Cooperative and cognitive radio systems have been proposed as a solution to improve the quality-of-service (QoS) and spectrum efficiency of existing communication systems. The objective of this dissertation is to propose and analyze schemes for cooperative and cognitive radio systems considering real world scenarios and to make these technologies implementable. In most of the research on cooperative relaying, it has been assumed that the communicating nodes have perfect channel state information (CSI). However, in reality, this is not the case and the nodes may only have an estimate of the CSI or partial knowledge of the CSI. Thus, in this dissertation, depending on the amount of CSI available, novel receivers are proposed to improve the performance of amplify-and forward relaying. Specifically, new coherent receivers are derived which do not perform channel estimation at the destination by using the received pilot signals directly for decoding. The derived receivers are based on new metrics that use distribution of the channels and the noise to achieve improved symbol-error-rate (SER) performance. The SER performance of the derived receivers is further improved by utilizing the decision history in the receivers. In cases where receivers with low complexity are desired, novel non-coherent receiver which detects the signal without knowledge of CSI is proposed. In addition, new receivers are proposed for the situation when only partial CSI is available at the destination i.e. channel knowledge of either the source-relay link or the relay-destination link but not both, is available. These receivers are termed as `half-coherent receivers' since they have channel-state-information of only one of the two links in the system. In practical systems, the CSI at the communicating terminals becomes outdated due to the time varying nature of the channel and results in system performance degradation. In this dissertation, the impact of using outdated CSI for relay selection on the performance of a network where two sources communicate with each other via fixed-gain amplify-and-forward relays is studied and for a Rayleigh faded channel, closed-form expressions for the outage probability (OP), moment generating function (MGF) and SER are derived. Relay location is also taken into consideration and it is shown that the performance can be improved by placing the relay closer to the source whose channel is more outdated. Some practical issues encountered in cognitive radio systems (CRS) are also investigated. The QoS of CRS can be improved through spatial diversity which can be achieved by either using multiple antennas or exploiting the independent channels of each user in a multi-user network. In this dissertation, both approaches are examined and in multi-antenna CRS, transmit antenna selection (TAS) is proposed where as in a multi-user CRS, user selection is proposed to achieve performance gains. TAS reduces the implementation cost and complexity and thus makes CRS more feasible. Additionally, unlike previous works, in accordance with real world systems, the transmitter is assumed to have limited peak transmit power. For both these schemes, considering practical channel models, closed-form expression for the OP performance, SER performance and ergodic capacity (EC) are obtained and the performance in the asymptotic regimes is also studied. Furthermore, the OP performance is also analyzed taking into account the interference from the primary network on the cognitive network.

Em sistemas MIMO multiusuÃrio, o transmissor pode selecionar um subconjunto de antenas e/ou usuÃrios que tÃm bons canais para maximizar o rendimento do sistema usando vÃrios critÃrios de seleÃÃo. AlÃm disso, os prÃ-codificadores podem proporcionar dimensÃes livres de interferÃncia. O alinhamento de interferÃncia (IA) à baseado no conceito de prÃ-codificaÃÃo e oferece diferentes compromissos entre complexidade e desempenho. A idÃia bÃsica do Alinhamento InterferÃncia consiste em prÃ-codificar os sinais transmitidos de maneira que os mesmos sejam alinhados no receptor, em que eles constituem interferÃncia, enquanto que ao mesmo tempo os separa do sinal desejado. No entanto, a InformaÃÃo do Estado do Canal (CSI) tem sido uma preocupaÃÃo para os pesquisadores porque ela tem um impacto no desempenho de algoritmos de IA. Assim, nos propomos a analisar o desempenho da seleÃÃo de antena e diversidade multiusuÃrio em conjunto, a fim de permitir o IA oportunista usando vÃrios critÃrios com relaÃÃo à perturbaÃÃo da CSI. AnÃlises e simulaÃÃes verificam o comportamento do esquema proposto. / In multiuser MIMO systems, the transmitter can select a subset of antennas and/or users which have good channel conditions to maximize the system throughput using various selection criteria. Furthermore, precoding can provide free interference dimensions. The Interference Alignment (IA) is based on the concept of precoding and it offers different trade-offs between complexity and performance. The basic idea of Interference Alignment consists in precoding the transmitted signals such that they are aligned at the receiver where they constitute interference, while at the same time disjointed from the desired signal. However, the Channel State Information (CSI) has been a concern because it impacts the performance of IA algorithms. Hence, we propose to analyze the performance of antenna selection and multiuser diversity together in order to allow opportunistic IA using several criteria over the disturbance of CSI. Analyses and simulations verify the behavior of the proposed scheme.

This dissertation studies a number of important issues that arise in multiple-input multiple-out wireless systems. First, wireless systems equipped with multiple-transmit multiple-receive antennas are considered where an energy-based antenna selection is performed at the receiver. Three different situations are considered: (i) selection over iid MIMO fading channel, (ii) selection over spatially correlated fading channel, and (iii) selection for space-time coded OFDM systems. In all cases, explicit upper bounds are derived and it is shown that using the proposed antenna selection, one can achieve the same diversity order as that attained by full-complexity MIMO systems. Next, joint source-channel coding problem for MIMO antenna systems is studied and a turbo-coded multiple description code for multiple antenna transmission is developed. Simulations indicate that by the proposed iterative joint source-channel decoding that exchanges the extrinsic information between the source code and the channel code, one can achieve better reconstruction quality than that can be achieved by the single-description codes at the same rate. The rest of the dissertation deals with wireless networks. Two problems are studied: channel coding for cooperative diversity in wireless networks, and distributed detection in wireless sensor networks. First, a turbo-code based channel code for three-terminal full-duplex wireless relay channels is proposed where both the source and the relay nodes employ turbo codes. An iterative turbo decoding algorithm exploiting the information arriving from both the source and relay nodes is proposed. Simulation results show that the proposed scheme can perform very close to the capacity of a wireless relay channel. Next the parallel and serial binary distributed detection problem in wireless sensor networks is investigated. Detection strategies based on single-bit and multiple-bit decisions are considered. The expressions for the detection and false alarm rates are derived and used for designing the optimal detection rules at all sensor nodes. Also, an analog approach to the distributed detection in wireless sensor networks is proposed where each sensor nodes simply amplifies-and-forwards its sufficient statistics to the fusion center. This method requires very simple processing at the local sensor. Numerical examples indicate that the analog approach is superior to the digital approach in many cases.

This thesis deals with dual-polarized multiple input multiple output (MIMO) channels, an important issue for the practical deployment of multiple antenna systems. The MIMO architecture has the potential to dramatically improve the performance of wireless systems. Much of the focus of research has been on uni-polarized spatial MIMO configurations, the performance of which, is a strong function of the inter-element spacing. Thus the current trend of miniaturization, seems to be at odds with the implementation of spatial configurations in portable handheld devices. In this regard, dual-polarized antennas present an attractive alternative for realizing higher order MIMO architectures in compact devices. Unlike spatial channels, in the presence of polarization diversity, the subchannels of the MIMO channel matrix are not identically distributed. They differ in terms of average received power, envelope distributions, and correlation properties. In this thesis, we report on an indoor channel measurement campaign conducted at 2.4 GHz, to measure the copolarized and cross-polarized subchannels, under line-of-sight (LOS) and non-line-of-sight (NLOS) channel conditions. The measured data is then analyzed, to draw a fair comparison between spatial and dual-polarized MIMO systems, in terms of channel characteristics and achievable capacity. The main drawback of the MIMO architecture is that the gain in capacity comes at a cost of increased hardware complexity. Antenna selection is a technique using which we can alleviate this cost. We emphasize that this strategy is all the more relevant for compact devices, which are often constrained by complexity, power and cost. Using theoretical analysis and measurement results, this thesis investigates the performance of antenna selection in dual-polarized MIMO channels. Our results indicate that, antenna selection when combined with dual-polarized antennas, is an effective, low-complexity solution to the problem of realizing higher order MIMO architectures in compact devices.

Increasing energy consumption is a result of the rapid growth in cellular communication technologies and a massive increase in the number of mobile terminals (MTs) and communication sites. In cellular communication networks, energy efficiency (EE) and spectral efficiency (SE) are two of the most important criteria employed to evaluate the performance of networks. A compromise between these two conflicting criteria is therefore required, in order to achieve the best cellular network performance. Fractional frequency reuse (FFR), classed as either strict FFR or soft frequency reuse (SFR), is an intercell interference coordination (ICIC) technique applied to manage interference when more spectrum is used, and to enhance the EE. A conventional cellular model's downlink is designed as a reference in the presence of inter-cell interference (ICI) and a general fading environment. Energy-efficient cellular models,such as cell zooming, cooperative BSs and relaying models are designed, analysed and compared with the reference model, in order to reduce network energy consumption without degrading the SE. New mathematical models are derived herein to design a distributed antenna system (DAS), in order to enhance the system's EE and SE. DAS is designed in the presence of ICI and composite fading and shadowing with FFR. A coordinate multi-point (CoMP) technique is applied, using maximum ratio transmission (MRT) to serve the mobile terminal (MT), with all distributed antenna elements (DAEs), transmit antenna selection (TAS) being applied to select the best DAE and general selection combining (GSC) being applied to select more than one DAE. Furthermore, a Cloud radio access network (C-RAN) is designed and analysed with two different schemes, using the high-power node (HPN) and a remote radio head (RRH), in order to improve the EE and SE of the system. Finally, a trade-off between the two conflicting criteria, EE and SE, is handled carefully in this thesis, in order to ensure a green cellular communication network.

[pt] Esta dissertação enfoca a combinação de duas conhecidas e eficazes tecnologias usadas em muitas redes de comunicação atuais, as técnicas de transmissão Orthogonal Frequency Division Multiplexing (OFDM) e Multiple-Input Multiple-Output (MIMO). Sistemas MIMO-OFDM unem as vantagens conhecidas da comunicação MIMO, como altas taxas de dados e ampliação da confiabilidade do link, com as características marcantes da transmissão OFDM, como comunicação livre de interferência entre símbolos e a equalização simples no domínio da frequência. Este trabalho apresenta em detalhes a modelagem de sinais do sistema MIMO-OFDM e o processamento adequado no receptor para realizar detecções desacopladas dos sub-símbolos OFDM. Além disso, estratégias de seleção de antenas são propostas para aumentar o desempenho do sistema, explorando cenários em que o transmissor ou receptor está equipado com mais antenas do que o número de cadeias de radiofrequência (RF). Esses procedimentos são baseados em métricas específicas propostas para cada cenário. A avaliação de desempenho inclui sistemas equipados com técnicas de equalização linear e sistemas com pré-codificadores, como Zero-Forcing (ZF) e Minimum Mean Square Error (MMSE). Os resultados de simulação evidenciam que as estratégias de seleção da antena resultam em uma melhoria significativa no desempenho do sistema. / [en] This thesis focuses on the combination of two well-known effective technologies used in many of today s communication networks, Orthogonal Frequency Division Multiplexing (OFDM) and Multiple-Input Multiple- Output (MIMO). It unites the well-known advantages of MIMO communication, such as high data rates and improved link reliability to the characteristics of OFDM, known as intersymbol-interference-free communication and simple frequency-domain equalization. This work presents in detail the signal modelling of MIMO-OFDM system and the adequate processing at the receiver to perform decoupled detections per OFDM subsymbol. In addition, antenna selection strategies are proposed to increase system performance by exploiting some scenarios when the transmitter or receiver is equipped with more antennas than the number of radiofrequency (RF) chains. These procedures are based on the specific metric for the current scenario. The performance of the system is evaluated employing linear equalization or precoding techniques, such as Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE). Simulation results evidence that antenna selection strategies result in significant system performance improvement.

[pt] Modulação Espacial com Pré-codificação Generalizada (Generalized Precoding Aided Spatial Modulation, GPSM) é uma estratégia de comunicação em sistemas MIMO em que o transmissor codifica a informação em duas entidades: a transmissão paralela de símbolos pertencentes à constelação de uma modulação digital, e os índices das posições do vetor de informação que transportam estes símbolos, denominada information bearing positions (IBP), enquanto as demais posições transportam zero. Além disto, o transmissor, previamente à transmissão dos dados pré-codifica o vetor de informação, possibilitando a redução da complexidade do nó receptor. Entre as vantagens desta estratégia destaca-se a concentração da energia transmitida apenas nas posições do vetor de informação que efetivamente contém símbolos, favorecendo o desempenho do sistema. Esta tese considera um sistema MIMO multiusuário (MU-MIMO) que emprega GPSM no enlace direto. O modelo de sinais desenvolvido para descrever este sistema evidencia a influência das matrizes que codificam as IBP no desempenho do sistema. Com base neste modelo, o sistema GPSM MU-MIMO é apresentado para três pré-codificadores lineares: Zero-Forcing, Block Diagonalization e Block Diagonalization de Duas Fases. Para cada um destes pré-codificadores são propostas estratégias de seleção das matrizes de codificação IBP, de acordo com a matriz que descreve o canal MU-MIMO corrente, a serem empregadas pelo transmissor visando melhorar o desempenho de detecção do sistema. As curvas de desempenho de detecção são comparadas a limitantes semianalíticos desenvolvidos. Por fim, considera-se o cenário em que existem mais antenas disponíveis na estação rádio-base e/ou nos usuários do que o número de cadeias de radiofrequência que os equipam. Esta tese apresenta estratégias ótimas e de complexidade reduzida de se explorar o uso das antenas mais favoráveis à transmissão e/ou recepção, em adição à escolha das matrizes de codificação IBP, com o objetivo de prover melhorias ao desempenho do sistema. / [en] Generalized Pre-coding Aided Spatial Modulation (GPSM) is a MIMO system communication strategy in which the transmitter encodes the information in two entities: the parallel transmission of symbols belonging to a digital modulation constellation, and the choice of the indices of the information vector elements that carries the informaiton symbols, denoted information bearing positions (IBP), while the remaing positions are set to zero. Besides, the transmitter precodes, prior to transmission, the information vector, which lets the receiver node benefit from complexity reduction. Among the advantages of this strategies, the concentration of the transmitted energy only on the information vector positions that transports modulated symbols, resulting in system performance improvement. This thesis considers a multiuser MIMO (MU-MIMO) that employs GPSM in the donwlink transmission. The presented signal model to describe this system evidences the influence of the IBP coding matrices on the system performance. Based on this model, GPSM MU-MIMO system is presented considering three linear precoders: Zero-Forcing, Block Diagonalization and Double-Stage Block Diagonalization. For each precoder, strategies to select the IBP encoding matrix, acording to the matrix that describes the current MU-MIMO channel, is proposed. These matrices are to be employed by the user, aiming at system detection performance improvement. Detection performance curves are compared to semianalytic lower bounds. Finally, a scenario in which that are a number of available antennas at the BS and/or at the users that exceed the number of radiofrequency chains. this thesis porposes optimal and reduced complexity strategies that exploit the use of the most favorable antennas for transmission and/or reception, in addition to the choice of the IBP enconding matrices, aiming at system performance improvement.

Motivated by the increasing demand for higher data rates, coverage, and spectral efficiency, current and next generation wireless systems adapt transmission parameters and even who is being transmitted to, based on the instantaneous channel states. For example, frequency-domain scheduling(FDS) is an instance of adaptation in orthogonal frequency division multiple access(OFDMA) systems in which the base station opportunistically assigns different subcarriers to their most appropriate user. Likewise ,transmit antenna selection(AS) is another form of adaptation in which the transmitter adapts which subset of antennas it transmits with. Cognitive radio(CR), which is a next generation technology, itself is a form of adaptation in which secondary users(SUs) adapt their transmissions to avoid interfering with the licensed primary users(PUs), who own the spectrum. However, adaptation requires channel state information(CSI), which might not be available apriori at the node or nodes that are adapting. Further, the CSI might not be perfect due to noise or feedback delays. This can result in suboptimal adaptation in OFDMA systems or excessive interference at the PUs due to transmissions by the SUs in CR. In this thesis, we focus on adaptation techniques in current and next generation wireless systems and evaluate the impact of CSI –both perfect and imperfect –on it. We first develop a novel model and analysis for characterizing the performance of AS in frequency-selective OFDMA systems. Our model is unique and comprehensive in that it incorporates key LTE features such as imperfect channel estimation based on dense, narrow band demodulation reference signal and coarse, broad band sounding reference signal. It incorporates the frequency-domain scheduler, the hardware constraint that the same antenna must be used to transmit over all the subcarriers that are allocated to a user, and the scheduling constraint that the allocated subcarriers must all be contiguous. Our results show the effectiveness of combined AS and FDS in frequency-selective OFDMA systems even at lower sounding reference signal powers. We then investigate power adaptation in underlay CR, in which the SU can transmit even when the primary is on but under stringent interference constraints. The nature of the interference constraint fundamentally decides how the SU adapts its transmit power. To this end, assuming perfect CSI, we propose optimal transmit power adaptation policies that minimize the symbol error probability of an SU when they are subject to different interference and transmit power constraints. We then study the robustness of these optimal policies to imperfections in CSI. An interesting observation that comes out of our study is that imperfect CSI can not only increase the interference at the PU but can also decrease it, and this depends on the choice of the system parameters, interference, and transmit power constraints. The regimes in which these occur are characterized.

Most of the modern wireless communication systems as WiMAX, DVB-NGH, WiFi, HSPA+ and 4G have adopted the use of multiple antennas at the transmitter and the receiver, called multiple-input multiple-output (MIMO). Space time coding for MIMO systems is a promising technology to increase the data rate and enhance the reliability of wireless communications. Space-time block codes (STBCs) are commonly designed according to the rank-determinant criteria suitable at high signal to noise ratios (SNRs). In contrast, wireless communication standards employ MIMO technology with capacity-approaching forward-error correcting (FEC) codes like turbo codes and low-density parity-check (LDPC) codes, ensuring low error rates even at low SNRs. In this thesis, we investigate the design of STBCs for MIMO systems with capacity-approaching FEC codes. We start by proposing a non-asymptotic STBC design criterion based on the bitwise mutual information (BMI) maximization between transmitted and soft estimated bits at a specific target SNR. According to the BMI criterion, we optimize several conventional STBCs. Their design parameters are shown to be SNR-dependent leading to the proposal of adaptive STBCs. Proposed adaptive STBCs offer identical or better performance than standard WiMAX profiles for all coding rates, without increasing the detection complexity. Among them, the proposed adaptive trace-orthonormal STBC can pass continuously from spatial multiplexing, suitable at low SNRs and therefore at low coding rates, to the Golden code, optimal at high SNRs. Uncorrelated, correlated channels and transmit antenna selection are considered. We design adaptive STBCs for these cases offering identical or better performance than conventional non-adaptive STBCs. In addition, conventional STBCs are designed in a way achieving the asymptotic DMT frontier. Recently, the finite-SNR DMT has been proposed to characterize the DMT at finite SNRs. Our last contribution consists of the derivation of the exact finite-SNR DMT for MIMO channels with dual antennas at the transmitter and/or the receiver. Both uncorrelated and correlated Rayleigh fading channels are considered. It is shown that at realistic SNRs, achievable diversity gains are significantly lower than asymptotic values. This finite-SNR could provide new insights on the design of STBCs at operational SNRs.

[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.