[pt] Esta dissertação enfoca o enlace direto de sistemas MIMO multiusuário com pré-codificação onde a estação base e os terminais dos usuários possuem múltiplas antenas mas transmitem e recebem, respectivamente, símbolos de informação através de subconjuntos selecionados de seus conjuntos de antenas. O trabalho considera sistemas que utilizam técnicas de précodificação linear como Zero Forcing (ZF) e Minimum Mean Square Error (MMSE). Expressões gerais que descrevem os sistemas e relacionam a energia gasta na transmissão com a energia disponível para a detecção em cada usuário são apresentadas. Com base nestas relações, um procedimento para seleção de antenas na transmissão é proposto visando a minimização da probabilidade de erro. Um algoritmo de busca não exaustiva denominado ITES (Iterative Search) foi desenvolvido e testado e mostrou-se capaz de, com apenas uma pequena fração do esforço computacional, fornecer um desempenho próximo ao da seleção ótima, que demanda uma busca exaustiva. A seleção de antenas na recepção é também efetuada usando um critério de otimização semelhante. O caso geral da seleção conjunta de antenas na transmissão e na recepção contempla a combinação de ambas estratégias, resultando na redução da complexidade tanto na estação base, quanto nos terminais dos usuários. Os resultados de desempenho em termos da taxa de erro de bit, obtidos por meio de simulações e abordagem semianalítica, são apresentados para diferentes cenários. / [en] This thesis focuses on the downlink of a multiuser multiple-input multiple-output (MU-MIMO) systems where the Base Station (BS) and the users stations (UEs) transmit and receive information symbols, respectively, by selected subset of their antennas. The performance of the system is evaluated employing linear precoding techniques as Zero Forcing (ZF) and Minimum Mean Square Error (MMSE). A general model to describe the system and expressions that relate the energy spent in transmission with the energy available for detection at each user are presented. A transmit antenna selection procedure is proposed aiming at the minimization of the detection error probability. A suboptimal search algorithm, called ITES (Iterative Search), able to deliver a performance close to the one resulting from the optimal exhaustive search selection is also proposed. The receive antenna selection is also performed using a similar optimization criterion. Joint antennas selection at the transmitter and receiver contemplates the efficient combination of both strategies, leading to a complexity reduction in BS and UEs. BER performance results, obtained via simulation and semi-analytical approaches, are presented for different scenarios.

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Les systèmes de communication MIMO à utilisateurs multiples (MU-MIMO) connus dans la théorie de l'information comme système de canal de diffusion de l'anglais Broadcast Channel (BC) est devenu ces dernières années l'un des sujets les plus étudiés dans le domaine des communications sans fil. Cet intérêt important vient de l'énorme potentiel qu'il offre dans l'amélioration aussi bien de la fiabilité que la stabilité des systèmes. Par ailleurs, ce type de système commence à apparaître dans les systèmes de nouvelle génération tels que LTE, WiFi. . . Cependant, du fait, de la corrélation non linéaire entre les directions et à cause du couplage avec l'attribution de puissance, le débit total qui représente notre fonction de coût à maximiser devient une fonction non convexe. Néanmoins, la théorie de l'information a démontré que la capacité de BC pourrait être atteinte par un codage DPC. Le problème avec ce précodage est d'une part est un précodage non linéaire et donc difficilement réalisable, et d'autre part, présente une grande complexité et consomme beaucoup de ressources. Afin de remédier à cela, des algorithmes linéaires sous-optimaux on été proposés. Elles peuvent être classées en solutions itératives et approchée (CF). Les techniques de conception de precodeurs peuvent également être différenciée en fonction du nombre de flux attribués par utilisateur. En fait, certains ne permettent qu'un seul flux par utilisateur même si le système ne soit pas entièrement chargé. On a récemment proposé des algorithmes multi-flux. Néanmoins, ils présentent quelques inconvénients : Certains doivent imposer à l'avance la distribution des flux et accentuent la sous optimalité. Mais le plus grand inconvénient reste celui des problèmes de convergence vers un maxima local ou parfois de divergence. Cette thèse s'inscrit dans ce cadre et à travers elle on essaye de proposer des solutions afin d'améliorer les algorithmes d'optimisation et de maximiser le débit total du système. Nous avons étudié et proposé des solution avec précodage itératif mais aussi en forme approchée. La thèse est essentiellement une collection de ce qui suit : * Précodage linéaire pour MU-MIMO BC avec flux unique par utilisateur. * Précodage linéaire pour MU-MIMO BC avec flux multiples et sélection d'utilisateurs.

In this thesis we investigate how to improve the performance of MU-MIMO wireless system in terms of achieving Shannon capacity limit and efficient use of precious resource of radio spectrum in wireless communication. First a new suboptimal volume-based scheduling algorithm is presented, which can be applied in MU-MIMO downlink system to transmit signals concurrently to multiple users under the assumption of perfect channel information at transmitter and receiver. The volume-based scheduling algorithm utilises Block Diagonalisation precoding and Householder reduction procedure of QR factorisation. In comparison with capacity-based suboptimal scheduling algorithm, the volume-based algorithm has much reduced computational complexity with only a fraction of sum-rate capacity penalty from the upper bound of system capacity limit. In comparison with semi-orthogonal user selection suboptimal scheduling algorithm, the volume-based scheduling algorithm can be implemented with less computational complexity. Furthermore, the sum-rate capacity achieved via volume-based scheduling algorithm is higher than that achieved by SUS scheduling algorithm in the MIMO case. Then, a two-step scheduling algorithm is proposed, which can be used in the MU-MIMO system and under the assumption that channel state information is known to the receiver, but it is not known to the transmitter and the system under the feedback resource constraint. Assume that low bits codebook and high bits codebook are stored at the transmitter and receiver. The users are selected by using the low bits codebook; subsequently the BD precoding vectors for selected users are designed by employing high bits codebook. The first step of the algorithm can alleviate the load on feedback uplink channel in the MU-MIMO wireless system while the second step can aid precoding design to improve system sum-rate capacity. Next, a MU-MIMO cognitive radio (CR) wireless system has been studied. In such system, a primary wireless network and secondary wireless network coexist and the transmitters and receivers are equipped with multiple antennas. Spectrum sensing methods by which a portion of spectrum can be utilised by a secondary user when the spectrum is detected not in use by a primary user were investigated. A Free Probability Theory (FPT) spectrum sensing method that is a blind spectrum sensing method is proposed. By utilizing the asymptotic behaviour of random matrix based on FPT, the covariance matrix of transmitted signals can be estimated through a large number of observations of the received signals. The method performs better than traditional energy spectrum sensing method. We also consider cooperative spectrum sensing by using the FPT method in MU-MIMO CR system. Cooperative spectrum sensing can improve the performance of signal detection. Furthermore, with the selective cooperative spectrum sensing approach, high probability of detection can be achieved when the system is under false alarm constraint. Finally, spectrum sensing method based on the bispectrum of high-order statistics (HOS) and receive diversity in SIMO CR system is proposed. Multiple antennas on the receiver can improve received SNR value and therefore enhance spectrum sensing performance in terms of increase of system-level probability of detection. Discussions on cooperative spectrum sensing by using the spectrum sensing method based on HOS and receive diversity are presented.

[pt] Sistemas de múltiplas antenas de larga escala são técnicas fundamentais para sistemas de comunicação sem fio do futuro, que deverão servir dezenas de usuários por estação rádio-base. Neste contexto, um problema chave é o aumento do consumo de energia à medida que o número de antenas cresce. Recentemente, CADs de baixa resolução têm atraído grande interesse de pesquisa. Em particular, CADs de 1 bit são adequados para sistemas de larga escala devido ao seu baixo custo e consumo de energia. Nesta tese, CADs de 1 bit são usados em três diferentes abordagens de projeto, que operam a taxa de Nyquist e a taxas superiores a taxa de Nyquist com estratégias de amostragem uniforme e dinâmica. Nos sistemas operando a taxa de Nyquist, algoritmos de estimação de canal que exploram o conhecimento da baixa resolução e um novo esquema de detecção e decodificação iterativas são propostos, em que códigos low-density paritycheck de bloco curto são considerados para evitar alta latência. Nos sistemas operando a taxas superiores a taxa de Nyquist com sobreamostragem uniforme, algoritmos eficientes de estimação de canal e de detecção com janela deslizante com exploração da baixa resolução são propostos. Além disso, são deduzidas expressões analíticas associadas aos limitantes de Cramér-Rao para os sistemas com sobreamostragem. Resultados numéricos ilustram o desempenho dos algoritmos de estimação de canal propostos e existentes e os limitantes teóricos deduzidos. Nos sistemas operando com sobreamostragem dinâmica, duas abordagens de projeto são desenvolvidas: uma técnica baseada na maximização da soma das taxas e uma técnica baseada na minimização do erro médio quadrático. Em seguida, três algoritmos de redução de dimensão são apresentados e investigados. Resultados de simulações mostram que os sistemas com sobreamostragem dinâmica têm melhor desempenho do que os sistemas com sobreamostragem uniforme em termos de soma das taxas alcançáveis e de taxa de erro de símbolos, enquanto o custo computacional das técnicas examinadas é comparável. / [en] Large-scale multiple-antenna systems are a key technique for future wireless communications, which will serve tens of users per base station (BS). In this scenario, one problem faced is the large energy consumption as the number of receive antennas scales up. Recently, low-resolution analogto-digital converters (ADCs) have attracted much attention. Specifically, 1-bit ADCs in the front-end are suitable for such systems due to their low cost and low energy consumption. In this thesis, 1-bit ADCs are applied in three different system designs, which operate at the Nyquist rate and faster than Nyquist rates along with uniform and dynamic strategies. In the Nyquist-sampling system, low-resolution-aware channel estimation algorithms and a novel iterative detection and decoding scheme are proposed, where short block length low-density parity-check codes are considered for avoiding high latency. In the faster than Nyquist rates with uniform oversampling system, lowresolution-aware channel estimation and sliding window based detection algorithms are proposed due to their low computational cost and high detection accuracy. Particularly, analytical expressions associated with the Bayesian Cramér-Rao bounds for the oversampled systems are presented. Numerical results are provided to illustrate the performance of the proposed channel estimation algorithms and the derived theoretical bounds. In the dynamic-oversampling system, two different system designs are devised, namely, sum rate and mean square error based. Three different dimension reduction algorithms are presented and thoroughly investigated. Simulation results show that the systems with the proposed dynamic oversampling outperform the uniformly oversampled system in terms of the computational cost, achievable sum rate and symbol error rate performance.

The research reported in this thesis is concerned with robust precoder and transceiver optimization in multiuser multi-antenna wireless communication systems in the presence of imperfect channel state information(CSI). Precoding at the transmit side, which utilizes the CSI, can improve the system performance and simplify the receiver design. Transmit precoding is essential for inter-user interference cancellation in multiuser downlink where users do not cooperate. Linear and non-linear precoding have been widely investigated as low-complexity alternatives to dirty paper coding-based transmission scheme for multiuser multiple-input multiple-output(MU-MIMO)downlink. Similarly, in relay-assisted networks, precoding at the relay nodes have been shown to improve performance. The precoder and joint precoder/receive filter (transceiver) designs usually assume perfect knowledge of the CSI. In practical systems, however, the CSI will be imperfect due to estimation errors, feedback errors and feedback delays. Such imperfections in CSI will lead to deterioration of performance of the precoders/transceivers designed assuming perfect CSI. In such situations, designs which are robust to CSI errors are crucial to realize the potential of multiuser multi-antenna systems in practice. This thesis focuses on the robust designs of precoders and transceivers for MU-MIMO downlink, and for non-regenerative relay networks in the presence of errors in the CSI. We consider a norm-bounded error(NBE) model, and a stochastic error(SE) model for the CSI errors. These models are suitable for commonly encountered errors, and they allow mathematically and computationally tractable formulations for the robust designs. We adopt a statistically robust design in the case of stochastic error, and a minimax or worst-case robust design in the case of norm-bounded error. We have considered the robust precoder and transceiver designs under different performance criteria based on transmit power and quality-of-service(QoS) constraints. The work reported in this thesis can be grouped into three parts, namely,i ) robust linear pre-coder and transceiver designs for multiuser downlink, ii)robust non-linear precoder and transceiver designs for multiuser downlink, and iii)robust precoder designs for non-regenerative relay networks. Linear precoding: In this part, first, a robust precoder for multiuser multiple-input single-output(MU-MISO)downlink that minimizes the total base station(BS)transmit power with constraints on signal-to-interference-plus-noise ratio(SINR) at the user terminals is considered. We show that this problem can be reformulated as a second order cone program(SOCP) with the same order of computational complexity as that of the non-robust precoder design. Next, a robust design of linear transceiver for MU-MIMO downlink is developed. This design is based on the minimization of sum mean square error(SMSE) with a constraint on the total BS transmit power, and assumes that the error in the CSI at the transmitter(CSIT) follows the stochastic error model. For this design, an iterative algorithm based on the associated Karush-Kuhn-Tucker(KKT) conditions is proposed. Our numerical results demonstrate the robust performance of the propose designs. Non-linear precoding: In this part, we consider robust designs of Tomlinson-Harashima precoders(THP) for MU-MISO and MU-MIMO downlinks with different performance criteria and CSI error models. For MU-MISO systems with imperfect CSIT, we investigate the problem of designing robust THPs under MSE and total BS transmit power constraints. The first design is based on the minimization of total BS transmit power under constraints on the MSE at the individual user receivers. We present an iterative procedure to solve this problem, where each iteration involves the solution of a pair of convex optimization problems. The second design is based on the minimization of a stochastic function of the SMSE under a constraint on the total BS transmit power. We solve this problem efficiently by the method of alternating optimization. For MU-MIMO downlink, we propose robust THP transceiver designs that jointly optimize the TH precoder and receiver filters. We consider these transceiver designs under stochastic and norm-bounded error models for CSIT. For the SE model, we propose a minimum SMSE transceiver design. For the NBE model, we propose three robust designs, namely, minimum SMSE design, MSE-constrained design, and MSE-balancing design. Our proposed solutions to these robust design problems are based on iteratively solving a pair of sub-problems, one of which can be solved analytically, and the other can be formulated as a convex optimization problem that can be solved efficiently. Robust precoder designs for non-regenerative relay networks: In this part, we consider robust designs for two scenarios in the case of relay-assisted networks. First, we consider a non-regenerative relay network with a source-destination node pair assisted by multiple relay nodes, where each node is equipped with a single antenna. The set of the cooperating relay nodes can be considered as a distributed antenna array. For this scenario, we present a robust distributed beam former design that minimizes the total relay transmit power with a constraint on the SNR at the destination node. We show that this robust design problem can be reformulated as a semi-definite program (SDP)that can be solved efficiently. Next, we consider a non-regenerative relay network, where a set of source-destination node pairs are assisted by a MIMO-relay node, which is equipped with multiple transmit and multiple receive antennas. For this case, we consider robust designs in the presence of stochastic and norm-bounded CSI errors. We show that these problems can be reformulated as convex optimization problems. In the case of norm-bounded error, we use an approximate expression for the MSE in order to obtain a tractable solution.