Iterative detection for channels with memory

作     者：Anastasopoulos, Achilleas Chugg, M. Colavolpe, Giulio Ferrari, Gianluigi Raheli, Riccardo 

作者机构：Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA Univ So Calif Inst Commun Sci Elect Engn Dept Syst Div Los Angeles CA 90089 USA 

出 版 物：《PROCEEDINGS OF THE IEEE》 (电气与电子工程师学会会报)

年 卷 期：2007年第95卷第6期

页      面：1272-1294页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：ESA-ESTEC National Science Foundation, NSF University of Southern California, USC European Space Agency, ESA 

主　　题：adaptive iterative detection channels with memory finite-memory detection iterative detection/decoding message passing detection algorithms polynomial complexity detection trellis-based detection 

摘      要：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.