Multiple-Input Multiple-Output Detection Algorithms for Generalized Frequency Division Multiplexing

Since its invention, cellular communication has dramatically transformed personal lifes and the evolution of mobile networks is still ongoing. Evergrowing demand for higher data rates has driven development of 3G and 4G systems, but foreseen 5G requirements also address diverse characteristics such as low latency or massive connectivity. It is speculated that the 4G plain cyclic prefix (CP)-orthogonal frequency division multiplexing (OFDM) cannot sufficiently fulfill all requirements and hence alternative waveforms have been in-vestigated, where generalized frequency division multiplexing (GFDM) is one popular option. An important aspect for any modern wireless communication system is the application of multi-antenna, i.e. MIMO techiques, as MIMO can deliver gains in terms of capacity, reliability and connectivity. Due to its channel-independent orthogonality, CP-OFDM straightforwardly supports broadband MIMO techniques, as the resulting inter-antenna interference (IAI) can readily be resolved. In this regard, CP-OFDM is unique among multicarrier waveforms. Other waveforms suffer from additional inter-carrier interference (ICI), inter-symbol interference (ISI) or both. This possibly 3-dimensional interference renders an optimal MIMO detection much more complex. In this thesis, weinvestigate how GFDM can support an efficient multiple-input multiple-output (MIMO) operation given its 3-dimensional interference structure. To this end, we first connect the mathematical theory of time-frequency analysis (TFA) with multicarrier waveforms in general, leading to theoretical insights into GFDM. Second, we show that the detection problem can be seen as a detection problem on a large, banded linear model under Gaussian noise. Basing on this observation, we propose methods for applying both space-time code (STC) and spatial multiplexing techniques to GFDM. Subsequently, we propose methods to decode the transmitted signals and numerically and theoretically analyze their performance in terms of complexiy and achieved frame error rate (FER). After showing that GFDM modulation and linear demodulation is a direct application of Gabor expansion and transform, we apply results from TFA to explain singularities of the modulation matrix and derive low-complexity expressions for receiver filters. We derive two linear detection algorithms for STC encoded GFDM signals and we show that their performance is equal to OFDM. In the case of spatial multiplexing, we derive both non-iterative and iterative detection algorithms which base on successive interference cancellation (SIC) and minimum mean squared error (MMSE)-parallel interference cancellation (PIC) detection, respectively. By analyzing the error propagation of the SIC algorithm, we explain its significantly inferior performance compared to OFDM. Using feedback information from the channel decoder, we can eventually show that near-optimal GFDM detection can outperform an optimal OFDM detector by up to 3dB for high SNR regions. We conclude that GFDM, given the obtained results, is not a general-purpose replacement for CP-OFDM, due to higher complexity and varying performance. Instead, we can propose GFDM for scenarios with strong frequency-selectivity and stringent spectral and FER requirements

Sistemas MIMO auxiliados por grandes superfícies refletoras como novidade para tecnologias 6G

Orientador: Gustavo FraidenraichDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Large Intelligent Surfaces (LIS) é uma tecnologia promissora para a sexta geração (6G) de comunicações móveis devido ao seu potencial para melhorar a relação sinal-ruído (SNR), aumentar a eficiência espectral e ainda possibilitar a redução do consumo de energia no estação rádio base (BS) durante a transmissão. O LIS é um painel formado por células que podem refletir ondas eletromagnéticas para fazer beamforming e remover a fase do canal, a superfície é formada por metamateriais que podem alterar a fase das ondas incidentes com um ângulo quantizado que pode ser controlado digitalmente por software permitindo que o sinal resultante da soma de todas as componentes refletidas pelo LIS possua uma fase adaptada para cancelar o efeito da fase do canal. Esta fase é estimada por algoritmos de aprendizado de máquina e quanto mais eficiente a estimativa melhor será o processo de ajuste de fase, mas devido às não idealidades do sistema, temos um erro de fase residual que neste trabalho é modelado pela distribuição de Von Mises. Dividimos nosso estudo em dois capítulos, o primeiro referindo-se a sistemas com apenas uma antena na BS, considerando a presença de uma linha direta de propagação de ondas eletromagnéticas a.k.a. line of sight (LoS) com desvanecimento Nakagami-m e nós ignoramos a possibilidade de um link direto com o usuário, já na segunda parte consideramos um arranjo de antenas na estação base e incluindo um link direto entre o usuário e a BS, mas negligenciando a LoS ao considerar canais com desvanecimento Rayleigh. Para o cenário da BS de uma antena, derivamos a probabilidade de erro de bit exata considerando modulação M-QAM e BPSK quando o número de elementos do LIS, n , é igual a 2 e 3 considerando que os coeficientes de desvanecimento do canal são Nakagami-m e o LIS tem um erro de fase com distribuição de Von Mises. Além disso, com base no teorema do limite central, e considerando um grande número de elementos refletores, apresentamos uma aproximação precisa e limites superiores para a taxa de erro de bit. Por meio de várias simulações de Monte Carlo, demonstramos que todas as expressões derivadas correspondem perfeitamente aos resultados simulados. No cenário de matriz de antenas, consideramos o Rayleigh flat fading para cada subcanal entre a BS, o LIS e o usuário e aplicamos um precoder na estação base para ter a transmissão de razão máxima (MRT). Com base no teorema do limite central (CLT), concluímos que o canal total tem um desvanecimento Gamma equivalente cujos parâmetros são derivados dos momentos estatísticos do canal entre o arranjo de antenas e LIS, e também do LIS para o usuário. Assumindo que o canal equivalente pode ser modelado como uma distribuição Gama, propomos expressões de forma fechada muito precisas para a probabilidade de erro de bit e um limite superior muito restrito. Para o caso em que o LIS não é capaz de realizar o cancelamento de fase perfeito, ou seja, sob erros de fase, é possível analisar o desempenho do sistema considerando as aproximações analíticas e os resultados simulados obtidos pelo método de Monte Carlo. As expressões analíticas para os parâmetros da distribuição Gama são muito difíceis de serem obtidas devido à complexidade das transformações não lineares de variáveis aleatórias com média diferente de zero e termos correlatos. Mesmo com o cancelamento de fase perfeito, todos os coeficientes de desvanecimento são complexos devido à ligação entre o usuário e a estação base que não é negligenciada neste estudoAbstract: Large intelligent surfaces (LIS) is a promising technology for the sixth generation (6G) of mobile communications due to its potential to improve the signal to noise ratio (SNR), increase spectral efficiency, and even make it possible to reduce energy consumption in the radio base station (BS) during transmission. The LIS is a panel formed by cells that can reflect electromagnetic waves to make beamforming and cancel the channel phase, the surface is formed by metamaterials that can change the phase of the incident waves with a quantized angle that can be controlled digitally by software allowing that the signal resulting from the sum of all components reflected by the LIS has a phase adapted to nullify the effect of the channel phase. The channel information is estimated by machine learning algorithms and more efficient phase estimations implies better phase adjustments at the LIS, but due to the system's non-idealities, we have a residual phase error that in this work is modeled by the Von Mises distribution. We divided our study into two chapters, the first referring to systems with a single antenna at the BS considering the existence of a straight and unobstructed line for electromagnetic wave propagation a.k.a. line of sight (LoS) with Nakagami-m fading and we ignore the possibility of a direct link between the user, in the second part we consider an antenna array at the base station and including a direct link between the user and the BS but neglecting the LoS by considering Rayleigh fading channels. For the single antenna BS scenario, we derive the exact bit error probability considering quadrature amplitude modulation (M-QAM) and binary phase-shift keying (BPSK) when the number of LIS elements, n, is equal to 2 and 3 considering that the channel fading coefficients are Nakagami-m. Also, based on the central limit theorem (CLT), and considering a large number of reflecting elements, we present an accurate approximation and upper bounds for the bit error rate. Through several Monte Carlo simulations, we demonstrate that all derived expressions perfectly match the simulated results. In the antenna array scenario, we consider Rayleigh flat fading for each subchannel between the BS, the LIS, and the user and we apply a precoder at the base station to have the maximum ratio transmission (MRT). Based on the CLT, we conclude that the overall channel has an equivalent Gamma fading whose parameters are derived from the moments of the channel fading between the antenna array and LIS, and also from the LIS to the single user. Assuming that the equivalent channel can be modeled as a Gamma distribution, we propose very accurate closed-form expressions for the bit error probability and a very tight upper bound. For the case where the LIS is not able to perform perfect phase cancellation, that is, under phase errors, it is possible to analyze the system performance considering the analytical approximations and the simulated results obtained using the well known Monte Carlo method. The analytical expressions for the parameters of the Gamma distribution are very difficult to be obtained due to the complexity of the nonlinear transformations of random variables with non-zero mean and correlated terms. Even with perfect phase cancellation, all the fading coefficients are complex due to the link between the user and the base station that is not neglected in this studyMestradoTelecomunicações e TelemáticaMestre em Engenharia Elétrica88882.329402/2019-01CAPE

Achievable rates of iterative MIMO receivers over interference channels

In this thesis, we study the achievable rates of some interference communication schemes when iterative interference-cancellation (IC) is applied. We assume multiple-input multiple-output (MIMO) communication employing iterative receivers with linear front-ends which involves two modules concatenated serially and cooperating iteratively; a linear combiner based on minimum-mean-square-error (MMSE) detection or maximal-ratio-combining (MRC) and a SISO decoder. We investigate the achievable rates of this receiver when the transmitted signal is Gaussian-distributed with hypothetical erasure-type feedback from the decoder to the combiner and a more practical case with large-size QAM constellations with log-likelihood-ratios (LLRs) being exchanged between the receiver's modules. The achievable rate is approximated by the area below the EXIT curve of the linear FE receiver. Some properties have been observed and mathematically been proved about the iterative MIMO receivers with linear front-end

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic