SVM-Based Channel Estimation and Data Detection for One-Bit Massive MIMO systems

The use of low-resolution Analog-to-Digital Converters (ADCs) is a practical solution for reducing cost and power consumption for massive Multiple-Input-Multiple-Output (MIMO) systems. However, the severe nonlinearity of low-resolution ADCs causes significant distortions in the received signals and makes the channel estimation and data detection tasks much more challenging. In this paper, we show how Support Vector Machine (SVM), a well-known supervised-learning technique in machine learning, can be exploited to provide efficient and robust channel estimation and data detection in massive MIMO systems with one-bit ADCs. First, the problem of channel estimation for uncorrelated channels is formulated as a conventional SVM problem. The objective function of this SVM problem is then modified for estimating spatially correlated channels. Next, a two-stage detection algorithm is proposed where SVM is further exploited in the first stage. The performance of the proposed data detection method is very close to that of Maximum-Likelihood (ML) data detection when the channel is perfectly known. We also propose an SVM-based joint Channel Estimation and Data Detection (CE-DD) method, which makes use of both the to-be-decoded data vectors and the pilot data vectors to improve the estimation and detection performance. Finally, an extension of the proposed methods to OFDM systems with frequency-selective fading channels is presented. Simulation results show that the proposed methods are efficient and robust, and also outperform existing ones

A Reduced Complexity Ungerboeck Receiver for Quantized Wideband Massive SC-MIMO

Employing low resolution analog-to-digital converters in massive multiple-input multiple-output (MIMO) has many advantages in terms of total power consumption, cost and feasibility of such systems. However, such advantages come together with significant challenges in channel estimation and data detection due to the severe quantization noise present. In this study, we propose a novel iterative receiver for quantized uplink single carrier MIMO (SC-MIMO) utilizing an efficient message passing algorithm based on the Bussgang decomposition and Ungerboeck factorization, which avoids the use of a complex whitening filter. A reduced state sequence estimator with bidirectional decision feedback is also derived, achieving remarkable complexity reduction compared to the existing receivers for quantized SC-MIMO in the literature, without any requirement on the sparsity of the transmission channel. Moreover, the linear minimum mean-square-error (LMMSE) channel estimator for SC-MIMO under frequency-selective channel, which do not require any cyclic-prefix overhead, is also derived. We observe that the proposed receiver has significant performance gains with respect to the existing receivers in the literature under imperfect channel state information.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Técnicas de equalização para MIMO massivo com amplificação não linear

The dawn of the new generation of mobile communications and the trafic explosion that derives from its implementation pose great challenge. The milimeter wave band and the use of massive number of antennas are technologies which, when combined, allow the transmission of high data rate, functioning in zones of the electromagnetic spectrum that are less explored and with capability of allocation of dozens of GHz of bandwidth. In this dissertation we consider a massive MIMO millimeter wave system employing a hybrid architecture, i.e., the number of transmit and receive antennas are lower than the number of radio frequency chains. As consequence, the precoder and equalizers should be designed in both digital and analog domains. In the literature, most of the proposed hybrid beamforming schemes were evaluated without considering the effects of nonlinear amplifications. However, these systems face non-avoidable nonlinear effects due to power amplifiers functioning in nonlinear regions. The strong nonlinear effects throughout the transmission chain will have a negative impact on the overall system performance and thus its study and the design of equalizers that take into account these effects are of paramount importance. This dissertation proposes a hybrid iterative equalizer for massive MIMO millimeter wave SC-FDMA systems. The user terminals have low complexity, just equipped with analog precoders based on average angle of departure, each with a single radio frequency chain. At the base station it is designed an hybrid analog-digital iterative equalizer with fully connected architecture in order to eliminate both the multi-user interference and the nonlinear distortion caused by signal amplification during the transmission. The equalizer is optimized by minimizing the bit error rate, which is equivalent to minimize the mean square error rate. The impact of the saturation threshold of the amplifiers in the system performance is analysed, and it is demonstrated that the iterative process can efficiently remove the multi-user interference and the distortion, improving the overall system performance.O surgimento de uma nova geração de comunicações móveis e a explosão de tráfego que advém da sua implementação apresenta grandes desafios. A banda de ondas milimétricas e o uso massivo de antenas são tecnologias que, combinadas, permitem atingir elevadas taxas de transmissão, funcionando em zonas do espectro electromagnético menos exploradas e com capacidade de alocação de dezenas de GHz para largura de banda. Nesta dissertação foi considerado um sistema de MIMO massivo de ondas milimétricas usando uma arquitectura híbrida, i.e., o número de antenas para transmissão e recepção é menor que o número de cadeias de radiofrequência. Consequentemente, o pré-codificador e equalizadores devem ser projectados nos domínios digital e analógico. Na literatura, a maioria dos esquemas híbridos de beamforming são avaliados sem ter em conta os efeitos de não linearidade da amplificação do sinal. No entanto, estes sistemas sofrem inevitavelmente de efeitos não lineares devido aos amplificadores de potência operarem em regiões não lineares. Os fortes efeitos das não-linearidades ao longo da cadeia de transmissão têm um efeito nefasto no desempenho do sistema e portanto o seu estudo e projecto de equalizadores que tenham em conta estes efeitos são de extrema importância. Esta dissertação propõe um equalizador híbrido para sistemas baseados em ondas milimétricas para MIMO massivo com modulação SC-FDMA. Os terminais de utilizador possuem baixa complexidade, equipados apenas com pré-codificadores analógicos baseados no ângulo médio de partida, cada um com uma única cadeia de radiofrequência. Na estação base é projectado um equalizador iterativo híbrido analógico-digital com arquitectura completamente conectada de modo a eliminar a interferencia multi-utilizador e a distorção causada pela amplificação do sinal aquando da transmissão. O equalizador é optimizado minimizando a taxa de erro de bit, o que é equivalente a minimizar a taxa de erro quadrático médio. O impacto do limiar de saturação dos amplificadores no desempenho do sistema é analisado, e é demonstrado que o processo iterativo consegue eliminar de modo eficiente a interferência multi-utilizador e a distorção, melhorando o desempenho do sistema.Mestrado em Engenharia Eletrónica e Telecomunicaçõe