This research addresses green communication issues, including energy efficiency, peak-to-average power ratio (PAPR) reduction and power amplifier (PA) linearization. Green communication is expected to be a primary goal in next generation cellular systems because it promises to reduce operating costs. The first key issue is energy efficiency of distributed antenna systems (DASs). The power consumption of high power amplifiers (HPAs) used in wireless communication systems is determined by the transmit power and drain efficiency. For unequal power allocation of orthogonal frequency division multiplexing (OFDM), the drain efficiency of the PA is determined by the PAPR and hence by the power distribution. This research proposes a PAPR-aware energy-efficient resource allocation scheme for joint orthogonal frequency division multiple access (OFDMA)/space division multiple access (SDMA) downlink transmission from DASs. Grouping-based SDMA is applied to exploit the spatial diversity while avoiding performance degradation from correlated channels. The developed scheme considers the impact of both system data rate and effective power consumption on the PAPR during resource allocation. We also present a suboptimal joint subcarrier and power allocation algorithm to facilitate implementation of power-efficient multi-channel wireless communications. By solving Karush-Kuhn-Tucker conditions, a closed-form solution for the power allocation of each remote radio head is obtained. The second key issue is related with PAPR reduction in the massive multiple-input multiple-output (MIMO) systems. The large number of PAs in next generation massive MIMO cellular communication system requires using inexpensive PAs at the base station to keep array cost reasonable. Large-scale multiuser (MU) MIMO systems can provide extra spatial degrees-of-freedom (DoFs) for PAPR reduction. This work applies both recurrent neural network (RNN)- and semidefinite relaxation (SDR)-based schemes for different purposes to reduce PAPR. The highly parallel structure of RNN is proposed in this work to address the issues of scalability and stringent requirements on computational times in PAPR-aware precoding problem. An SDR-based framework is proposed to reduce PAPR that accommodates channel uncertainties and intercell coordination. Both of the proposed structures reduce linearity requirements and enable the use of lower cost RF components for large-scale MU-MIMO-OFDM downlink. The third key issue is digital predistortion (DPD) in the massive MIMO systems. The primary source of nonlinear distortion in wireless transmitters is the PA, which is commonly modeled using polynomials. Conventional DPD schemes use high-order polynomials to accurately approximate and compensate for the nonlinearity of the PA. This is impractical for scaling to tens or hundreds of PAs in massive MIMO systems. This work therefore proposes a scalable DPD method, achieved by exploiting massive DoFs of next generation front ends. We propose a novel indirect learning structure which adapts the channel and PA distortion iteratively by cascading adaptive zero-forcing precoding and DPD. Experimental results show that over 70% of computational complexity is saved for the proposed solution, it is shown that a 3rd order polynomial with the new solution achieves the same performance as the conventional DPD using 11th order polynomial for a 100x10 massive MIMO configuration. / Ph. D. / The global climate change has emerged as a critical issue over the last decades. The increasing popularity of wireless communication networks, has resulted in information and communication technology becoming a non-negligible contributor to the overall carbon footprint. The increasing number of base stations and remote radio heads leads to higher operating expenditure mainly because of the higher energy consumption. This growth can be attributed not only to the increase in the number of smart devices in emerging economies, but also to the growth of shared multimedia data and online games. The wireless industry needs significant improvements in the energy efficiency of base stations and other network infrastructure to compensate for the increased energy demands from the network growth. Therefore, designing energy-efficient communication systems has become a critical issue for 5G, which promises massive deployment of smart devices served new infrastructure elements. In this dissertation, we primarily investigate the theoretical foundations and practical algorithms for the next generation wireless technologies, and discuss the impact of ongoing trends in cellular communications, such as shrinking cell sizes and multi-antenna system deployments, on energy-efficient 5G networks. The theoretical development and wireless algorithms are valuable for the deployment of next generation wireless network systems

In this thesis, resource allocation and multiple access in cognitive radio (CR) and compressed sensing (CS)-based wireless networks are studied. Energy-efficiency oriented design becomes more and more important in wireless systems, which motivates us to propose a location-aware power strategy for single user and multiple users in CR systems and a CS-based processing in wireless sensor networks (WSNs) which reduces the number of data transmissions and energy consumption by utilizing sparsity of the transmitted data due to spatial correlation and temporal correlation. In particular, the work on location-aware power allocation in CR system gives a brief overview of the existing power allocation design in the literature and unifies them into a general power allocation framework. The impact of the network topology on the system performance is highlighted, which motivates us to propose a novel location-aware strategy that intelligently utilizes frequency and space opportunities and minimizes the overall power consumption while maintaining the quality of service (QoS) of the primary system. This work shows that in addition to exploring the spectrum holes in time and frequency domains, spatial opportunities can be utilized to further enhance energy efficiency for CR systems. Then the work of resource allocation is extended to finding the power strategy and channel allocation optimization for multiple secondary users in an orthogonal frequency division multiplexing (OFDM) based cognitive radio network. Three different spectrum access methods are considered and utilized adaptively according to the different locations of the secondary users, and we unify these spectrum access methods into a general resource allocation framework. An interference violation test is proposed to decide the parameters in this framework that indicate the set of licensed channels to be sensed. The proposed scheme intelligently utilizes frequency and space opportunities, avoids unnecessary spectrum sensing and minimizes the overall power consumption while maintaining the quality of service of the primary system. The uncertainty of channel state information between the secondary users (SUs) and the primary users (PUs) is also taken into account in the study of power and channel allocation optimization of the SUs. Simulation results validate the effectiveness of the proposed method in terms of energy efficiency and show that enhanced performance can be obtained by utilizing spatial opportunities. The work on CS-based WSNs considers the application of compressed sensing to WSNs for data measurement communication and reconstruction, where N sensor nodes compete for medium access to a single receiver. Sparsity of the sensor data in three domains due to time correlation, space correlation and multiple access are being utilized. A CS-based medium access control (MAC) scheme is proposed and an in depth analysis on this scheme from a physical layer perspective is provided to reveal the impact of communication signal-to-noise ratio on the reconstruction performance. We show the process of the sensor data converted to the modulated symbols for physical layer transmission and how the modulated symbols recovered via compressed sensing. This work further identifies the decision problem of distinguishing between active and inactive transmitters after symbol recovery and provides a comprehensive performance comparison between carrier sense multiple access and the proposed CSbased scheme. Moreover, a network data recovery scheme that exploits both spatial and temporal correlations is proposed. Simulation results validate the effectiveness of the proposed method in terms of communication throughput and show that enhanced performance can be obtained by utilizing the sensed signal’s temporal and spatial correlations. / Graduate

Les communications sans fil prolifèrent dans presque chaque aspect de la société humaine : puissants ‘smart-phones' et ‘tablets', accès haut débit sans fil, et communications ‘machine-to-machine' ont généré des volumes de trafic de données imprévisibles quelques années en arrière. Dans ce nouveau paradigme, l'industrie des télécommunications se doit de garantir à la fois la durabilité économique des communications sans fil à large bande ainsi que la qualité de son service. En outre, il y a une forte incitation sociale à réduire les émissions de C02 duent aux communications mobiles, qui a augmenté notamment dans la dernière décennie. Dans ce contexte, l'intégration des ‘femtocells' dans les réseaux cellulaires est une solution à faible coût pour offrir une qualité de service élevée et en même temps de décharger le réseau macrocellule. Cependant, le déploiement massif et chaotique des points d'accès femtocell et leurs opérations non coordonnées peuvent conduire à une augmentation de l'interférence co-canal. De plus, un nombre élevé de cellules faiblement chargées augmente la consommation énergétique du réseau. Dans cette thèse, nous avons étudié les effets du déploiement de femtocells sur l'efficacité énergétique du réseau cellulaire. Par ailleurs, nous investiguons sur les mécanismes d'adaptation pour les réseaux des femtocells comme un moyen pour améliorer l'efficacité des communications mobiles. Notre objectif est de répondre dynamiquement à la demande des ressources afin de limiter la consommation d'énergie moyenne et l'interférence co-canal, tout en garantissant la qualité de service. Nous profitons du contexte inhabituel de communication ‘femtocellulaire' pour proposer des mécanismes d'allocation des ressources et des systèmes de gestion de réseau qui coordonne l'activité des points d'accès, la consommation d'énergie et de la couverture. Les résultats des simulations montrent que nos propositions améliorent l'efficacité énergétique et les performances perçues par les utilisateurs du système dans les réseaux ‘femtocellulaires' coopératives et autonomes. / Wireless communication proliferates into nearly each aspect of the human society, driving to the exponential growth in number of permanently connected devices. Powerful smart-phones and tablets, ubiquitous wireless broadband access, and machine-to-machine communications gen- erate volumes of data traffic that were unpredictable few years back. In this novel paradigm, the telecommunication industry has to simultaneously guarantee the economical sustainability of broadband wireless communications and users' quality of experience. Additionally, there is a strong social incentive to reduce the carbon footprint due to mobile communications, which has notably increased in the last decade. In this context, the integration of femtocells in cellular networks is a low-power, low-cost solution to offer high data rates to indoor customers and simultaneously offload the macrocell network. However, the massive and unplanned deployment of femtocell access points and their uncoordinated operations may result in harmful co-channel interference. Moreover, a high number of lightly loaded cells increases the network energy consumption. In this thesis, we investigate the effects of femtocells deployment on the cellular network energy efficiency. Moreover, we look into adaptive mechanisms for femtocell networks as a means to pave the way towards agile and economically viable mobile communications. Our goal is to dynamically match resource demand and offered capacity in order to limit the average power consumption and co-channel interference while guaranteeing quality of service constraints. We take advantage of the unusual communication context of femtocells to propose resource allocation and network management schemes that coordinate the access points activity, power consumption, and coverage. Simulation results show that our proposals improve system energy efficiency and users' performance in both networked and stand-alone femtocell deployment scenarios.

Solving the key issue of sustainability of battery-powered sensors continues to attract significant research attention. The prevailing theme of this research is to address this concern using energy-efficient protocols based on a form of simple cooperative transmission (CT) called the opportunistic large arrays (OLAs), and intelligent exploitation of energy harvesting and hybrid energy storage systems (HESSs). The two key contributions of this research, namely, OLA with transmission threshold (OLA-T) and alternating OLA-T (A-OLA-T), offer an signal-to-noise ratio (SNR) advantage (i.e., benefits of diversity and array (power) gains) in a multi-path fading environment, thereby reducing transmit powers or extending range. Because these protocols do not address nodes individually, the network overhead remains constant for high density networks or nodes with mobility. During broadcasting across energy-constrained networks, while OLA-T saves energy by limiting node participation within a single broadcast, A-OLA-T optimizes over multiple broadcasts and drains the the nodes in an equitable fashion. Another important contribution of this research is the design and analysis of a novel routing metric called communications using HESS (CHESS), which extends the rechargeable battery (RB)-life by relaying exclusively with supercapacitor (SC) energy, and is asymptotically optimal with respect to the number of nodes in the network.

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

Dans les systèmes de communications sans fil, la transmission de grandes quantités d'information et à faible coût énergétique sont les deux principales questions qui n'ont jamais cessé d'attirer l'attention de la communauté scientifique au cours de la dernière décennie. Récemment, il a été démontré que la communication coopérative est une technique intéressante notamment parce qu'elle permet d'exploiter la diversité spatiale dans le canal sans fil. Cette technique assure une communication robuste et fiable, une meilleure qualité de service (QoS) et rend le concept de coopération prometteur pour les futurs générations de systèmes cellulaires. Typiquement, les QoS sont le taux d'erreurs paquet, le débit et le délai. Ces métriques sont impactées par le délai, induit par les mécanismes de retransmission Hybrid-Automatic Repeat-Request (HARQ) inhérents à la réception d'un paquet erroné et qui a un retard sur la QoS demandée. En revanche, les mécanismes HARQ créent une diversité temporelle. Par conséquent, l'adoption conjointe de la communication coopérative et des protocoles HARQ pourrait s'avérer avantageux pour la conception de schémas cross-layer. Nous proposons tout d'abord une stratégie de maximisation de débit total dans un réseau cellulaire hétérogène. Nous introduisons un algorithme qui alloue la puissance optimale à la station de base (BS) et aux relais, qui à chaque utilisateur attribue de manière optimale les sous-porteuses et les relais. Nous calculons le débit maximal atteignable ainsi que le taux d'utilisateurs sans ressources dans le réseau lorsque le nombre d'utilisateurs actifs varie. Nous comparons les performances de notre algorithme à ceux de la littérature existante, et montrons qu'un gain significatif est atteint sur la capacité globale. Dans un second temps, nous analysons théoriquement le taux d'erreurs paquet, le délai ainsi que l'efficacité de débit des réseaux HARQ coopératifs, dans le canal à évanouissements par blocs. Dans le cas des canaux à évanouissement lents, le délai moyen du mécanisme HARQ n'est pas pertinent à cause de la non-ergodicité du processus. Ainsi, nous nous intéressons plutôt à la probabilité de coupure de délai en présence d'évanouissements lents. La probabilité de coupure de délai est de première importance pour les applications sensibles au délai. Nous proposons une forme analytique de la probabilité de coupure permettant de se passer de longues simulations. Dans la suite de notre travail, nous analysons théoriquement l'efficacité énergétique (bits/joule) dans les réseaux HARQ coopératifs. Nous résolvons ensuite un problème de minimisation de l'énergie dans les réseaux coopératifs en liaison descendante. Dans ce problème, chaque utilisateur possède une contrainte de délai moyen à satisfaire de telle sorte que la contrainte sur la puissance totale du système soit respectée. L'algorithme de minimisation permet d'attribuer à chaque utilisateur la station-relai optimale et sa puissance ainsi que la puissance optimale de la BS afin de satisfaire les contraintes de délai. Les simulations montrent qu'en termes de consommation d'énergie, les techniques assistées par relais prédominent nettement les transmissions directes, dans tout système limité en délai. En conclusion, les travaux proposés dans cette thèse peuvent promettre d'établir des règles fiables pour l'ingénierie et la conception des futures générations de systèmes cellulaires énergétiquement efficaces. / In wireless systems, transmitting large amounts of information with low energetic cost are two main issues that have never stopped drawing the attention of the scientific community during the past decade. Later, it has been shown that cooperative communication is an appealing technique that exploits spatial diversity in wireless channel. Therefore, this technique certainly promises a robust and reliable communications, higher quality-of-service (QoS) and makes the cooperation concept attractive for future cellular systems. Typically, the QoS requirements are the packet error rate, throughput and delay. These metrics are affected by the delay, where each erroneous packet is retransmitted several times according to Hybrid-Automatic Repeat-Request (HARQ) mechanism inducing a delay on the demanded QoS but a temporal diversity is created. Therefore, adopting jointly cooperative communications and HARQ mechanisms could be beneficial for designing cross-layer schemes. First, a new rate maximization strategy, under heterogeneous data rate constraints among users is proposed. We propose an algorithm that allocates the optimal power at the base station (BS) and relays, assigns subcarriers and selects relays. The achievable data rate is investigated as well as the average starvation rate in the network when the load, i.e. the number of active users in the network, is increasing. It showed a significant gain in terms of global capacity compared to literature. Second, in block fading channel, theoretical analyses of the packet error rate, delay and throughput efficiency in relayassisted HARQ networks are provided. In slow fading channels, the average delay of HARQ mechanisms w.r.t. the fading states is not relevant due to the non-ergodic process of the fading channel. The delay outage is hence invoked to deal with the slow fading channel and is defined as the probability that the average delay w.r.t. AWGN channel exceeds a predefined threshold. This criterion has never been studied in literature, although being of importance for delay sensitive applications in slow fading channels. Then, an analytical form of the delay outage probability is proposed which might be useful to avoid lengthy simulations. These analyses consider a finite packet length and a given modulation and coding scheme (MCS) which leads to study the performance of practical systems. Third, a theoretical analysis of the energy efficiency (bits/joule) in relay-assisted HARQ networks is provided. Based on this analysis, an energy minimization problem in multiuser relayassisted downlink cellular networks is investigated. Each user has an average delay constraint to be satisfied such that a total power constraint in the system is respected. The BS is assumed to have only knowledge about the average channel statistics but no instantaneous channel state information (CSI). Finally, an algorithm that jointly allocates the optimal power at BS, the relay stations and selects the optimal relay in order to satisfy the delay constrains of users is proposed. The simulations show the improvement in terms of energy consumption of relay-assisted techniques compared to nonaided transmission in delay-constrained systems. Hence, the work proposed in this thesis can give useful insights for engineering rules in the design of the next generation energyefficient cellular systems.