Iterative Detection for Channels With Memory

Abstract

By examining various approaches and techniques, this paper aims to help designers to create improved algorithms for communications over noisy channels with memory.By Achilleas Anastasopoulos, Member IEEE, Keith M. Chugg, Member IEEE, Giulio Colavolpe, Member IEEE, Gianluigi Ferrari, Member IEEE, and Riccardo Raheli, Member IEEE ABSTRACT | In this paper, we present an overview on the design of algorithms for iterative detection over channels with memory. The starting point for all the algorithms is the implementation of soft-input soft-ouput maximum a posteriori (MAP) symbol detection strategies for transmissions over channels encompassing unknown parameters, either stochastic or deterministic. The proposed solutions represent effective ways to reach this goal. The described algorithms are grouped into three categories: i) we first introduce algorithms for adaptive iterative detection, where the unknown channel parameters are explicitly estimated; ii) then, we consider finite-memory iterative detection algorithms, based on ad hoc truncation of the channel memory and often interpretable as based on an implicit estimation of the channel parameters; and iii) finally, we present a general detection-theoretic approach to derive optimal detection algorithms with polynomial complexity. A few illustrative numerical results are also presented.

Factor graph based detection approach for high-mobility OFDM systems with large FFT modes

“…Essentially, FGs represent graphically the factorization of a function, and have been shown to be a good alternative to solve complex inference problems. Many recent articles address the use of FG-based algorithms (also known as belief propagation (BP) algorithms) for detection or equalization in channels with memory [31][32][33]. Recently, this framework has been extended to ICI channels: a set of detection algorithms have been presented based on the Ungerboeck approach for MAP symbol detection [34], while in [35], progressive parallel ICI cancelation has been proposed based on FGs.…”

Equalization of Time-Varying Channels

“…For fixed-lag MAP symbol estimation, Zhang, Fitz, and Gelfand [ZFG97] proposed to use per-survivor Kalman filtering, echoing earlier work by Iltis et al [ISG94]. Anastasopoulos and Chugg [AC00] then presented two general families of trellis algorithms, one based on parameter-first combining and the other on sequence-first combining, that yield both forward-backward and fixed-lag algorithms.…”

“…For example, Kubo, Murakami, and Fujino [KMF94] proposed to use the Viterbi algorithm in conjunction with the LMS algorithm [Hay01] for per-survivor channel estimation, whereas Raheli, Polydoros, and Tzou [RPT95] proposed to use the Viterbi algorithm in conjunction with the RLS algorithm [Hay01]. Other LMS and RLS approaches were discussed in [AC00].…”

A novel soft equalization for MIMO systems with recycled extrinsic information

“…These methods iteratively update the extrinsic information between soft equalizer and soft decoder where the output of each terminal is striped off the input information. An extensive review of these methods can be found in [3].…”