La densification des réseaux allant de pair avec le déploiement de petites cellules, les systèmes Massive MIMO disposent de caractéristiques prometteuses pour accroître la capacité des réseaux au travers des techniques de formation de faisceau, appelées beamforming. Les transmissions aux longueurs d’onde millimétriques (mmWave) sont, quant à elle, très convoitées car, non seulement les bandes passantes exploitables sont extrêmement larges, mais le canal de propagation est principalement Line-of-Sight (LOS), ce qui correspond à la visibilité directe entre le terminal et la station de base. L’attrait que peut avoir un système multi-utilisateurs Massive MIMO à de telles fréquences provient, en partie, du faible encombrement du réseau d’antennes, mais aussi du fort gain de beamforming dont il permet de bénéficier afin de contrecarrer les fortes pertes en espace libre que subissent les signaux à de telles longueurs d’onde. Dans un premier temps nous montrons comment l’augmentation de la fréquence porteuse impacte les performances de deux précodeurs connus. Au travers d’une modélisation déterministe et géométrique du canal, on simule un scénario Outdoor à faible mobilité et à forte densité de population en mettant en avant l’influence du trajet direct et des trajets réfléchis sur les performances. Plus précisément on prouve qu’en configuration purement LOS, le précodeur Zero-Forcing est beaucoup plus sensible à la structure du réseau d’antennes, et à la position des utilisateurs, que le Conjugate Beamforming (aussi connu sous le nom de retournement temporel). On introduit alors un précodeur basé uniquement sur la position angulaire des utilisateurs dans la cellule en référence à la station de base, puis l’on compare ses performances à celles des deux autres. La robustesse d’une telle implémentation à une erreur d’estimation d’angles est illustrée pour un scénario spécifique afin de souligner la pertinence des solutions angulaires, une direction étant plus facile à estimer et son évolution dans le temps plus prévisible.On décrit dans un second temps comment la connaissance des positions angulaires des utilisateurs permet d’accroître la capacité de la cellule par le biais d’un procédé d’allocation de puissance reposant sur une évaluation de l’interférence que chaque faisceau génère sur les autres. On prouve à l’aide de simulations que l’obtention de cette interférence, même exprimée sous une forme très simplifiée, permet d’améliorer très nettement la capacité totale de la cellule. Enfin, nous introduisons les systèmes Hybrides Numériques et Analogiques ayant récemment été proposés afin de permettre à une station de base de conserver un large nombre d’antennes, nécessaire à l’obtention d’un fort gain de beamforming, tout en réduisant le nombre de chaînes Radiofréquences (RF). On commence par décrire une solution permettant à un terminal de former un faisceau dont la direction s’adapte à sa propre inclinaison, en temps réel, pour toujours viser la station de base. On compare ensuite les performances de tels récepteurs, associés à des stations de base Massive MIMO, avec celles d’une solution hybride connue, le nombre de chaînes RF des deux systèmes étant identiques. Principalement, la flexibilité et la capacité d’évolution de ces systèmes est mise en avant, ces deux atouts étant particulièrement pertinents pour de nombreux environnements à forte densité de population. / As wireless communication networks are driven toward densification with small cell deployments, massive MIMO technology shows great promises to boost capacity through beamforming techniques. It is also well known that millimeter-Wave systems are going to be an important part of future dense network solutions because, not only do they offer high bandwidth, but channel is mostly Line-of-Sight (LOS). The attractiveness of using a multi-user Massive MIMO system at these frequencies comes partly from the reduced size of a many antenna base station, but also from the high beamforming gains they provide, which is highly suited to combat the high path losses experienced at such small wavelengths. First we show how raising the carrier frequency impacts the performance of some linear precoders widely used in Massive MIMO systems. By means of a geometrical deterministic channel model, we simulate a dense outdoor scenario and highlight the influence of the direct and multi-paths components. More importantly we prove that, in a Line-of-Sight (LOS) configuration, the discriminating skill of the well-known Zero Forcing precoder is much more sensitive to the antenna array structure and the user location than the Conjugate Beamforming precoder, also known as Time-Reversal. A precoder based on the knowledge of the angular position of all users is then introduced and compared to the other precoders based on channel response knowledge. Its robustness against angle estimation error is illustrated for a specific scenario and serves to back up the importance such a solution represents for future dense 5G networks, angular information being easier to estimate, and more so to keep track of.After that, we show how the knowledge of Directions of Arrival can be used to increase the sum capacity of a multi-user transmission through leakage based power allocation. This allocation uses an estimation of inter-user interference, referred to as Leakage, and we show through simulations how this factor, even under its most simplified form, improves realistic transmissions. Moreover this solution is not iterative and is extremely easy to implement which makes it particularly well suited for high deployment scenarios.Finally we introduce the Hybrid Analog and Digital Beamforming systems that have recently emerged to retain a high number of antennas without as many Radio Frequency (RF) chains, in order to keep high beamforming gains while lowering the complexity of conceiving many antenna base stations. We first describe a user equipment solution allowing the system to form a beam that adapts to its own movement so that it always focuses its energy toward the base station, using an on-board analog array and an Inertial Measurement Unit. Then we compare the performance of a known Hybrid solution with a fully digital Massive MIMO system, having as many RF chains as the Hybrid system, but serving user equipments with beamforming abilities. Mostly we emphasize how such a system allows for great flexibility and evolution, both traits being invaluable features in many future networks.

In the last decade, wireless applications have witnessed a tremendous growth. This can be envisioned in the surge of smart devices which became almost in everyone's possession, demand for high speed connection and the internet of things (IoT) along with its enabling technologies. Hence, the multiuser interference became the main limiting factor in wireless communications. Moreover, just like diamonds and emeralds, the electromagnetic spectrum is limited and precious. Therefore, the high data rate application may not be satisfied by our current technologies. In order to solve this spectrum scarcity problem, researchers have steered their focus to develop new techniques such as cognitive radio (CR) and in-band full-duplex (FD). However, these systems suffer from the interference problem that can dramatically impede their quality-of-service (QoS). Therefore, investigating communication techniques/systems that can relieve the interference adverse signature becomes imperative. Improper Gaussian signaling (IGS) has been recently shown to outperform the traditional proper Gaussian signaling (PGS) in several interference-limited systems. In this thesis, we use IGS in order to mitigate the interference issue in three different communication settings. IGS has the ability to control the interference signal dimension, and hence, it can be considered as one form of interference alignment. In the first part, we investigate an underlay CR system with in-band FD primary users (PUs) and one-way communication for the secondary user (SU). IGS is employed to alleviate the interference introduced by the SU on the PUs. First, we derive a closed form expression and an upper bound for the SU and PUs outage probabilities, respectively. Second, we optimize the SU signal parameters, represented in its power and the circularity coefficient, to achieve the design objectives of the SU while satisfying certain QoS constraints for the PU under instantaneous, average and partial channel state information (CSI). Finally, we provide some numerical results that demonstrate the advantages that can be reaped by using IGS to access the spectrum of the FD PUs. Specifically, with the existence of week PU direct channels and/or strong SU interference channels, PGS tends to use less transmit power while IGS uses more power along with increasing the signal impropriety. Part 2 studies the potential employment of IGS in FD cooperative settings with non-negligible residual self-interference (RSI). In this part, IGS is used in an attempt to alleviate the RSI adverse effect in full-duplex relaying (FDR). To this end, we derive a tight upper bound expression for the end-to-end outage probability in terms of the relay signal parameters. We further show that the derived upper bound is either monotonic or unimodal in the relay's circularity coefficient. This result allows for easily locating the global optimal point using known numerical methods. Based on the analysis, IGS allows FDR systems to operate even with high RSI. It is shown that, while the communication totally fails with PGS as the RSI increases, the IGS outage probability approaches a fixed value that depends on the channel statistics and target rate. The obtained results show that IGS can leverage higher relay power budgets than PGS to improve the performance, meanwhile it relieves its RSI impact via tuning the signal impropriety. In part 3, we investigate the potential benefits of adopting IGS in a two-hop alternate relaying (AR) system. Given the known benefits of using IGS in interference-limited networks, we propose to use IGS to relieve the inter-relay interference (IRI) impact on the AR system assuming no CSI is available at the source. In this regard, we assume that the two relays use IGS and the source uses PGS. Then, we optimize the degree of impropriety of the relays signal, measured by the circularity coefficient, to maximize the total achievable rate. Simulation results show that using IGS yields a significant performance improvement over PGS, especially when the first hop is a bottleneck due to weak source-relay channel gains and/or strong IRI.

The Chief Security Officer Problem (CSO) consists of a CSO, a group of agents trying to communicate with the CSO and a group of eavesdroppers trying to listen to the conversations between the CSO and its agents. Through Lemmas and Theorems, several Information Theoretic questions are answered.

[pt] Os sistemas de múltiplas antenas empregam diferentes técnicas de processamento de sinais em ambos extremos do sistema de comunicações para se beneficiar das múltiplas dimensões espaciais e transmitir para diversos usuarios usando os mesmos recursos de tempo e frequência. Desta forma, uma alta eficiência espectral pode ser atingida sem precisar de largura de banda extra. No entanto, o desempenho depende de uma estimativa do canal altamente precisa do lado do transmissor, a qual é denominada channel state information at the transmitter (CSIT). Se o valor estimado do canal for perfeito, o sistema consegue suprimir a interferência multiusuário (MUI), que é a principal responsável pela degradação do desempenho do sistema. Porém, supor uma estimativa perfeita é bastante otimista pois sistemas reais introduzem incerteza devido ao processo de estimação, a erros de quantização e a retardos próprios dos sistemas. Nesse contexto, a técnica conhecida como divisão de taxas ou rate splitting (RS) surge como uma ferramenta promissora para lidar com as imperfeições na estimativa do canal. RS divide os dados em um fluxo comum e vários fluxos privados e então sobrepõe o fluxo comum no topo dos fluxos privados. Esta tese propõe várias técnicas de processamento que aumentam ainda mais os benefícios dos sistemas RS. Neste trabalho, consideramos o downlink (DL) de um sistema de comunicações sem fio onde o transmissor envia mensagens independentes para cada usuário. A métrica usada para avaliar o desempenho do sistema é a soma das taxas ergódica (ESR). Diferente dos trabalhos convencionais em RS, consideramos que os terminais dos usuários estão equipados com múltiplas antenas. Isso nos permite implementar na recepção combinadores de fluxos que aumentem a taxa do fluxo comum. Aumentar esta taxa é um dos grandes problemas dos sistemas RS, uma vez que a taxa comum é limitada pelo pior usuário o que pode degradar fortemente o desempenho do sistema. Assim, três combinadores de fluxos diferentes são propostos e as expressões analíticas para calcular a soma das taxas são apresentadas. Os combinadores são derivados empregando-se os critérios Min-Max, MRC e MMSE. O critério Min-Max seleciona para cada usuário a melhor antena para decodificar o símbolo comum. O MRC visa maximizar o SNR ao decodificar o símbolo comum. Finalmente, o critério MMSE minimiza o quadrado da diferença entre o símbolo comum e o sinal recebido. Até o momento, RS foi considerado com precodificadores lineares. Devido a isto, neste trabalho investigamos o desempenho do RS com precodificadores não lineares. Para este fim, usamos diferentes tipos de precodificador Tomlinson-Harashima (THP) baseados nos precodificadores lineares ZF e MMSE. Em seguida, propomos um algoritmo multi-branch (MB) adequado para o RS-THP proposto. Este algoritmo cria vários padrões de transmissão e seleciona o melhor padrão para efetuar a transmissão. Esta técnica de préprocessamento aumentam ainda mais a soma das taxas obtida, uma vez que o desempenho do THP depende da ordem dos símbolos, porém também aumenta a complexidade computacional. Expressões analíticas para calcular a soma das taxas das técnicas propostas são derivadas por meio de análises estatísticas dos principais parâmetros. Finalmente, propomos quatro técnicas adaptativas diferentes de alocação de potência, as quais se caracterizam por sua baixa complexidade computacional. Duas destas técnicas são projetadas para sistemas SDMA convencionais, enquanto as outras duas são projetadas para sistemas RS. Um dos principais objetivos dos algoritmos propostos é realizar uma alocação de potência robusta capaz de lidar com os efeitos prejudicias das imperfeições no CSIT. É importante mencionar que a alocação de potência em sistemas RS é uma das tarefas mais importantes e deve ser realizada com extremo cuidado. Se a potência não for alocada corretamente, o desempenho do sistema RS será bastante degradado e as arquiteturas convencionais, como SDMA e NOMA, poderão ter um desempenho melhor. No entanto, a alocação de potência em sistemas RS precisa da solução de problemas complexos de otimização, o que aumenta o tempo gasto no processamento do sinal. Os algoritmos adaptativos propostos reduzem a complexidade computacional e são uma solução atrativa para aplicações práticas em sistemas de grande porte. / [en] Multiple-antenna systems employ different signal processing techniques at both ends of the communication to exploit the spatial dimensions and serve multiple users simultaneously in the same time-frequency domain. In this way, high spectral efficiency can be reached without the need of extra bandwidth. However, such gain depends on a highly accurate channel state information at the transmitter (CSIT). Perfect CSIT allows the system to suppress the multi user interference (MUI), which is the main responsible of the performance degradation. Nonetheless, assuming perfect CSIT is rather optimistic since the estimation procedure, quantization errors and delays of real system lead to CSIT uncertainties. In this context, rate splitting (RS) has arisen as a promising technique to deal with CSIT imperfections. Basically, RS splits the data into a common stream and private streams and then superimposes the common stream on top of the private streams. This thesis proposes several processing techniques which further enhance the benefits of RS systems. We consider the downlink (DL) of a wireless communications system, where the transmitter sends independent messages to each receiver. The ergodic sum rate (ESR) is adopted as the main metric to evaluate the performance of the system. Different from conventional RS works, we consider that the users are equipped with multiple antennas. This allows us to implement stream combiners for the common stream at the receivers. The implementations of the stream combiners improves the common rate performance, which is a major problem of RS systems since the common rate is limited by the performance of the worst user and can be heavily degraded. In this work, three different stream combiners are proposed along with analytical expressions to compute their sum rate performance. Specifically, the combiners are derived employing the min-max, maximum ratio combining (MRC), and minimum mean square error (MMSE) criteria. The min-max criterion selects at each user the best receive antenna to decode the common symbol. The MRC criterion aims at maximizing the SNR when decoding the common symbol. Finally, the MMSE criterion minimizes the squared difference between the common symbol and the received signal. So far, RS has been predominantly considered with channel inversiontype linear precoders. Therefore, this motivates us to investigate the performance of RS with non-linear precoders. For this purpose, we employ different architectures of the Tomlinson-Harashima precoder (THP) which are based on the zero-forcing (ZF) and MMSE precoders. We then propose a multi-branch (MB) algorithm for the proposed RS-THP, which creates several transmit patterns and selects the best for transmission. This pre-processing techniques further enhance the sum rate obtained since the performance of THP is dependent on the symbol ordering but also increases the computational complexity. Analytical expressions to calculate the sum rate of the proposed techniques are derived through statistical evaluation of key parameters. Finally, we propose four different adaptive power allocation techniques, which are characterized by their low computational complexity. Two of them are designed for conventional SDMA systems whereas the other two are intended for RS systems. One major objective of the proposed algorithms is to perform robust power allocation capable of dealing with the detrimental effects of imperfect CSIT. It is important to mention that power allocation in RS systems is one of the critical tasks that should be carefully performed. If the power is not properly allocated the performance of RS systems is heavily degraded and conventional architectures such as SDMA and NOMA could perform better. However, RS rely on solving complex optimization problems to perform power allocation, increasing the time and effort dedicated to signal processing. The proposed adaptive power allocation algorithms reduce the computational complexity and are an attractive solution for practical applications with large-scale systems.

This thesis comprises two parts: the first part presents channel-adaptive techniques to achieve high spectral efficiency in a single user multiple-input multiple-output (MIMO) system; the second part exhibits a programmable and reconfigurable software-defined-radio orkbench(SDR-WB) in the Matlab/Octave environment that accommodates a variety of wireless applications. In an attempt to achieve high spectral efficiency, an adaptive modulation technique is applied at the transmitter to vary the data rate depending on the channel state information (CSI). To further enhance the spectral efficiency, adaptive power allocation schemes are applied in the spatial domain to adjust the power on every transmit antenna. We analyze several power control schemes subject to a peak power constraint to maximize the spectral efficiency given an instantaneous target bit-error-rate (BER). A novel power allocation trategy is proposed to achieve high spectral efficiency with relatively low complexity. In addition, adaptive techniques that switch across different MIMO schemes enables even higher spectral efficiency by choosing the scheme with the highest spectral efficiency. We propose a new method to switch between spatial multiplexing with zero-forcing (ZF) detection and orthogonal space-time block coding (OSTBC). This is done by exploiting closed form expressions of the spectral efficiencies--discrete rate spectral efficiency--and finding the crossing points of the two curves. The proposed adaptation scheme adds limited complexity to the transmitter since it requires only statistical information of the channel, which does not change as time evolves. Software Defined Radio (SDR) has received more and more interest recently as a promising multi-band multi-standard solution for transceiver design. In order to support as many wireless applications as possible, we build up a programmable and reconfigurable workbench, namely SDR-WB, in Matlab/Octave environment. The workbench is functionally modularized into generic blocks to facilitate fast development and verification of new algorithms and architectures. The modulation formats that are currently supported by the SDR-WB are MIMO, Orthogonal frequency-division multiplexing (OFDM), MIMO-OFDM, DS-CDMA and Filtered Multitone (FMT). / QC 20101108

Le système OFDM (Orthogonal Frequency Division Multiplexing) utilise plusieurs sous-porteuses pour transmettre de l’information. Comparé à un schéma mono-porteuse, la modulation multi-porteuses OFDM permet d’obtenir facilement des réglages optimaux (au sens de la capacité de Shannon) pour une transmission à haut débit sur un canal sélectif en fréquence. En ce sens, on peut alors garantir une transmission fiable et une meilleure gestion de l'énergie utilisée. Lors de la transmission avec une modulation OFDM, les sous-porteuses utilisent des canaux différents qui n’ont pas forcement la même atténuation. Allouer le même niveau de puissance à chaque sous-porteuse ne garantit pas une capacité optimale dans une liaison point à point. Une allocation dynamique de la puissance (c’est-à-dire attribuer différents niveaux de puissance aux sous-porteuses en fonction du canal) donne de meilleures performances. Par contre, dans une situation de diffusion (broadcast), l’émetteur ne connaît pas les canaux vers tous les utilisateurs, et la meilleure stratégie consiste à émettre avec la même puissance sur toutes les sous-porteuses. Cette thèse a pour objectif d’explorer les situations intermédiaires, et de proposer les outils d’allocation de puissance appropriés. Cette situation intermédiaire est appelée « multicast », ou « multidiffusion » : l’émetteur envoie les signaux vers un nombre fini (pas trop grand) d’utilisateurs, dont il connaît les paramètres de canaux, et il peut adapter son émission à cette connaissance des canaux. On est donc dans une situation intermédiaire entre le « point à point » et la « diffusion ». L’objectif final de ce travail est d’évaluer le gain apporté par la connaissance des canaux en situation de multicast par rapport à la même communication effectuée comme si on était en diffusion. Bien évidemment, quand le nombre de destinataires est très grand, les gains seront négligeables, car le signal rencontre un nombre très élevé de canaux, et une allocation de puissance uniforme sera quasi optimale. Quand le nombre est très faible, on sera proche du point à point et les gains devraient être sensibles. Nous proposons des outils pour quantifier ces améliorations dans les cas de systèmes ayant une antenne à l'émission et une antenne à la réception, dit SISO (Single Input Single Output) et de systèmes avec plusieurs antennes, dits MIMO (Multiple Input Multiple Output). Les étapes nécessaires pour réaliser ce travail sont : 1) En supposant une connaissance préalable de l’état des canaux (entre station de base et terminaux), mettre en œuvre les outils de la théorie de l'information pour effectuer l’allocation de puissance et évaluer les capacités des systèmes étudiés. 2) Pour le système multi-utilisateur SISO-OFDM, nous proposons un algorithme d'allocation de puissance sur chaque sous porteuse dans une situation de multicast. 3) Pour le système multi-utilisateur MIMO-OFDM, nous proposons un algorithme qui exploite les caractéristiques du précodage "zero forcing". L'objectif est alors de partager la puissance disponible entre toutes les sous-porteuses et toutes les antennes. 4) Enfin, dans une dernière étape nous nous intéressons à une conception efficace de la situation de diffusion, afin de déterminer à l’aide d’outils de géométrie stochastique quelle zone peut être couverte afin qu’un pourcentage donné d’utilisateurs reçoivent une quantité d’information déterminée à l’avance. Ceci permet de déterminer la zone de couverture sans mettre en œuvre des simulations intensives. La combinaison de ces outils permet un choix efficace des situations qui relèvent de la « diffusion », du « multicast » et du « point à point ». / The OFDM (Orthogonal Frequency Division Multiplexing) system uses multiple sub-carriers for data transmission. Compared to the single-carrier scheme, the OFDM technique allows optimal settings for high data rate transmission over a frequency selective channel (from the Shannon’s capacity point of view). We can, by this way, ensure reliable communication and efficient energy use. When we use OFDM, the sub-carriers use different channels with different attenuations as well. The equal power allocation on each sub-carrier does not ensure an optimal capacity in a peer to peer link. Dynamic power allocation (i.e., assign different amount of power to subcarriers according to the channel) gives better results, assuming that the channel state information is available at the transmitter. Nevertheless, the transmitter does not know the channels to all users when broadcast transmission are used, and the best strategy is to transmit with the same power on all subcarriers. This thesis aims to explore the intermediate situations, and propose appropriate power allocation tools. This intermediate situation is called "multicast": the transmitter, which knows the channel parameters, sends signals to a finite number of users, and it can adapt the transmission using this knowledge. It is an intermediate position between the "peer to peer" and the "broadcast. The goal of this work is to evaluate the gain brought by the knowledge of the channel state information in multicast situation beside the broadcast situation. Obviously, when the number of receivers is very large, the gain will not be appreciable because the signal found on its path a very large number of channels, and a uniform power allocation is near optimal. When the number of users is very low, we will be close to the peer to peer transmission and gains should be more appreciable. We propose some tools to quantify these improvements in the case where the systems have one antenna at the transmitter and the receiver, this case named SISO (Single Input Single Output). We also propose those tools on systems with multiple antennas, called MIMO (Multiple Input Multiple Output). The steps required to do this work are: 1) Assuming that the channel state information of the users are known at the base station, we implement tools, using information theory, to perform power allocation and evaluate the capacities of the systems under study. 2) For multi-user SISO-OFDM scheme, we propose a power allocation algorithm on each subcarrier on multicast situation. 3) For multi-user MIMO-OFDM, we propose an algorithm that exploits the characteristics of the "zero forcing" precoding. The objective is to share the available power among all subcarriers and all antennas. 4) Finally, in a last step we focus on an efficient design of the broadcast situation. We use tools from stochastic geometry to determine which area can be covered, with the aim that a percentage of users can receive a predetermined amount of information. This determines the coverage area without implementing long period simulations. The combination of these tools allows an effective choice between the situations that fall under the "broadcast", "multicast" and "peer to peer" transmissions.

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / Ericsson Brasil / Uma nova geraÃÃo de sistemas de comunicaÃÃes sem fio, 5a GeraÃÃo (5G), à prevista para 2020. Para a 5G, à esperado o surgimento de diversos serviÃos baseados em comunicaÃÃes mÃquina à mÃquina em diferentes Ãreas, como assistÃncia mÃdica, seguranÃa e redes de mediÃÃo inteligente. Cada um com diferentes requerimentos de taxa de transmissÃo, latÃncia, capacidade de processamento, eficiÃncia energÃtica, etc. Independente do serviÃo, os clientes precisam ficar satisfeitos. Isto està impondo uma mudanÃa de paradigmas em direÃÃo à priorizaÃÃo do usuÃrio como fator mais importante no gerenciamento de redes sem fio. Com esta mudanÃa, criou-se o conceito de qualidade de experiÃncia (do inglÃs, Quality of Experience (QoE)), que descreve de forma subjetiva como o serviÃo à percebido pelo usuÃrio. A QoE normalmente à avaliada por uma nota entre 1 e 5, chamada nota mÃdia de opiniÃo (do inglÃs, Mean Opinion Score (MOS)). Neste contexto, conceitos de QoE podem ser considerados com diferentes objetivos, como: aumentar a vida Ãtil de baterias, melhorar a seleÃÃo para acesso à rede e aprimorar a alocaÃÃo dos recursos de rÃdio (do inglÃs, Radio Resource Allocation (RRA)). Com relaÃÃo à RRA, nesta dissertaÃÃo consideram-se requerimentos de QoE na gestÃo dos recursos disponÃveis em um sistema de comunicaÃÃes sem fio, como espectro de frequÃncia e potÃncia de transmissÃo. Mais especificamente, estuda-se um problema de assinalamento de recursos de rÃdio e de alocaÃÃo de potÃncia que objetiva maximizar a mÃnima MOS do sistema sujeito a satisfazer um nÃmero mÃnimo de usuÃrios prÃ-estabelecido. Inicialmente, formula-se um novo problema de otimizaÃÃo considerando restriÃÃes quanto à potÃncia de transmissÃo e quanto à fraÃÃo de usuÃrios que deve ser satisfeita, o que à um importante tÃpico do ponto de vista das operadoras. Este à um problema nÃo linear e de difÃcil soluÃÃo. Ele à entÃo reformulado como um problema linear inteiro e misto, que pode ser resolvido de forma Ãtima usando algoritmos conhecidos de otimizaÃÃo. Devido à complexidade da soluÃÃo Ãtima obtida, propÃe-se uma heurÃstica chamada em inglÃs de Power and Resource Allocation Based on Quality of Experience (PRABE). O mÃtodo proposto à avaliado por meio de simulaÃÃes e os resultados obtidos mostram que sua performance à superior à de outros existentes, sendo prÃxima à da Ãtima. / A new generation of wireless networks, the 5th Generation (5G), is predicted for beyond 2020. For the 5G, it is foreseen an emerging huge number of services based on Machine-Type Communications (MTCs) in different fields, such as, health care, smart metering and security. Each one of them requiring different throughput rates, latency, processing capacity, energy efficiency, etc. Independently of the service type, the customers still need to get satisfied, which is imposing a shift of paradigm towards incorporating the user as the most important factor in wireless network management. This shift of paradigm drove the creation of the Quality of Experience (QoE) concept, which describes the service quality subjectively perceived by the users. QoE is generally evaluated by a Mean Opinion Score (MOS) ranging from 1 to 5. In this context, QoE concepts can be considered with different objectives, such as, increasing battery life, optimizing handover decision, enhancing access network selection and improving Radio Resource Allocation (RRA). Regarding the RRA, in this masterâs thesis we consider QoE requirements when managing the limited available resources of a communication system, such as frequency spectrum and transmit power. More specifically, we study a radio resource assignment and power allocation problem that aims at maximizing the minimum MOS of the users in a system subject to attaining a minimum number of satisfied users. Initially, we formulate a new optimization problem taking into account constraints on the total transmit power and on the fraction of users that must be satisfied, which is an important topic from an operatorâs point of view. The referred problem is non-linear and hard to solve. However, we get to transform it into a simpler form, a Mixed Integer Linear Problem (MILP), that can be optimally solved using standard numerical optimization methods. Due to the complexity of obtaining the optimal solution, we propose a heuristic solution to this problem, called Power and Resource Allocation Based on Quality of Experience (PRABE). We evaluate the proposed method by means of simulations and the obtained results show that it outperforms some existing algorithms, as well as it performs close to the optimal solution.

We study energy-efficient power allocation among relays for lifetime maximization in a dual-hop relay network operated by amplify-and-forward relays with battery limitations. Power allocation algorithms are proposed for three different scenarios. First, we study the relay cooperation case where all the relays jointly support transmissions for a targeted data rate. By exploring the correlation of time-varying relay channels, we develop a prediction-based relay cooperation method for optimal power allocation strategy to improve the relay network lifetime over existing methods that do not predict the future channel state, or assume the current channel state remains static in the future. Next, we consider energy-efficient relay selection for the single source-destination case. Assuming finite transmission power levels, we propose a stochastic shortest path approach which gives the optimal relay selection decision to maximize the network lifetime. Due to the high computational complexity, a suboptimal prediction-based relay selection algorithm, directly coming from previous problem, is created. Finally, we extend our study to multiple source-destination case, where relay selection needs to be determined for each source-destination pair simultaneously. The network lifetime in the presence of multiple source-destination pairs is defined as the longest time when all source-destination pairs can maintain the target transmission rate. We design relay-to-destination mapping algorithms to prolong the network lifeii time. They all aim at maximizing the perceived network lifetime at the current time slot. The optimal max-min approach and suboptimal user-priority based approach are proposed with different levels of computational complexity. / UOIT

There has been phenomenal interest in applying space-time coding techniques in wireless communications in the last two decades. In general, the benefit of applying space-time codes in multiple-input, multiple-output (MIMO) wireless channels is an increase in transmission reliability or system throughput (capacity). However, such a benefit cannot be obtained in some wireless systems where size or other constraints preclude the use of multiple antennas. As such, wireless relay communications has recently been proposed as a means to provide spatial diversity in the face of this limitation. In this approach, some users or relay nodes assist the transmission of other users information. This dissertation contributes to the advancement of wireless relay communications by investigating the performance of various relaying signal processing methods under different practical fading environments. In particular, it examines two main relaying methods, namely decode-and-forward (DF) and amplify-and-forward (AF).<p> For DF, the focus is on the diversity analysis of relaying systems under various practical protocols when detection error at relays is taken into account. In order to effectively mitigate the phenomenon of error propagation, the smart relaying technique proposed by Wang et al. in [R1] is adopted. First, diversity analysis of a single-relay system under the scenario that only the relay is allowed to transmit in the second time slot (called Protocol II) is carried out. For Nakagami and Hoyt generalized fading channels, analytical and numerical results are provided to demonstrate that the system always obtains the maximal diversity when binary phase shift keying (BPSK) modulation is used. Second, a novel and low-complexity relaying system is proposed when smart relaying and equal gain combing (EGC) techniques are combined. In the proposed system, the destination requires only the phases of the channel state information in order to detect the transmitted signals. For the single-relay system with M-ary PSK modulation, it is shown that the system can achieve the maximal diversity under Nakagami and Hoyt fading channels. For the K-relay system, simulation results suggest that the maximal diversity can also be achieved. Finally, the diversity analysis for a smart relaying system under the scenario when both the source and relay are permitted to transmit in the second time slot (referred to as Protocol I) is presented. It is shown that Protocol I can achieve the same diversity order as Protocol II for the case of 1 relay. In addition, the diversity is very robust to the quality of the feedback channel as well as the accuracy of the quantization of the power scaling implemented at the relay.<p> For AF, the dissertation considers a fixed-gain multiple-relay system with maximal ratio combining (MRC) detection at the destination under Nakagami fading channels. Different from the smart relaying for DF, all the channel state information is assumed to be available at the destination in order to perform MRC for any number of antennas. Upperbound and lowerbound on the system performance are then derived. Based on the bounds, it is shown that the system can achieve the maximal diversity. Furthermore, the tightness of the upperbound is demonstrated via simulation results. With only the statistics of all the channels available at the destination, a novel power allocation (PA) is then proposed. The proposed PA shows significant performance gain over the conventional equal PA.

There has been phenomenal interest in applying space-time coding techniques in wireless communications in the last two decades. In general, the benefit of applying space-time codes in multiple-input, multiple-output (MIMO) wireless channels is an increase in transmission reliability or system throughput (capacity). However, such a benefit cannot be obtained in some wireless systems where size or other constraints preclude the use of multiple antennas. As such, wireless relay communications has recently been proposed as a means to provide spatial diversity in the face of this limitation. In this approach, some users or relay nodes assist the transmission of other users information. This dissertation contributes to the advancement of wireless relay communications by investigating the performance of various relaying signal processing methods under different practical fading environments. In particular, it examines two main relaying methods, namely decode-and-forward (DF) and amplify-and-forward (AF).<p> For DF, the focus is on the diversity analysis of relaying systems under various practical protocols when detection error at relays is taken into account. In order to effectively mitigate the phenomenon of error propagation, the smart relaying technique proposed by Wang et al. in [R1] is adopted. First, diversity analysis of a single-relay system under the scenario that only the relay is allowed to transmit in the second time slot (called Protocol II) is carried out. For Nakagami and Hoyt generalized fading channels, analytical and numerical results are provided to demonstrate that the system always obtains the maximal diversity when binary phase shift keying (BPSK) modulation is used. Second, a novel and low-complexity relaying system is proposed when smart relaying and equal gain combing (EGC) techniques are combined. In the proposed system, the destination requires only the phases of the channel state information in order to detect the transmitted signals. For the single-relay system with M-ary PSK modulation, it is shown that the system can achieve the maximal diversity under Nakagami and Hoyt fading channels. For the K-relay system, simulation results suggest that the maximal diversity can also be achieved. Finally, the diversity analysis for a smart relaying system under the scenario when both the source and relay are permitted to transmit in the second time slot (referred to as Protocol I) is presented. It is shown that Protocol I can achieve the same diversity order as Protocol II for the case of 1 relay. In addition, the diversity is very robust to the quality of the feedback channel as well as the accuracy of the quantization of the power scaling implemented at the relay.<p> For AF, the dissertation considers a fixed-gain multiple-relay system with maximal ratio combining (MRC) detection at the destination under Nakagami fading channels. Different from the smart relaying for DF, all the channel state information is assumed to be available at the destination in order to perform MRC for any number of antennas. Upperbound and lowerbound on the system performance are then derived. Based on the bounds, it is shown that the system can achieve the maximal diversity. Furthermore, the tightness of the upperbound is demonstrated via simulation results. With only the statistics of all the channels available at the destination, a novel power allocation (PA) is then proposed. The proposed PA shows significant performance gain over the conventional equal PA.