specifically, edge devices will experience improved performance and reduced latency through localized decision-making, real-time processing, and reduced reliance on centralized infrastructure. In the first part of the thesis, we tackle the predicament of statistical heterogeneity in federated learning stemming from divergent data distributions among devices datasets. Rather than training a conventional one-model-fits-all, which often performs poorly with non-IID data, we propose user-centric set of rules that produce personalized models tailored to each user objectives. To mitigate the prohibitive communication overhead associated with training distinct personalized model for each user, users are partitioned into clusters based on their objectives similarity. This enables collective training of cohort-specific personalized models. As a result, the total number of personalized models trained is reduced. This reduction lessens the consumption of wireless resources required to transmit model updates across bandwidth-limited wireless channels. In the second part, our focus shifts towards integrating IoT remote devices into the intelligent edge by leveraging unmanned aerial vehicles as a federated learning orchestrator. While previous studies have extensively explored the potential of UAVs as flying base stations or relays in wireless networks, their utilization in facilitating model training is still a relatively new area of research. In this context, we leverage the UAV mobility to bypass the unfavorable channel conditions in rural areas and establish learning grounds to remote IoT devices. However, UAV deployments poses challenges in terms of scheduling and trajectory design. To this end, a joint optimization of UAV trajectory, device scheduling, and the learning performance is formulated and solved using convex optimization techniques and graph theory. In the third and final part of this thesis, we take a critical look at thecommunication overhead imposed by federated learning on wireless networks. While compression techniques such as quantization and sparsification of model updates are widely used, they often achieve communication efficiency at the cost of reduced model performance. We employ over-parameterized random networks to approximate target networks through parameter pruning rather than direct optimization to overcome this limitation. This approach has been demonstrated to require transmitting no more than a single bit of information per model parameter. We show that SoTA methods fail to capitalize on the full attainable advantages in terms of communication efficiency using this approach. Accordingly, we propose a regularized loss function which considers the entropy of transmitted updates, resulting in notable improvements to communication and memory efficiency during federated training on edge devices without sacrificing accuracy

In this thesis, we design advanced interference management techniques for future wireless networks under the availability of perfect and imperfect channel state information (CSI). We do so by considering a generalized imperfect CSI model where the variance of the channel estimation error depends on the signal-to-noise ratio (SNR). First, we analyze the performance of standard linear precoders, namely channel inversion (CI) and regularized CI (RCI), in downlink of cellular networks by deriving the received signal-to-interference-plus-noise ratio (SINR) of each user subject to both perfect and imperfect CSI. In this case, novel bounds on the asymptotic performance of linear precoders are derived, which determine howmuch accurate CSI should be to achieve a certain quality of service (QoS). By relying on the knowledge of error variance in advance, we propose an adaptive RCI technique to further improve the performance of standard RCI subject to CSI mismatch. We further consider transmit-power efficient design of wireless cellular networks. We propose two novel linear precoding techniques which can notably decrease the deployed power at transmit side in order to secure the same average output SINR at each user compared to standard linear precoders like CI and RCI. We also address a more sophisticated interference scenario, i.e., wireless interference networks, wherein each of the K transmitters communicates with its corresponding receiver while causing interference to the others. The most representative interference management technique in this case is interference alignment (IA). Unlike standard techniques like time division multiple access (TDMA) and frequency division multiple access (FDMA) where the achievable degrees of freedom (DoF) is one, with IA, the achievable DoF scales up with the number of users. Therefore, in this thesis, we quantify the asymptotic performance of IA under a generalized CSI mismatch model by deriving novel bounds on asymptotic mean loss in sum rate and the achievable DoF. We also propose novel least squares (LS) and minimum mean square error (MMSE) based IA techniques which are able to outperform standard IA schemes under perfect and imperfect CSI. Furthermore, we consider the implementation of IA in coordinated networks which enable us to decrease the number of deployed antennas in order to secure the same achievable DoF compared to standard IA techniques.

The steep growth in mobile data traffic has gained a lot of attention in recent years. With current infrastructure deployments and radio resources, operators will not be able to cope with the upcoming demands. Consequently, discussions of the next generation of mobile networks, referred to as the fifth generation (5G), have started in both academia and industry. In addition to more capacity, stringent requirements for improving energy efficiency, decreasing delays, and increasing reliability have been envisioned in 5G. Many solutions have been put forward, one of them being device-to-device (D2D) communications where users in close proximity can transmit directly to one another bypassing the base station (BS). In this thesis, we identify trade-offs and challenges of integrating D2D communications into cellular networks and propose potential solutions. To maximize gains from such integration, resource allocation and interference management are key factors. We start by introducing cooperation between D2D and cellular users in order to minimize any interference between the two user types and identifying the scenarios where this cooperation can be beneficial. It is shown that an increase in the number of cellular users within the coverage area and in the size of the cell is associated with a higher probability of cooperation. With this cooperation, we can potentially increase the number of connected devices, reduce the delay, increase the cell sum rate, and offload an overloaded cell. Next, we consider D2D communications underlaying the uplink of cellular networks. In such a scenario, any potential gain from resource sharing (time, frequency, or space) is determined by how the interference is managed. The quality and performance of the interference management techniques depend on the availability of the channel state information (CSI) and the location of nodes as well as the frequency of updates regarding such information. The more information is required, the more signaling is needed, which results in higher power consumption by the users. We investigate the trade-off between the availability of full CSI, which necessitates instantaneous information, and that of limited CSI, which requires infrequent updates. Our results show that with limited CSI, a good performance (in terms of the sum rate of both user types) can be achieved if a small performance loss is tolerated by cellular users. In addition, we propose a novel approach for interference management which only requires the information on the number of D2D users without any knowledge about their CSI. This blind approach can achieve a small outage probability with very low computational complexity when the number of scheduled D2D users is small. We then study the problem of mode selection, i.e., if a user should transmit in the D2D mode or in the conventional cellular mode. We identify the decision criteria for both overlay and underlay scenarios with two different objectives. We find out that the D2D communication is beneficial in macro cells or at cell boundaries. The area in which D2D mode is optimal varies with the objective of the network, transmit power, required quality-of-service, and the number of BS antennas. In the second part of this thesis, we study the effects of integration and coexistence of underlay D2D communications with another promising technology proposed for 5G, namely massive multiple-input-multiple-output (MIMO). Potential benefits of both technologies are known individually, but the possibility of and performance gains from their coexistence are not adequately addressed. We evaluate the performance of this hybrid network in terms of energy efficiency and the average sum rate. Comprehensive analysis reveals that the performance highly depends on the D2D user density. We conclude that underlay D2D communications can only coexist with massive MIMO systems in the regime of low D2D user density. By introducing a high number of D2D users, gains from the massive MIMO technology degrade rapidly, and therefore in this case, the D2D communications should use the overlay approach rather than the underlay, or the network should only allow a subset of D2D transmissions to be active at a time.
Den stora ökningen i mobildatatrafik de senaste åren har tilldragit sig mycket intresse. Med nuvarande infrastruktur och radioresurser kommer inte mobiloperatörerna att kunna hantera de kommande kraven. Därför har diskussioner kring den femte generationens (5G) mobila nätverk startat inom både akademin och industrin. Utöver högre kapacitet så kommer strikta krav på ökad energieffektivitet, minskad fördröjning samt ökad tillförlitlighet att planeras för 5G. En av många lösningar som har föreslagits är enhet-till-enhetskommunikation (device-to-device communications, D2D, på engelska), vilket innebär att närliggande mobilanvändare kan sända direkt till varandra utan att gå genom basstationen.  I denna avhandling identifierar vi kompromisser och problem kring, samt föreslår lösningar för, integrering av D2D-kommunikation i cellulära nätverk. Viktiga faktorer för att maximera vinsten av sådan integrering är resursallokering och störningshantering. Avhandlingen börjar med att beskriva samarbetet mellan D2D- och cellulära användare för att minska störningen mellan de två användartyperna, samt för att identifiera scenarier där denna typ av samarbete kan vara fördelaktigt. Vi visar att samarbetssannolikheten ökar med antalet cellulära användare i täckningsområdet, samt när cellstorleken ökar. Denna typ av samarbete kan användas för att öka antalet ansluta enheter, minska fördröjningen, öka cellsummadatataken eller avlasta överlastade celler.  Härnäst studerar vi D2D-kommunikation underliggande upplänken i cellulära nätverk. I ett sådant scenario bestäms eventuell vinst från resursdelning (t.ex. i tid, frekvens eller rymd) av hur störningen hanteras. Kvaliteten och prestandan hos störningshanteringen beror på tillgängligheten av kanalkännedom och information om nodernas position, samt uppdateringsfrekvensen för dessa. Ju mer information som behövs, desto mer signalering krävs, vilket leder till högre effektförbrukning hos användarna. Vi undersöker kompromissen mellan fullt tillgänglig kanalkännedom, vilket kräver momentan information, och ett scenario där kanalkännedomen är begränsad, vilket enbart kräver uppdatering med låg frekvens. Våra resultat visar att god summadatatakt kan uppnås när enbart begränsad kanalkännedom är tillgänglig, om en liten prestandaförlust tillåts för cellulära användare. Vi föreslår dessutom en ny metod för störningshantering som enbart kräver information om antalet D2D-användare, utan vetskap om deras kanalkännedom. Denna blinda metod kan uppnå hög täckningssannolikhet med låg beräkningskomplexitet när antalet schemalagda D2D-användare är lågt. Vi studerar även lägesvalsproblemet, dvs. om en användare ska sända i D2D-läge eller i konventionellt cellulärt läge. Vi karaktäriserar beslutskriterierna för både överliggande och underliggande scenarier med två olika objektivfunktioner och visar att D2D-kommunikation är fördelaktig i makroceller samt vid cellkanterna. Området för D2D-optimalitet varierar med objektivfunktionen för nätverket, sändeffekten, servicekvalitetskraven och antalet basstationsantenner.  I den andra delen av avhandlingen så studerar vi effekter kring integrering och samexistens av underliggande D2D-kommunikation med en annan lovande teknologi för 5G, nämligen massiv multiple input-multiple output (massiv MIMO). De individuella fördelarna för de två teknologierna är välkända, men eventuella prestandavinster när teknologierna samexisterar har inte studeras tillräckligt. Vi undersöker prestanda i detta hybridnätverk i termer av energieffektivitet och genomsnittlig summadatatakt. En noggrann analys visar att prestandan beror på tätheten av D2D-användare. Vi drar slutsatsen att underliggande D2D-kommunikation bara kan samexistera med massiv MIMO när tätheten av D2D-användare är låg. När det existerar många D2D-användare minskas prestandavinsten från massiv MIMO snabbt och därför bör D2D-kommunikationen ske i överliggande läge istället för underliggande läge. Alternativt kan nätverket tillåta att enbart en delmängd av D2D-sändningar är aktiva samtidigt.

QC 20150529

The proliferation of hand-held devices and Internet of Things (IoT) applications has heightened demand for popular content download. A high volume of content streaming/downloading services during peak hours can cause network congestion. Proactive content caching has emerged as a prospective solution to tackle this congestion problem. In proactive content caching, data storage units are used to store popular content in helper nodes at the network edge. This contributes to a reduction of peak traffic load and network congestion. However, data storage units require additional energy, which offers a challenge to researchers that intend to reduce energy consumption up to 90% in next generation networks. This thesis presents proactive content caching techniques to reduce grid energy consumption by utilizing renewable energy sources to power-up data storage units in helper nodes. The integration of renewable energy sources with proactive caching is a significant challenge due to the intermittent nature of renewable energy sources and investment costs. In this thesis, this challenge is tackled by introducing strategies to determine the optimal time of the day for content caching and optimal scheduling of caching nodes. The proposed strategies consider not only the availability of renewable energy but also temporal changes in network trac to reduce associated energy costs. While proactive caching can facilitate the reduction of peak trac load and the integration of renewable energy, cached content objects at helper nodes are often more vulnerable to malicious attacks due to less stringent security at edge nodes. Potential content leakage can lead to catastrophic consequences, particularly for cache-equipped Industrial Internet of Things (IIoT) applications. In this thesis, the concept of \trusted caching nodes (TCNs)" is introduced. TCNs cache popular content objects and provide security services to connected links. The proposed study optimally allocates TCNs and selects the most suitable content forwarding paths. Furthermore, a caching strategy is designed for mobile edge computing systems to support IoT task offloading. The strategy optimally assigns security resources to offloaded tasks while satisfying their individual requirements. However, security measures often contribute to overheads in terms of both energy consumption and delay. Consequently, in this thesis, caching techniques have been designed to investigate the trade-off between energy consumption and probable security breaches. Overall, this thesis contributes to the current literature by simultaneously investigating energy and security aspects of caching systems whilst introducing solutions to relevant research problems.

The widespread availability of many emerging services enabled by the Internet of Things (IoT) paradigm passes through the capability to provide long-range connectivity to a massive number of things, overcoming the well-known issues of ad-hoc, short-range networks. This scenario entails a lot of challenges, ranging from the concerns about the radio access network efficiency to the threats about the security of IoT networks. In this thesis, we will focus on wireless communication standards for long-range IoT as well as on fundamental research outcomes about IoT networks. After investigating how Machine-Type Communication (MTC) is supported nowadays, we will provide innovative solutions that i) satisfy the requirements in terms of scalability and latency, ii) employ a combination of licensed and license-free frequency bands, and iii) assure energy-efficiency and security.
La diffusione capillare di molti servizi emergenti grazie all’Internet of Things (IoT) passa attraverso la capacità di fornire connettività senza fili a lungo raggio ad un numero massivo di cose, superando le note criticità delle reti ad hoc a corto raggio. Questa visione comporta grandi sfide, a partire dalle preoccupazioni riguardo l’efficienza delle rete di accesso fino alle minacce alla sicurezza delle reti IoT. In questa tesi, ci concentreremo sia sugli standard di comunicazione a lungo raggio per l’IoT sia sulla ricerca di base per le reti IoT. Dopo aver analizzato come vengono supportate le comunicazioni Machine-to-Machine (M2M) oggi, forniremo soluzioni innovative le quali i) soddisfano i requisiti in termini di scalabilità e latenza, ii) utilizzano una combinazione di bande di frequenza licenziate e libere e iii) assicurano efficienza energetica e sicurezza.

To provide mobile hosts with seamless and broadband wireless Internet access, two fundamental problems that need to be tackled in wireless networking are transparently supporting host mobility and effectively utilizing wireless bandwidth. The increasing heterogeneity of wireless networks and the proliferation of wireless devices, however, severely expose the limitations of the paradigms adopted by existing solutions. In this work, we explore new research directions for addressing network heterogeneity and bandwidth scarcity in future wireless data networks. In addressing network heterogeneity, we motivate a transport layer solution for transparent mobility support across heterogeneous wireless networks. We establish parallelism and transpositionality as two fundamental principles to be incorporated in designing such a transport layer solution. In addressing bandwidth scarcity, we motivate a cooperative wireless network model for scalable bandwidth utilization with wireless user population. We establish base station assistance and multi-homed peer relay as two fundamental principles to be incorporated in designing such a cooperative wireless network model. We present instantiations based on the established principles respectively, and demonstrate their performance and functionality gains through theoretic analysis, packet simulation, and testbed emulation.

En la actualidad, la Internet de las Cosas (Internet of Things, IoT) es una tecnología esencial para la próxima generación de sistemas inalámbricos. La conectividad es la base de IoT, y el tipo de acceso requerido dependerá de la naturaleza de la aplicación. Uno de los principales facilitadores del entorno IoT es la comunicación machine-to-machine (M2M) y, en particular, su enorme potencial para ofrecer conectividad ubicua entre dispositivos inteligentes. Las redes celulares son la elección natural para las aplicaciones emergentes de IoT y M2M. Un desafío importante en las redes celulares es conseguir que la red sea capaz de manejar escenarios de acceso masivo en los que numerosos dispositivos utilizan comunicaciones M2M. Por otro lado, los sistemas celulares han experimentado un tremendo desarrollo en las últimas décadas: incorporan tecnología sofisticada y nuevos algoritmos para ofrecer una amplia gama de servicios. El modelado y análisis del rendimiento de estas redes multiservicio es también una tarea desafiante que podría requerir un gran esfuerzo computacional. Para abordar los desafíos anteriores, nos centramos en primer lugar en el diseño y la evaluación de las prestaciones de nuevos mecanismos de control de acceso para hacer frente a las comunicaciones masivas M2M en redes celulares. Posteriormente nos ocupamos de la evaluación de prestaciones de redes multiservicio y proponemos una nueva técnica analítica que ofrece precisión y eficiencia computacional. Nuestro principal objetivo es proporcionar soluciones para aliviar la congestión en la red de acceso radio cuando un gran número de dispositivos M2M intentan conectarse a la red. Consideramos los siguientes tipos de escenarios: (i) los dispositivos M2M se conectan directamente a las estaciones base celulares, y (ii) forman grupos y los datos se envían a concentradores de tráfico (gateways) que les proporcionan acceso a la infraestructura. En el primer escenario, dado que el número de dispositivos añadidos a la red aumenta continuamente, esta debería ser capaz de manejar el considerable incremento en las solicitudes de acceso. El 3rd Generation Partnership Project (3GPP) ha propuesto el access class barring (ACB) como una solución práctica para el control de congestión en la red de acceso radio y la red troncal. El ajuste correcto de los parámetros de ACB de acuerdo con la intensidad del tráfico es crítico, pero cómo hacerlo de forma dinámica y autónoma es un problema complejo cuya solución no está recogida en las especificaciones del 3GPP. Esta tesis doctoral contribuye al análisis del rendimiento y al diseño de nuevos algoritmos que implementen efectivamente este mecanismo, y así superar los desafíos introducidos por las comunicaciones masivas M2M. En el segundo escenario, dado que la heterogeneidad de los dispositivos IoT y las arquitecturas celulares basadas en hardware imponen desafíos aún mayores para permitir una comunicación flexible y eficiente en los sistemas inalámbricos 5G, esta tesis doctoral también contribuye al diseño de software-defined gateways (SD-GWs) en una nueva arquitectura propuesta para redes inalámbricas definidas por software que se denomina SoftAir. Esto permite manejar tanto un gran número de dispositivos como el volumen de datos que estarán vertiendo en la red. Otra contribución de esta tesis doctoral es la propuesta de una técnica novedosa para el análisis de prestaciones de redes multiservicio de alta capacidad que se basa en un nuevo enfoque del modelizado analítico de sistemas que operan a diferentes escalas temporales. Este enfoque utiliza el análisis del transitorio de una serie de subcadenas absorbentes y lo denominamos absorbing Markov chain approximation (AMCA). Nuestros resultados muestran que para un coste computacional dado, AMCA calcula los parámetros de prestaciones habituales de un sistema con mayor precisión, en comparación con los resultados obtenidos por otr
Nowadays, Internet of Things (IoT) is an essential technology for the upcoming generation of wireless systems. Connectivity is the foundation for IoT, and the type of access required will depend on the nature of the application. One of the leading facilitators of the IoT environment is machine-to-machine (M2M) communication, and particularly, its tremendous potential to offer ubiquitous connectivity among intelligent devices. Cellular networks are the natural choice for emerging IoT and M2M applications. A major challenge in cellular networks is to make the network capable of handling massive access scenarios in which myriad devices deploy M2M communications. On the other hand, cellular systems have seen a tremendous development in recent decades; they incorporate sophisticated technology and algorithms to offer a broad range of services. The modeling and performance analysis of these large multi-service networks is also a challenging task that might require high computational effort. To address the above challenges, we first concentrate on the design and performance evaluation of novel access control schemes to deal with massive M2M communications. Then, we focus on the performance evaluation of large multi-service networks and propose a novel analytical technique that features accuracy and computational efficiency. Our main objective is to provide solutions to ease the congestion in the radio access or core network when massive M2M devices try to connect to the network. We consider the following two types of scenarios: (i) massive M2M devices connect directly to cellular base stations, and (ii) they form clusters and the data is forwarded to gateways that provide them with access to the infrastructure. In the first scenario, as the number of devices added to the network is constantly increasing, the network should handle the considerable increment in access requests. Access class barring (ACB) is proposed by the 3rd Generation Partnership Project (3GPP) as a practical congestion control solution in the radio access and core network. The proper tuning of the ACB parameters according to the traffic intensity is critical, but how to do so dynamically and autonomously is a challenging task that has not been specified. Thus, this dissertation contributes to the performance analysis and optimal design of novel algorithms to implement effectively this barring scheme and overcome the challenges introduced by massive M2M communications. In the second scenario, since the heterogeneity of IoT devices and the hardware-based cellular architectures impose even greater challenges to enable flexible and efficient communication in 5G wireless systems, this dissertation also contributes to the design of software-defined gateways (SD-GWs) in a new architecture proposed for wireless software-defined networks called SoftAir. The deployment of these SD-GWs represents an alternative solution aiming at handling both a vast number of devices and the volume of data they will be pouring into the network. Another contribution of this dissertation is to propose a novel technique for the performance analysis of large multi-service networks. The underlying complexity of the network, particularly concerning its size and the ample range of configuration options, makes the solution of the analytical models computationally costly. However, a typical characteristic of these networks is that they support multiple types of traffic flows operating at different time-scales. This time-scale separation can be exploited to reduce considerably the computational cost associated to determine the key performance indicators. Thus, we propose a novel analytical modeling approach based on the transient regime analysis, that we name absorbing Markov chain approximation (AMCA). For a given computational cost, AMCA finds common performance indicators with greater accuracy, when compared to the results obtained by other approximate methods proposed in the literature.
En l'actualitat, la Internet de les Coses (Internet of Things, IoT) és una tecnologia essencial per a la propera generació de sistemes sense fil. La connectivitat és la base d'IoT, i el tipus d'accés requerit dependrà de la naturalesa de l'aplicació. Un dels principals facilitadors de l'entorn IoT és la comunicació machine-to-machine (M2M) i, en particular, el seu enorme potencial per oferir connectivitat ubiqua entre dispositius intel · ligents. Les xarxes mòbils són l'elecció natural per a les aplicacions emergents de IoT i M2M. Un desafiament important en les xarxes mòbils que actualment está rebent molta atenció és aconseguir que la xarxa siga capaç de gestionar escenaris d'accés massiu en què una gran quantitat de dispositius utilitzen comunicacions M2M. D'altra banda, els sistemes mòbils han experimentat un gran desenvolupament en les últimes dècades: incorporen tecnologia sofisticada i nous algoritmes per oferir una àmplia gamma de serveis. El modelatge i análisi del rendiment d'aquestes xarxes multiservei és també un desafiament important que podria requerir un gran esforç computacional. Per abordar els desafiaments anteriors, en aquesta tesi doctoral ens centrem en primer lloc en el disseny i l'avaluació de les prestacions de nous mecanismes de control d'accés per fer front a les comunicacions massives M2M en xarxes cel · lulars. Posteriorment ens ocupem de l'avaluació de prestacions de xarxes multiservei i proposem una nova tècnica analítica que ofereix precisió i eficiència computacional. El nostre principal objectiu és proporcionar solucions per a alleujar la congestió a la xarxa d'accés ràdio quan un gran nombre de dispositius M2M intenten connectar-se a la xarxa. Considerem els dos tipus d'escenaris següents: (i) els dispositius M2M es connecten directament a les estacions base cel · lulars, i (ii) formen grups i les dades s'envien a concentradors de trànsit (gateways) que els proporcionen accés a la infraestructura. En el primer escenari, atès que el nombre de dispositius afegits a la xarxa augmenta contínuament, aquesta hauria de ser capaç de gestionar el considerable increment en les sol · licituds d'accés. El 3rd Generation Partnership Project (3GPP) ha proposat l'access class barring (ACB) com una solució pràctica per al control de congestió a la xarxa d'accès ràdio i la xarxa troncal. L'ajust correcte dels paràmetres d'ACB d'acord amb la intensitat del trànsit és crític, però com fer-ho de forma dinàmica i autònoma és un problema complex, la solució del qual no està recollida en les especificacions del 3GPP. Aquesta tesi doctoral contribueix a l'anàlisi del rendiment i al disseny de nous algoritmes que implementen efectivament aquest mecanisme, i així superar els desafiaments introduïts per les comunicacions massives M2M en les xarxes mòbils actuals i futures. En el segon escenari, atès que l'heterogeneïtat dels dispositius IoT i les arquitectures cel · lulars basades en hardware imposen desafiaments encara més grans per permetre una comunicació flexible i eficient en els sistemes sense fil 5G, aquesta tesi doctoral també contribueix al disseny de software-defined gateways (SD-GWS) en una nova arquitectura proposada per a xarxes sense fils definides per programari que s'anomena SoftAir. Això permet gestionar tant un gran nombre de dispositius com el volum de dades que estaran abocant a la xarxa. Una altra contribució d'aquesta tesi doctoral és la proposta d'una tècnica innovadora per a l'anàlisi de prestacions de xarxes multiservei d'alta capacitat que es basa en un nou enfocament del modelitzat analític de sistemes que operen a diferents escales temporals. Aquest enfocament utilitza l'anàlisi del transitori d'una sèrie de subcadenes absorbents i l'anomenem absorbing Markov chain Approximation (AMCA). Els nostres resultats mostren que per a un cost computacional donat, AMCA calcula els paràmetres de prestacions habituals d
Tello Oquendo, LP. (2018). Design and Performance Analysis of Access Control Mechanisms for Massive Machine-to-Machine Communications in Wireless Cellular Networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/107946
TESIS

La quinta generación de redes móviles (5G) se encuentra a la vuelta de la esquina. Se espera provea de beneficios extraordinarios a la población y que resuelva la mayoría de los problemas de las redes 4G actuales. El éxito de 5G, cuya primera fase de estandarización ha sido completada, depende de tres pilares: comunicaciones tipo-máquina masivas, banda ancha móvil mejorada y comunicaciones ultra fiables y de baja latencia (mMTC, eMBB y URLLC, respectivamente). En esta tesis nos enfocamos en el primer pilar de 5G, mMTC, pero también proveemos una solución para lograr eMBB en escenarios de distribución masiva de contenidos. Específicamente, las principales contribuciones son en las áreas de: 1) soporte eficiente de mMTC en redes celulares; 2) acceso aleatorio para el reporte de eventos en redes inalámbricas de sensores (WSNs); y 3) cooperación para la distribución masiva de contenidos en redes celulares. En el apartado de mMTC en redes celulares, esta tesis provee un análisis profundo del desempeño del procedimiento de acceso aleatorio, que es la forma mediante la cual los dispositivos móviles acceden a la red. Estos análisis fueron inicialmente llevados a cabo por simulaciones y, posteriormente, por medio de un modelo analítico. Ambos modelos fueron desarrollados específicamente para este propósito e incluyen uno de los esquemas de control de acceso más prometedores: access class barring (ACB). Nuestro modelo es uno de los más precisos que se pueden encontrar en la literatura y el único que incorpora el esquema de ACB. Los resultados obtenidos por medio de este modelo y por simulación son claros: los accesos altamente sincronizados que ocurren en aplicaciones de mMTC pueden causar congestión severa en el canal de acceso. Por otro lado, también son claros en que esta congestión se puede prevenir con una adecuada configuración del ACB. Sin embargo, los parámetros de configuración del ACB deben ser continuamente adaptados a la intensidad de accesos para poder obtener un desempeño óptimo. En la tesis se propone una solución práctica a este problema en la forma de un esquema de configuración automática para el ACB; lo llamamos ACBC. Los resultados muestran que nuestro esquema puede lograr un desempeño muy cercano al óptimo sin importar la intensidad de los accesos. Asimismo, puede ser directamente implementado en redes celulares para soportar el tráfico mMTC, ya que ha sido diseñado teniendo en cuenta los estándares del 3GPP. Además de los análisis descritos anteriormente para redes celulares, se realiza un análisis general para aplicaciones de contadores inteligentes. Es decir, estudiamos un escenario de mMTC desde la perspectiva de las WSNs. Específicamente, desarrollamos un modelo híbrido para el análisis de desempeño y la optimización de protocolos de WSNs de acceso aleatorio y basados en cluster. Los resultados muestran la utilidad de escuchar el medio inalámbrico para minimizar el número de transmisiones y también de modificar las probabilidades de transmisión después de una colisión. En lo que respecta a eMBB, nos enfocamos en un escenario de distribución masiva de contenidos, en el que un mismo contenido es enviado de forma simultánea a un gran número de usuarios móviles. Este escenario es problemático, ya que las estaciones base de la red celular no cuentan con mecanismos eficientes de multicast o broadcast. Por lo tanto, la solución que se adopta comúnmente es la de replicar e contenido para cada uno de los usuarios que lo soliciten; está claro que esto es altamente ineficiente. Para resolver este problema, proponemos el uso de esquemas de network coding y de arquitecturas cooperativas llamadas nubes móviles. En concreto, desarrollamos un protocolo para la distribución masiva de contenidos, junto con un modelo analítico para su optimización. Los resultados demuestran que el modelo propuesto es simple y preciso, y que el protocolo puede reducir el con
La cinquena generació de xarxes mòbils (5G) es troba molt a la vora. S'espera que proveïsca de beneficis extraordinaris a la població i que resolga la majoria dels problemes de les xarxes 4G actuals. L'èxit de 5G, per a la qual ja ha sigut completada la primera fase del qual d'estandardització, depén de tres pilars: comunicacions tipus-màquina massives, banda ampla mòbil millorada, i comunicacions ultra fiables i de baixa latència (mMTC, eMBB i URLLC, respectivament, per les seues sigles en anglés). En aquesta tesi ens enfoquem en el primer pilar de 5G, mMTC, però també proveïm una solució per a aconseguir eMBB en escenaris de distribució massiva de continguts. Específicament, les principals contribucions són en les àrees de: 1) suport eficient de mMTC en xarxes cel·lulars; 2) accés aleatori per al report d'esdeveniments en xarxes sense fils de sensors (WSNs); i 3) cooperació per a la distribució massiva de continguts en xarxes cel·lulars. En l'apartat de mMTC en xarxes cel·lulars, aquesta tesi realitza una anàlisi profunda de l'acompliment del procediment d'accés aleatori, que és la forma mitjançant la qual els dispositius mòbils accedeixen a la xarxa. Aquestes anàlisis van ser inicialment dutes per mitjà de simulacions i, posteriorment, per mitjà d'un model analític. Els models van ser desenvolupats específicament per a aquest propòsit i inclouen un dels esquemes de control d'accés més prometedors: el access class barring (ACB). El nostre model és un dels més precisos que es poden trobar i l'únic que incorpora l'esquema d'ACB. Els resultats obtinguts per mitjà d'aquest model i per simulació són clars: els accessos altament sincronitzats que ocorren en aplicacions de mMTC poden causar congestió severa en el canal d'accés. D'altra banda, també són clars en què aquesta congestió es pot previndre amb una adequada configuració de l'ACB. No obstant això, els paràmetres de configuració de l'ACB han de ser contínuament adaptats a la intensitat d'accessos per a poder obtindre unes prestacions òptimes. En la tesi es proposa una solució pràctica a aquest problema en la forma d'un esquema de configuració automàtica per a l'ACB; l'anomenem ACBC. Els resultats mostren que el nostre esquema pot aconseguir un acompliment molt proper a l'òptim sense importar la intensitat dels accessos. Així mateix, pot ser directament implementat en xarxes cel·lulars per a suportar el trànsit mMTC, ja que ha sigut dissenyat tenint en compte els estàndards del 3GPP. A més de les anàlisis descrites anteriorment per a xarxes cel·lulars, es realitza una anàlisi general per a aplicacions de comptadors intel·ligents. És a dir, estudiem un escenari de mMTC des de la perspectiva de les WSNs. Específicament, desenvolupem un model híbrid per a l'anàlisi de prestacions i l'optimització de protocols de WSNs d'accés aleatori i basats en clúster. Els resultats mostren la utilitat d'escoltar el mitjà sense fil per a minimitzar el nombre de transmissions i també de modificar les probabilitats de transmissió després d'una col·lisió. Pel que fa a eMBB, ens enfoquem en un escenari de distribució massiva de continguts, en el qual un mateix contingut és enviat de forma simultània a un gran nombre d'usuaris mòbils. Aquest escenari és problemàtic, ja que les estacions base de la xarxa cel·lular no compten amb mecanismes eficients de multicast o broadcast. Per tant, la solució que s'adopta comunament és la de replicar el contingut per a cadascun dels usuaris que ho sol·liciten; és clar que això és altament ineficient. Per a resoldre aquest problema, proposem l'ús d'esquemes de network coding i d'arquitectures cooperatives anomenades núvols mòbils. En concret, desenvolupem un protocol per a realitzar la distribució massiva de continguts de forma eficient, juntament amb un model analític per a la seua optimització. Els resultats demostren que el model proposat és simple i precís
The 5th generation (5G) of mobile networks is just around the corner. It is expected to bring extraordinary benefits to the population and to solve the majority of the problems of current 4th generation (4G) systems. The success of 5G, whose first phase of standardization has concluded, relies in three pillars that correspond to its main use cases: massive machine-type communication (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communication (URLLC). This thesis mainly focuses on the first pillar of 5G: mMTC, but also provides a solution for the eMBB in massive content delivery scenarios. Specifically, its main contributions are in the areas of: 1) efficient support of mMTC in cellular networks; 2) random access (RA) event-reporting in wireless sensor networks (WSNs); and 3) cooperative massive content delivery in cellular networks. Regarding mMTC in cellular networks, this thesis provides a thorough performance analysis of the RA procedure (RAP), used by the mobile devices to switch from idle to connected mode. These analyses were first conducted by simulation and then by an analytical model; both of these were developed with this specific purpose and include one of the most promising access control schemes: the access class barring (ACB). To the best of our knowledge, this is one of the most accurate analytical models reported in the literature and the only one that incorporates the ACB scheme. Our results clearly show that the highly-synchronized accesses that occur in mMTC applications can lead to severe congestion. On the other hand, it is also clear that congestion can be prevented with an adequate configuration of the ACB scheme. However, the configuration parameters of the ACB scheme must be continuously adapted to the intensity of access attempts if an optimal performance is to be obtained. We developed a practical solution to this problem in the form of a scheme to automatically configure the ACB; we call it access class barring configuration (ACBC) scheme. The results show that our ACBC scheme leads to a near-optimal performance regardless of the intensity of access attempts. Furthermore, it can be directly implemented in 3rd Generation Partnership Project (3GPP) cellular systems to efficiently handle mMTC because it has been designed to comply with the 3GPP standards. In addition to the analyses described above for cellular networks, a general analysis for smart metering applications is performed. That is, we study an mMTC scenario from the perspective of event detection and reporting WSNs. Specifically, we provide a hybrid model for the performance analysis and optimization of cluster-based RA WSN protocols. Results showcase the utility of overhearing to minimize the number of packet transmissions, but also of the adaptation of transmission parameters after a collision occurs. Building on this, we are able to provide some guidelines that can drastically increase the performance of a wide range of RA protocols and systems in event reporting applications. Regarding eMBB, we focus on a massive content delivery scenario in which the exact same content is transmitted to a large number of mobile users simultaneously. Such a scenario may arise, for example, with video streaming services that offer a particularly popular content. This is a problematic scenario because cellular base stations have no efficient multicast or broadcast mechanisms. Hence, the traditional solution is to replicate the content for each requesting user, which is highly inefficient. To solve this problem, we propose the use of network coding (NC) schemes in combination with cooperative architectures named mobile clouds (MCs). Specifically, we develop a protocol for efficient massive content delivery, along with the analytical model for its optimization. Results show the proposed model is simple and accurate, and the protocol can lead to energy savings of up to 37 percent when compared to the traditional approach.
Leyva Mayorga, I. (2018). On reliable and energy efficient massive wireless communications: the road to 5G [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/115484
TESIS

The demand for wireless communication is ceaselessly increasing in terms of the number of subscribers and services. Future generations of cellular networks are expected to allow not only humans but also machines to be immersively connected. However, the radio frequency spectrum is already fully allocated. Therefore, developing techniques to increase spectrum efficiency has become necessary. This dissertation analyzes two spectrum sharing techniques that enable efficient utilization of the available radio resources in cellular networks. The first technique, called full-duplex (FD) communication, uses the same spectrum to transmit and receive simultaneously. Using stochastic geometry tools, we derive a closed-form expression of an upper-bound for the maximum achievable uplink ergodic rate in FD cellular networks. We show that the uplink transmission is vulnerable to the new interference introduced by FD communications (interference from the downlink transmission in other cells), especially when the disparity in transmission power between the uplink and downlink is considerable. We further show that adjusting the uplink transmission power according to the interference power level and the channel gain can improve the uplink performance in full-duplex cellular networks. Moreover, we propose an interference management technique that allows a flexible overlap between the spectra occupied by the downlink and uplink transmissions. The flexible overlap is optimized along with the user-to-base station association, the power allocation and the channel allocation in order to maximize a network-wide utility function. The second spectrum sharing technique, called non-orthogonal multiple access (NOMA), allows a transmitter to communicate with multiple receivers through the same frequency-time resource unit. We analyze the implementation of such a scheme in the downlink of cellular networks, more precisely, in the downlink of fog radio access networks (FogRANs). FogRAN is a network architecture that takes full advantage of the edge devices capability to process and store data. We propose managing the interference for NOMA-based FogRAN to improve the network performance by jointly optimizing user scheduling, the power allocated to each resource block and the division of power between the multiplexed users. The simulation results show that significant performance gains can be achieved through proper resource allocation with both studied spectrum sharing techniques.

碩士
國立交通大學
電信工程研究所
107
In this thesis, we develop a general modeling and analyzing framework for Internet of Things (IoT) devices over cellular neworks based on radio frequency (RF) wake-up. Because of the characteristic of low duty cycle, IoT devices can turn their main circuit off to save power when they have no data to transmit. However, IoT devices are possibly unable to respond to the wake-up signal or woken up by the interference. In order to analyze the system performance, we consider the fixed wake-up threshold and the location-dependent wake-up threshold schemes. By using stochastic geometry, we acquire the coverage probability and the energy efficiency, which are related to the performance of IoT applications. In our analysis, we find that the location-dependent wake-up threshold scheme achieves better performances under certain conditions, and we also present the trade-off between different considerations. The system performances are verified with both theoretical and simulation results.

1.1 Introduction Cellular technologies are evolving to help connect people and with the ever-increasing demand for and provision of Internet access. During this development cycle, there has been an increase in data speed, a decrease in latency and an improvement in the overall quality of communication that is carried out using the wireless medium. However, mobile networks are not only developing in this direction. There is an increase in aspects of the Internet of Things and machine-to-machine communication. This aspect is not new as such, but is gaining more and more popularity for various existing and new use cases that would enable a better connected world where technology enables such connectivity to improve the overall quality of life, safety and efficiency of various tasks. The concept is popularly known as the Internet of Things (IoT) and covers machine-to-machine (M2M) and machine-to-machine (MTC) communications with device use cases ranging from video surveillance requiring higher data rates to meter monitoring requiring very small, intermittent data capabilities . . The networks used to connect these IoT devices are usually referred to as Low Power Wide Area Networks (LPWAN) due to the nature of the devices that connect to such networks. The Narrowband IoT (a.k.a. NB-IoT) industry is on the rise. The most unique characteristic of NB-IoT is that it can be deployed over the operators existing network on the existing spectrum bands. One important feature of NB-IoT includes effective and efficient indoor coverage which cannot be matched by any other technology in this industry. It supports connections with massive low-throughput and low-cost devices. Low power consumption and optimized network architecture are some of the additional advantages worth mentioning. It is expected that NB-IoT will soon evolve into a large-scale deployment across various industries and across the world. The LPWAN market has existed for a decade now. The existing solutions in the market are fragmented and not standardized, hence leading to shortcomings like poor reliability, poor security, high operational and maintenance costs. Furthermore, the new overlay network deployment is not simple and involves lot of complexities. [22] NB-IoT overcomes the above issues by providing ubiquitous coverage, faster network upgrade, low power consumption, very long battery life, low cost terminal devices, high reliability and high carrier-class network security. The initial investment in the network implementation can be quite substantial and the superimposed costs are very little. In such a scenario, NB-IoT proves to be an ideal solution to the LPWA requirements. Moreover, it enables the communication service providers (CSPs) to enter into this new field. Traditional applications like smart tracking, smart metering, smart agriculture, smart parking, etc. can be provided by NB-IoT at and ultra-low cost ($5) per module and a extremely high connectivity (100K/cell) and opens up more industry opportunities like smart city, smart health and other low data rate applications yet to be uncovered. [22] NB-IoT is a new mobile radio access technology specified by the 3GPP in version 13 to address the rapidly expanding market for low power broadband connectivity. To ensure broad coverage and widespread adoption of NB-IoT services, MNOs (Mobile Network Operators) must ensure that devices and end-to-end services from different operators must connect to the NB-IoT systems that have been deployed. Data transfer options and connection modes must be well understood. [23] Various guidelines are available for the design and deployment of NB-IoT networks. This is done to ensure interoperability and smooth roaming. The GSMA guide contains the functions standardized in 3GPP Release 10-13, regarding the key functions that will be deployed in the coming time. The GSMA provided recommendations based on entry and implementation plans shared by members of the NB-IoT Operator Forum, which plan to roll out NB-IoT networks in more than 40 countries in Europe, the Middle East and Africa, South America and APAC, including Japan, China and South Korea.. Machine type correspondence (MTC) has a trademark which is expansive range of capacities. For instance, CCTV observation cameras need to convey immense measure of uplink (UL) information while being practically fixed. Then again, gadgets for armada following, pet following, and so on have a limited quantity of information while playing out a great deal of handovers. One more class of gadgets has neither of these abilities. Models for these incorporate gadgets for metering including power, gas or water utilization. These are many times standard and needn't bother with a streamlined handover. Non-defer delicate data is typically moved in little Delhi Technological University Study of Cellular-IoT and Development of a Business Case for Smart Campus Page 7 sums as it were. Nonetheless, the quantity of developing MTC gadgets might turn out to be very enormous, even up to a few significant degrees contrasted with the conventional gadgets. In any event, utilizing the current fast organizations would prompt an organization clog, in light of the fact that notwithstanding of their modest quantity of client information, how much flagging is about something very similar. The principal detail of NB-IoT focusses on this class of gadgets. These gadgets are frequently introduced at places without power supply. Subsequently, they run totally on battery and it could be extravagant to change the battery, since they may just be gotten to via prepared staff. Consequently, the battery lifetime now and again could decide the lifetime of the entire gadget. An enhanced power utilization is in this way fundamental for a legitimate activity. Moreover, the inclusion at these spots is in many cases very terrible. Subsequently, the indoor inclusion must be fundamentally improved, up to 23 dB are viewed as required. In this research, I have attempted to addresses the specialized potential outcomes of the equipment and programming engineering for terminals in view of LTE Feline M. I have attempted to give examinations that feature the contrasts between LTE Feline M and different classifications. Likewise, I have depicted the potential distinctions in structures among classes and how I can profit from the proposed changes in LTE Feline M. I have moreover tended to the LTE-NB (LTE Restricted Band) proposition that exist in 3GPP and contrasted them and existing advancements. Other contending advancements will likewise be contrasted with the LTE classifications and proposed classifications, featuring upsides and downsides. 1.2 Objective We at Delhi Technological University (DTU) are trying to develop a theoretical business pilot of a smart campus keeping the DTU Campus as a reference for the research. The main aim of this research is to improve the systems which exist and may also call for a full replacement of the existing system in case of implementing this pilot project. Under this project I plan to cover various domain including – smart classrooms, smart attendance, smart infrastructure including water and electricity management, smart parking, smart monitoring, pet tracking, implementation of AR/VR to improve the classroom experience, flipped classrooms, etc. With the advancements in technology, there has always been a change in the way the existing system operates. Technological advancements help in better capturing the requirements and data and also helps in taking preventive and corrective actions. The low power wide area (LPWA) technologies have always existed since a decade. However, large scale and wide geographical implementation of these technologies has pushed 3GPP to enable the mobile network operators (MNOs) to enter into the IoT space. With the standardization and wide implementation of cellular-IoT (CIoT) various new business cases can be implemented. Using the C-IoT technologies which include the underlying network of NB-IoT or LTE-Cat-M, I will try to present a theoretical business pilot. In this research I plan to include the details of the technologies including NB-IoT, LTE-Cat-M and justification why that particular technology should be implemented for the respective business case. 1.3 Conclusion Using the power of technology and with the growing IoT market in cellular domain, various business challenges can be solved and various new business cases can be implemented. Thus, the intention of implementing this pilot project is expected to lead to betterment in management of the resources, lower the wastage, enhance the learning experience, improve tracking and attendance systems. The underlying technology though explained may not be the soul solution to the project and the respective business case could be implemented using an alternative technology in the same domain. For example, implementation of a smart dustbin and waste management could be carried out using a NB-IoT network as well as LTE-Cat-M network. However, the case demands for the low data rate, stationary or low mobility solution which would call for implementing the NB-IoT network.

碩士
國立交通大學
電子工程學系 電子研究所
105
In this dissertation, we reduce the average delay for all devices transmission complete by reusing uplink resources. In this efficient way, we enhance the quality of service (QoS) and also reduce the energy consumption. In Machine to Machine (M2M) network, grouping method was proposed for managing massive devices. We use the grouping algorithm to find some appropriate coordinators to reduce energy consumption and overhead. In this hierarchical grouping method, coordi-nators are concentrated around the base station to help other devices to relay data. We propose a Multi-region concurrent transmission (MRCT) method which reuses the uplink resources to make all devices transmit complete in more stringent time, but the cost is energy consumption. Furthermore, we analyze the tradeoff between delay and energy consumption. We found relative efficient way, which delay improvement to energy de-grade ratio is the maximum. Then apply MRCT algorithm to achieve lower system delay.

Accompanied by the wide penetration of smartphones and other personal mobile devices in recent years, the foremost demand for cellular communications has been transformed from offering subscribers a way to communicate through low data rate voice call connections initially, into providing connectivity with good coverage, high data rate, as well as strong security for sensitive data transmission. To satisfy the demands for improved coverage and data rate, the cellular network is undergoing a significant transition from conventional macrocell-only deployment to heterogeneous network (HetNet), in which a multitude of radio access technologies can be co-deployed intelligently and flexibly. However, the small cells newly introduced in HetNet, such as picocells and femtocells, have complicated the network topology and the interference environment, thus presenting new challenges in network modeling and design. In recent studies, performance analyses were carried out accurately and tractably with the help of Poisson point process (PPP)-based base station (BS) model. This PPP-based model is extended in this work with the impact of directional antennas taken into account. The significance of this extension is emphasized by the wide usage of directional antennas in sectorized macrocell cells. Moreover, studies showed that little coverage improvement can be achieved if small cells are randomly deployed in a uniform-distributed way. This fact inspires us to explore the effect of the non-uniform BS deployment. We propose a non-uniform femtocell deployment scheme, in which femtocell BSs are not utilized if they are located close to any macrocell BSs. Based upon our analytical framework, this scheme can provide remarkable improvements on both coverage and data rate, thus stressing the importance of selectively deploying femtocell BSs by considering their relative locations with macrocell BSs. To alleviate the severe interference problem, the uplink attenuation technique is frequently employed in femtocell receivers to reduce the impact of interference from unattached terminals such that femtocell communication can take place. In order to analyze and optimize the femtocell system performance with this technique, we propose an analytical framework and demonstrate the performance tradeoff resulted from higher and lower uplink attenuation levels. Furthermore, we provide two improved uplink attenuation algorithms, which adaptively adjust to the information of the scheduled traffic, data rate requirement, and interference condition. Apart from the cellular coverage and data rate, communication security has been an important issue to be addressed due to the increasing demand for transmitting private and sensitive information over wireless networks. In the last part of the thesis, physical layer security, as a new way to improve wireless secrecy, is studied for cellular networks. By highlighting the unique cellular features offered by the carrier-operated high-speed backhaul, we investigate the probabilistic characterization of the secrecy rate, and identify the performance impacts of cell association and location information exchange between BSs. These results provide necessary network design guidelines for selecting the appropriate cell association method and information exchange range.

The Internet of Things (IoT) is a communication paradigm in which objects of everyday life will be able to, among others, communicate with one another, becoming an integral part of the Internet. In this context, wireless networking is expected to sustain the direct interaction between personal users’ devices and also to provide connectivity on large-scale resource-constrained devices. However, conventional networking protocols fail in large scale mobile wireless environments, such as IoT scenarios, due to node mobility, dynamic topologies, and intermittent connectivity. The Information-Centric Networking (ICN) has been considered the most promising candidate to overcome the drawbacks of host-centric architectures when applied to IoT networks. The main objective of this dissertation is to improve the network performance and the Content availability in mobile IoT environments based on the use of the ICN paradigm, which enables in-network caching and Content replication, thus facilitating the efficient and timely delivery of information. Therefore, it focuses on three primary goals: (1) the analysis of IoT environments regarding mobility aspects; (2) the design and implementation of an ICN caching proposal capable to take advantage of the context; (3) the incorporation of the previous proposal into an ICN architecture and the evaluation of the network performance. The proposal stands out for its use of a cache admission policy that uses information about the Content, the nodes, and the network to provide a more effective caching performance. The tests were conducted using three different mobility and connectivity datasets, addressing intermittent communications use cases. Based on the obtained results, it was possible to observe that the use of a cache admission policy, taking into consideration several parameters in the associated context of the Contents and nodes, provides benefits in terms of cache hits and evictions ratio, and request satisfaction ratio in mobile IoT environments.
A Internet das Coisas (IoT) é um paradigma de comunicação em que objetos da vida quotidiana poderão, entre outros, comunicar entre si, tornando-se parte integrante da Internet. Nesse contexto, espera-se que as redes sem fios mantenham a interação direta entre os mais diversos dispositivos com recursos limitados em larga escala. No entanto, os protocolos de rede convencionais falham em ambientes móveis sem fios de larga escala, como cenários de IoT, devido à mobilidade dos nós, topologias dinâmicas e conectividade intermitente. O conceito de Rede Centrada em Informação (ICN) foi considerado o candidato mais promissor para superar as desvantagens das arquiteturas host-centric quando aplicado a redes IoT. O principal objetivo desta dissertação é melhorar o desempenho da rede e a disponibilidade de Conteúdos em ambientes IoT móveis com base na utilização do paradigma de ICN, o qual permite armazenamento em cache na rede e a replicação de Conteúdos, facilitando a entrega eficiente e oportuna de informações. Portanto, esta concentra-se em três objetivos principais: (1) a análise dos ambientes IoT juntamente com os aspetos de mobilidade; (2) o desenho e a implementação de uma proposta de caching em ICN capaz de tirar proveito das informações de contexto; (3) a incorporação da proposta mencionada numa arquitetura ICN e a avaliação do seu desempenho da rede. A proposta destaca-se pelo uso de uma política de admissão de caching que usa informações sobre o Conteúdo, os nós e a rede, providenciando um desempenho da cache mais eficaz. Os testes realizados usaram três conjuntos de dados distintos de mobilidade e conectividade, abordando casos de uso com comunicações intermitentes. Com base nos resultados obtidos, foi possível perceber que o uso de uma política de admissão de caching que tem em consideração vários parâmetros no contexto associado aos Conteúdos e ao nós da rede, traz benefícios em termos do rácio de acessos com sucesso e de remoção da cache, e do rácio de pedidos satisfeitos em ambientes IoT móveis.
Mestrado em Engenharia de Computadores e Telemática

Wireless communications is on the brink of a major change. New technologies called multiple antenna systems (MIMO) and orthogonal frequency division multiple access (OFDMA) will be put together in the deployment of the next generation of cellular standards known as 4G. Consumers can expect peak data rates up to 160 Mbps. If the user is to have a good network experience with multimedia applications, then consistency in service data rates will be needed.

Yes
This study proposes a compact design of frequency-reconfigurable antenna array for fifth generation (5G) cellular networks. Eight compact discrete- fed slot antennas are placed on the top portion of a mobile phone printedcircuit- board (PCB) to form a beam-steerable array. The frequency response of the antenna can be reconfigured to operate at either 28 GHz or 38 GHz, two of the candidate frequency bands for millimeter-wave (MM-Wave) 5G communications. The reconfigurability function of the proposed design can be achieved by implementing and biasing a pair of diodes across each T-shaped slot antenna element. Rogers RT 5880 with thickness of 0.508 mm and properties of ε = 2.2 and δ = 0.0009 has been used as the antenna substrate. The antenna element is very compact in size with a good end-fire radiation pattern in the frequency bands of interest. The proposed beam-steerable array provides very good 3D coverage. The simulation results show that the proposed design provides some good characteristics fitting the need of the 5G cellular communications.
Innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET-722424, UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/E022936/1