Trellis-Based Equalization for Sparse ISI Channels Revisited

Sparse intersymbol-interference (ISI) channels are encountered in a variety of high-data-rate communication systems. Such channels have a large channel memory length, but only a small number of significant channel coefficients. In this paper, trellis-based equalization of sparse ISI channels is revisited. Due to the large channel memory length, the complexity of maximum-likelihood detection, e.g., by means of the Viterbi algorithm (VA), is normally prohibitive. In the first part of the paper, a unified framework based on factor graphs is presented for complexity reduction without loss of optimality. In this new context, two known reduced-complexity algorithms for sparse ISI channels are recapitulated: The multi-trellis VA (M-VA) and the parallel-trellis VA (P-VA). It is shown that the M-VA, although claimed, does not lead to a reduced computational complexity. The P-VA, on the other hand, leads to a significant complexity reduction, but can only be applied for a certain class of sparse channels. In the second part of the paper, a unified approach is investigated to tackle general sparse channels: It is shown that the use of a linear filter at the receiver renders the application of standard reduced-state trellis-based equalizer algorithms feasible, without significant loss of optimality. Numerical results verify the efficiency of the proposed receiver structure.Comment: To be presented at the 2005 IEEE Int. Symp. Inform. Theory (ISIT 2005), September 4-9, 2005, Adelaide, Australi

State–of–the–art report on nonlinear representation of sources and channels

This report consists of two complementary parts, related to the modeling of two important sources of nonlinearities in a communications system. In the first part, an overview of important past work related to the estimation, compression and processing of sparse data through the use of nonlinear models is provided. In the second part, the current state of the art on the representation of wireless channels in the presence of nonlinearities is summarized. In addition to the characteristics of the nonlinear wireless fading channel, some information is also provided on recent approaches to the sparse representation of such channels

Channel detection on two-dimensional magnetic recording

Two-dimensional magnetic recording (TDMR) coupled with shingled-magnetic recording (SMR) is one of next generation techniques for increasing the hard disk drive (HDD) capacity up to 10 Tbit/in2 in order to meet the growing demand of mass storage.We focus on solving the tough problems and challenges on the detection end of TDMR. Since the reader works on the overlapped tracks, which are even narrower than the read head, the channel detector works in an environment of low signal-to-noise ratio (SNR), two-dimensional (2-D) inter-symbol interference (ISI) and colored noise, therefore it requires sophisticated detection techniques to provide reliable data recovery. Given that the complexity of optimal 2-D symbol detection is exponential on the data width, we had to choose suboptimal solutions.To build our research environment, we use an innovative Voronoi grain based channel model which captures the important features of SMR, such as squeezed tracks, tilted bit cells, 2-D ISI, electronic and media noise, etc. Then we take an in-depth exploration of channel detection techniques on the TDMR channel model. Our approaches extend the conventional 1-D detection techniques, by using a joint-track equalizer to optimize the 2-D partial-response (PR) target followed by the multi-track detector (MTD) for joint detection, or using the inter-track interference (ITI) canceller to estimate and cancel the ITI from side tracks, followed by a standard BCJR detector. We used the single-track detector (STD) for pre-detecting the side tracks to lower the overall complexity. Then we use pattern-dependent noise prediction (PDNP) techniques to linearly predict the noise sample, so as to improve the detection performance under colored media noise, and especially the data dependent jitter noise. The results show that our 2-D detectors provide significant performance gains against the conventional detectors with manageable complexity

Sparse Nonlinear MIMO Filtering and Identification

In this chapter system identification algorithms for sparse nonlinear multi input multi output (MIMO) systems are developed. These algorithms are potentially useful in a variety of application areas including digital transmission systems incorporating power amplifier(s) along with multiple antennas, cognitive processing, adaptive control of nonlinear multivariable systems, and multivariable biological systems. Sparsity is a key constraint imposed on the model. The presence of sparsity is often dictated by physical considerations as in wireless fading channel-estimation. In other cases it appears as a pragmatic modelling approach that seeks to cope with the curse of dimensionality, particularly acute in nonlinear systems like Volterra type series. Three dentification approaches are discussed: conventional identification based on both input and output samples, semi–blind identification placing emphasis on minimal input resources and blind identification whereby only output samples are available plus a–priori information on input characteristics. Based on this taxonomy a variety of algorithms, existing and new, are studied and evaluated by simulation

Mixed Norm Equalization with Applications in Television Multipath Cancellation

Electrical Engineerin

Spatial diversity in MIMO communication systems with distributed or co-located antennas

The use of multiple antennas in wireless communication systems has gained much attention during the last decade. It was shown that such multiple-input multiple-output (MIMO) systems offer huge advantages over single-antenna systems. Typically, quite restrictive assumptions are made concerning the spacing of the individual antenna elements. On the one hand, it is typically assumed that the antenna elements at transmitter and receiver are co-located, i.e., they belong to some sort of antenna array. On the other hand, it is often assumed that the antenna spacings are sufficiently large, so as to justify the assumption of independent fading. In this thesis, the above assumptions are relaxed. In the first part, it is shown that MIMO systems with distributed antennas and MIMO systems with co-located antennas can be treated in a single, unifying framework. In the second part this fact is utilized, in order to develop appropriate transmit power allocation strategies for co-located and distributed MIMO systems. Finally, the third part focuses on specific synchronization problems that are of interest for distributed MIMO systems

Underwater acoustic communication under doppler effects

In this thesis we perform a research survey of the three available technologies for wireless underwater communications. We discuss the main features and drawbacks inherent to acoustic, RF, and optical communications. We focus our research on underwater acoustic communications, and we analyze and evaluate the channel frequency response of Arraial do Cabo using data acquired in situ. We further investigate the Doppler effect, a phenomenon that is inherent to underwater acoustic channels. We analyze and justify a compensation algorithm to mitigate the Doppler effects. We propose a simplified algorithm version for minimizing the required number of pilot symbols. We also develop a simple strategy to determine how often our proposed compensation method should be retrained. Our main contribution is the proposal of a new receiver design to deal with Doppler effects. We present the idea of iteratively adapt the correlator filter placed at the receiver side. We show that the adaptation of this filter’s support reduces the inter-symbol interference of the estimated symbols. Besides this idea, we demonstrate that the time-dependent phase-shift component of the received signal should be removed beforehand. That is, we propose a modification in the signal processing sequence blocks for improving the symbol estimation. For testing and comparing this new receiver design, we implement a communication model encompassing physical layer aspects. We perform several numerical simulations for single-carrier and multicarrier systems. Simulation results show that our proposal might provide a reduction in the bit error rate for high signal-to-noise ratios. This performance improvement can be observed for all tested relative movement, and even with dense digital signal constellation.Nesta tese foi realizada uma pesquisa extensa sobre as tecnologias existentes para comunicação sem fio subaquática. Foram analisadas as principais características das comunicações acústicas, RF e ótica. O estudo foi aprofundado na comunicação acústica, e foi realizada uma análise da resposta em frequência do canal de Arraial do Cabo com dados adquiridos no local. O efeito Doppler, um fenômeno inerente aos canais subaquáticos acústicos, foi investigado de forma minuciosa. Dentre as técnicas estudas para compensação deste efeito, foi escolhido um algoritmo adaptativo, o qual foi re-analisado com uma nova abordagem. Uma versão simplificada deste algoritmo foi proposta para reduzir a quantidade de símbolos pilotos. Foi também desenvolvida uma estratégia para determinar a frequência de treinamento deste novo algoritmo. A principal contribuição da tese é a proposta de uma nova estrutura de receptor para compensar o efeito Doppler. Nesta estrutura, é proposta a adaptação de forma iterativa do filtro correlator. A adaptação do suporte temporal deste filtro reduz a interferência inter-simbólica. Além desta ideia, foi demonstrado que a componente de fase do sinal recebido, que é dependente do tempo, deve ser removida em um estágio anterior ao usual. Ou seja, foi proposta uma modificação na sequência do processamento do sinal recebido para melhorar a sua estimativa. Para testar esta nova estrutura do receptor, foi implementado um sistema de comunicação. Foram realizadas simulações numéricas com sistemas de uma única e de múltiplas portadoras. Os resultados das simulações mostram que a nova estrutura pode reduzir a quantidade de erros de bits para altos valores de razão sinal-ruído. A melhora do desempenho pode ser observada em todas as velocidades relativas testadas, e também para constelações densas