Abstract Multiuser demodulation algorithms for centralized receivers of asynchronous direct-sequence (DS) spread-spectrum code-division multiple-access (CDMA) systems in frequency-selective fading channels are studied. Both DS-CDMA systems with short (one symbol interval) and long (several symbol intervals) spreading sequences are considered. Linear multiuser receivers process ideally the complete received data block. The approximation of ideal infinite memory-length (IIR) linear multiuser detectors by finite memory-length (FIR) detectors is studied. It is shown that the FIR detectors can be made near-far resistant under a given ratio between maximum and minimum received power of users by selecting an appropriate memory-length. Numerical examples demonstrate the fact that moderate memory-lengths of the FIR detectors are sufficient to achieve the performance of the ideal IIR detectors even under severe near-far conditions. Multiuser demodulation in relatively fast fading channels is analyzed. The optimal maximum likelihood sequence detection receiver and suboptimal receivers are considered. The parallel interference cancellation (PIC) receiver is demonstrated to achieve better performance in known channels than the decorrelating receiver, but it is observed to be more sensitive to channel coefficient estimation errors than the decorrelator. At high channel loads the PIC receiver suffers from bit error rate (BER) saturation, whereas the decorrelating receiver does not. Choice of channel estimation filters is shown to be crucial if low BER is required. Data-aided channel estimation is shown to be more robust than decision-directed channel estimation, which may suffer from BER saturation caused by hang-ups at high signal-to-noise ratios. Multiuser receivers for dynamic CDMA systems are studied. Algorithms for ideal linear detector computation are derived and their complexity is analyzed. The complexity of the linear detector computation is a cubic function of KL, where K and L are the number of users and multipath components, respectively. Iterative steepest descent, conjugate gradient, and preconditioned conjugate gradient algorithms are proposed to reduce the complexity. The computational requirements for one iteration are a quadratic function of KL. The iterative detectors are also shown to be applicable for parallel implementation. Simulation results demonstrate that a moderate number of iterations yields the performance of the corresponding ideal linear detectors. A quantitative analysis shows that the PIC receivers are significantly simpler to implement than the linear receivers and only moderately more complex than the conventional matched filter bank receiver.

Turbo-codes have attracted an explosion of interest since their discovery in 1993: for the first time, the gap with the limits predicted by information and coding theory was on the way to be bridged. The astonishing performance of turbo-codes relies on two major concepts: code concatenation so as to build a powerful global code, and iterative decoding in order to efficiently approximate the optimal decoding process. As a matter of fact, the techniques involved in turbo coding and in the associated iterative decoding strategy can be generalized to other problems frequently encountered in digital communications. This results in a so-called turbo principle. A famous application of the latter principle is the communication scheme referred to as turbo-equalization: when considering coded transmission over a frequency-selective channel, it enables to jointly and efficiently perform the equalization and decoding tasks required at the receiver. This leads by the way to significant performance improvement with regard to conventional disjoint approaches. In this context, the purpose of the present thesis is the derivation and the performance study of novel digital communication receivers, which perform iterative joint detection and decoding by means of the turbo principle. The binary turbo-equalization scheme is considered as a starting point, and improved in several ways, which are detailed throughout this work. Emphasis is always put on the performance analysis of the proposed communication systems, so as to reach insight about their behavior. Practical considerations are also taken into account, in order to provide realistic, tractable, and efficient solutions.

Timing recovery is the processing of synchronizing the sampler with the received analog signal. Sampling at the wrong times can have a devastating impact on performance. Conventional timing recovery techniques are based on a decision-directed phase-locked loop (PLL). They are adequate only when the operating signal-to-noise ratio (SNR) is sufficiently high, but recent advances in error-control coding have made it possible to communicate reliably at very low SNR, where conventional techniques fail. This thesis develops new techniques for timing recovery that are capable of working at low SNR. We propose a new timing recovery scheme based on per-survivor processing (PSP), which jointly performs timing recovery and equalization, by embedding a separate PLL into each survivor of a Viterbi algorithm. The proposed scheme is shown to perform better than conventional scheme, especially when the SNR is low and the timing error is large. An important advantage of this technique is its amenability to real-time implementation. We also propose a new iterative timing recovery scheme that exploits the presence of the error-control code; in doing so, it can perform even better than the PSP scheme described above, but at the expense of increased complexity and the requirement of batch processing. This scheme is realized by embedding the timing recovery process into a trellis-based soft-output equalizer using PSP. Then, this module iteratively exchanges soft information with the error-control decoder, as in conventional turbo equalization. The resulting system jointly performs the functions of timing recovery, equalization, and decoding. The proposed iterative timing recovery scheme is shown to perform better than previously reported iterative timing recovery schemes, especially when the timing error is severe. Finally, performance analysis of iterative timing recovery schemes is difficult because of their high complexity. We propose to use the extrinsic information transfer (EXIT) chart as a tool to predict and compare their performances, considering that the bit-error rate computation takes a significant amount of simulation time. Experimental results indicate that the system performance predicted by the EXIT chart coincides with that obtained by simulating data transmission over a complete iterative receiver, especially when the coded block length is large.

The objective of this research work is to develop reliable and power-efficient synchronization algorithms for continuous phase modulation (CPM). CPM is a bandwidth and power efficient signaling scheme suitable for wireless and mobile communications. Binary CPM schemes have been widely used in many commercial and military systems. CPM with multilevel symbol inputs, i.e., M-ary CPM, can achieve a higher data rate than binary CPM. However, the use of M-ary CPM has been limited due to receiver complexity and synchronization problems. In the last decade, serially concatenated CPM (SCCPM) has drawn more attention since this turbo-like coded scheme can achieve near Shannon-limit performance by performing iterative demodulation/decoding. Note that SCCPM typically operates at a low signal-to-noise ratio, which makes reliable and power-efficient synchronization more challenging. In this thesis, we propose a novel timing and phase recovery technique for CPM. Compared to existing maximum-likelihood estimators, the proposed data-aided synchronizer can achieve a better acquisition performance when a preamble is short or channel model errors are present. We also propose a novel adaptive soft-input soft-output (A-SISO) module for iterative detection with parameter uncertainty. In contrast to the existing A-SISO algorithms using linear prediction, the parameter estimation in the proposed structure is performed in a more general least-squares sense. Based on this scheme, a family of fixed-interval A-SISO algorithms are utilized to implement blind iterative phase synchronization for SCCPM. Moreover, the convergence characteristics of iterative phase synchronization and detection are analyzed by means of density evolution. Particularly, an oscillatory convergence behavior is observed when cycle slips occur during phase tracking. In order to reduce performance degradation due to this convergence fluctuation, design issues, including delay depth of the proposed algorithms, iteration-stopping criteria and interleaver size, are also discussed. Finally, for completeness of the study on phase synchronization, we investigate the error probability performance of noncoherently detected full-response CPM, which does not require channel (or phase) estimation.

[Truncated abstract] The transmission of digital information over a wireless communication channel gives rise to a number of issues which can detract from the system performance. Propagation effects such as multipath fading and intersymbol interference (ISI) can result in significant performance degradation. Recent developments in the field of iterative detection have led to a number of powerful strategies that can be effective in mitigating the detrimental effects of wireless channels. In this thesis, iterative detection is considered for use in two distinct areas of wireless communications. The first considers the iterative decoding of concatenated block codes over slow flat fading wireless channels, while the second considers the problem of detection for a coded communications system transmitting over highly-dispersive frequency-selective wireless channels. The iterative decoding of concatenated codes over slow flat fading channels with coherent signalling requires knowledge of the fading amplitudes, known as the channel state information (CSI). The CSI is combined with statistical knowledge of the channel to form channel reliability metrics for use in the iterative decoding algorithm. When the CSI is unknown to the receiver, the existing literature suggests the use of simple approximations to the channel reliability metric. However, these works generally consider low rate concatenated codes with strong error correcting capabilities. In some situations, the error correcting capability of the channel code must be traded for other requirements, such as higher spectral efficiency, lower end-to-end latency and lower hardware cost. ... In particular, when the error correcting capabilities of the concatenated code is weak, the conventional metrics are observed to fail, whereas the proposed metrics are shown to perform well regardless of the error correcting capabilities of the code. The effects of ISI caused by a frequency-selective wireless channel environment can also be mitigated using iterative detection. When the channel can be viewed as a finite impulse response (FIR) filter, the state-of-the-art iterative receiver is the maximum a posteriori probability (MAP) based turbo equaliser. However, the complexity of this receiver's MAP equaliser increases exponentially with the length of the FIR channel. Consequently, this scheme is restricted for use in systems where the channel length is relatively short. In this thesis, the use of a channel shortening prefilter in conjunction with the MAP-based turbo equaliser is considered in order to allow its use with arbitrarily long channels. The prefilter shortens the effective channel, thereby reducing the number of equaliser states. A consequence of channel shortening is that residual ISI appears at the input to the turbo equaliser and the noise becomes coloured. In order to account for the ensuing performance loss, two simple enhancements to the scheme are proposed. The first is a feedback path which is used to cancel residual ISI, based on decisions from past iterations. The second is the use of a carefully selected value for the variance of the noise assumed by the MAP-based turbo equaliser. Simulations are performed over a number of highly dispersive channels and it is shown that the proposed enhancements result in considerable performance improvements. Moreover, these performance benefits are achieved with very little additional complexity with respect to the unmodified channel shortened turbo equaliser.

[pt] Este trabalho tem como finalidade estudar o problema da detecção de usuários no canal reverso de sistemas MIMO de larga escala, que são caracterizados pelo elevado número de elementos de transmissão e recepção, com foco na complexidade computacional e no desempenho em termos de taxa de erro destes sistemas. Inicialmente, os algoritmos de detecção da família Likelihood Ascent Search (LAS) são investigados e é desenvolvido um novo algoritmo de detecção, denominado de Random-List Based LAS (RLBLAS), capaz de atingir melhores taxas de erros com menor complexidade computacional do que os demais detectores considerados. Posteriormente, técnicas de detecção e decodificação iterativas (Iterative Detection and Decoding - IDD) em sistemas MIMO foram analisadas de forma a propor uma estratégia IDD de complexidade computacional reduzida a fim de viabilizar a sua aplicação em cenários massivos. Finalmente, o problema da contaminação por pilotos em sistemas MIMO multicelulares de larga escala, um dos principais limitadores do desempenho desse tipo de sistema, é estudado e estratégias de detecção com cooperação parcial entre as estações base componentes do sistema que visam mitigar os efeitos da contaminação por pilotos são propostas. As análises e afirmações realizadas durante a presente tese são sustentadas por resultados de simulações de Monte Carlo dos sistemas de comunicações em diversos cenários distintos, incluindo os casos em que são considerados os efeitos de correlação entre as antenas de transmissão/recepção, os efeitos de sombreamento e os erros de estimação dos estados dos canais de comunicações envolvidos. / [en] This work focuses on the multi-user multi-cellular large-scale MIMO reverse channel detection problem, where the number of transmitting and receiving antenna elements grows to the order of hundreds. In these scenarios, one major issue is the computational complexity of such systems. Therefore, this thesis aims to propose low-complexity techniques with good BER performance for the reverse channel detection of MIMO systems. Initially, the detection algorithms of the Likelihood Ascent Search (LAS) family are investigated and a new LAS based detector is proposed. This new detector, named Random-List Based LAS (RLB-LAS), is capable of achieving better BER with lower complexity then the other considered detectors. Next, iterative detection and decoding (IDD) techniques are analyzed in order to propose an IDD strategy applied to the detection and decoding of the reverse MIMO channel with reduced complexity to make possible its application to massive scenarios. Finally, the pilot contamination problem in multi-cellular large-scale MIMO systems, one of the major bounds on BER performance of these systems, are studied and some cooperative strategies are proposed in order to reduce the effects of this type of impairments. The analysis and statements of this thesis are supported by Monte Carlo simulation results of the considered systems in different scenarios, including the cases where the effects of transmitting and receiving antenna correlation, log-normal shadowing, and the estimation errors on the channel state information acquisition are considered.

[pt] Com um número crescente de antenas em sistemas MIMO, o consumo de energia e os custos das interfaces de rádio correspondentes tornam-se relevantes. Nesse contexto, uma abordagem promissora é a utilização de conversores de dados de baixa resolução. Neste estudo, propomos dois novos pré-codificadores ótimos para a sinais de envelope constante e quantização de fase. O primeiro maximiza a distância mínima para o limite de decisão (MMDDT) nos receptores, enquanto o segundo minimiza o erro médio quadrático entre os símbolos dos usuários e o sinal de recepção. O design MMDDT apresetado nesse estudo é uma generalização de designs anteriores que baseiam-se em quantização de 1-bit. Além disso, ao contrário do projeto MMSE anterior que se baseia na resolução de 1-bit, a abordagem proposta emprega quantização de fase uniforme e a etapa de limite no método branch-and-bound é diferente em termos de considerar o relaxamento mais restritivo do problema não convexo, que é então utilizado para um design sub ótimo também. Além disso, três métodos diferentes de detecção suave e um esquema iterativo de detecção e decodificação que permite a utilização de codificação de canal em conjunto com pré-codificação de baixa resolução são propostos. Além de uma abordagem exata para calcular a informação extrínseca, duas aproximações com reduzida complexidade computacional são propostas. Os algoritmos propostos de pré-codificação branch-and-bound são superiores aos métodos existentes em termos de taxa de erro de bit. Resultados numéricos mostram que as abordagens propostas têm complexidade significativamente menor do que a busca exaustiva. Finalmente, os resultados baseados em um código de bloco LDPC indicam que os esquemas de processamento de recepção geram uma taxa de erro de bit menor em comparação com o projeto convencional. / [en] With an increasing number of antennas in multiple-input multiple-output (MIMO) systems, the energy consumption and costs of the corresponding front ends become relevant. In this context, a promising approach is the consideration of low-resolution data converters. In this study two novel optimal precoding branch-and-bound algorithms constrained to constant envelope signals and phase quantization are proposed. The first maximizes the minimum distance to the decision threshold (MMDDT) at the receivers, while the second minimizes the MSE between the users data symbols and the receive signal. This MMDDT design presented in this study is a generalization of prior designs that rely on 1-bit quantization. Moreover, unlike the prior MMSE design that relies on 1-bit resolution, the proposed MMSE approach employs uniform phase quantization and the bounding step in the branch-and-bound method is different in terms of considering the most restrictive relaxation of the nonconvex problem, which is then utilized for a suboptimal design also. Moreover, three different soft detection methods and an iterative detection and decoding scheme that allow the utilization of channel coding in conjunction with low-resolution precoding are proposed. Besides an exact approach for computing the extrinsic information, two approximations with reduced computational complexity are devised. The proposed branch-and-bound precoding algorithms are superior to the existing methods in terms of bit error rate. Numerical results show that the proposed approaches have significantly lower complexity than exhaustive search. Finally, results based on an LDPC block code indicate that the proposed receive processing schemes yield a lower bit-error-rate compared to the conventional design.