Wireless systems with multiple antennas at both the transmitter and receiver (MIMO systems) have been the focus of research in the recent past due to their ability to provide higher data rates and better reliability than their single antenna counterparts. Designing a communication system for MIMO frequency selective channels provides many signal processing challenges. Popular methods like MIMOOFDM and space-time precoding linearly process blocks of data at both the transmitter and the receiver. Independence between the blocks is ensured by introducing sufficient redundancy between successive blocks. This approach has many pitfalls, including the limit on achievable data rate due to redundancy requirements and the need for additional coding/processing. In this thesis, we provide a filterbank precoding framework (FBP) for communication over MIMO frequency selective channels. By viewing the channel as a polynomial matrix, we derive the minimum redundancy required for achieving FIR equalization of the precoded channel. It is shown that, for most practical channels, a nominal redundancy is enough. The results are general, and hold for channels of any dimension and order. We derive the zero-forcing and MMSE equalizers for the precoded channel. The role of equalizer delay in system performance is analyzed. We extend the minimum redundancy result to the case of space-time filterbank precoding (STFP). Introducing the time dimension allows the channel to be represented by a block pseudocirculant matrix. By using the Smith form of block pseudocirculant matrices, we show that very high data rates can be achieved with STFP. When channel information is available at the transmitter, we derive an iterative algorithm for obtaining the MMSE optimal precoder-equalizer pair. We then provide a comparison of FBP with the block processing methods. It is shown that FBP provides better BER performance than the block processing methods at a lower computational cost. The reasons for the better performance of FBP are discussed.

[pt] Sistemas de múltiplas antenas livres de células surgiram recentemente como uma combinação de MIMO massivo, sistemas de antenas distribuídas (DAS) e network MIMO. Esta dissertação explora o downlink deste cenário com pontos de acesso (PAs) de uma ou múltiplas antenas e considerando conhecimento perfeito e imperfeito do canal. São desenvolvidos esquemas que combinam pré-codificação, alocação de potência e seleção de PAs (SPA). Para começar, duas estratégias de SPA foram investigadas, uma baseada em busca exaustiva (BE-SPA) e a outra em coeficientes de desvanecimento de larga escala (LE-SPA), com o intuito de reduzir a complexidade das redes livres de células. Subsequentemente, apresentamos duas técnicas iterativas de pré-codificação, todas seguindo o critério Minimum Mean-Square Error (MMSE), combinadas à restrição de potência total. A primeira nós chamamos de MMSE, com restrição de potência total. Nós também incorporamos robustez ao método desenvolvido chamado RMMSE, um pré-codificador robusto com restrição de potência total. Como terceiro elemento da configuração proposta, esquemas de alocação de potência foram desenvolvidos, com abordagens ótimas, adaptativas e uniformes. Um algoritmo de alocação de potência ótima (APO) é apresentado, baseado na maximização da mínima Signal-to-Interference-plus-Noise Ratio (SINR). A solução adaptativa (APA) é caracterizada pelo gradiente estocástico (GE) do mean-square error (MSE) e a alternativa uniforme (UPA) propõe a equalização de todos os coeficientes de potência. Todas as configurações devem respeitar a restrição de potência por antena, imposta pelo sistema. Uma análise de soma das taxas é feita, para todas as técnicas estudadas e o custo computacional de cada uma delas é calculado. Resultados numéricos provam que as técnicas propostas têm performance superior à pré-codificadores Conjugate Beamforming (CB) e Zero-Forcing (ZF), ambos com alocação de potência uniforme e ótima, na forma de taxa de erro de bit (BER), soma das taxas e mínima SINR. Além disso, os resultados atestam que o desempenho pode ser mantido e até melhorado com a aplicação de SPA. / [en] Cell-Free Massive multiple-input multiple-output (MIMO) systems have emerged in recent years as a combination of massive MIMO, distributed antenna systems (DAS) and network MIMO. This thesis explores the downlink channel of such scenario with single and multiple-antenna access points (APs) and takes into account both perfect and imperfect channel state information (CSI). We propose transmit processing schemes that combine precoding, power allocation and AP selection (APS). To begin with, two APS strategies have been investigated, one based on exhaustive search (ES-APS) and the other on the large-scale fading coefficients (LSAPS), in order to reduce the complexity of cell-free networks. Subsequently, we present two iterative precoding techniques following the minimum meansquare error (MMSE) criterion with total power constraint. The first we call MMSE, with total power constraint. We also incorporate robustness in the developed method, called RMMSE, a robust precoder with total power constraint. As the third element of the proposed schemes, power allocation techniques are developed, with optimal, adaptive and uniform approaches. An optimal power allocation (OPA) algorithm is presented based on the maximization of the minimum signal-to-interference-plus-noise ratio (SINR). The adaptive solution (APA) is characterized by the stochastic gradient of the mean-square error (MSE) and the uniform alternative (UPA) proposes to equalize all power coefficients. All configurations must fulfil an antenna power constraint, imposed by the system. A sum-rate analysis is carried out for all studied techniques and the computational cost of each one is calculated. Numerical results prove that the proposed techniques outperform existing conjugate beamforming (CB) and zero-forcing (ZF) precoders, both with uniform and optimal power allocation, in terms of bit error rate (BER), sum-rate and minimum SINR. Furthermore, we also attest that performance can be maintained or even improved in the presence of APS.