NDLI: Iterative Detection for Channels With Memory

Content Provider	IEEE Xplore Digital Library
Author	Anastasopoulos, A. Chugg, K.M. Colavolpe, G. Ferrari, G. Raheli, R.
Copyright Year	1963
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.
Sponsorship	IEEE Publication
Starting Page	1272
Ending Page	1294
Page Count	23
File Size	753088
File Format	PDF
ISSN	00189219
Volume Number	95
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Iterative algorithms Detection algorithms Iterative decoding Algorithm design and analysis Polynomials Iterative methods Parameter estimation Turbo codes Parity check codes Stochastic processes trellis-based detection Adaptive iterative detection channels with memory finite-memory detection iterative detection/decoding message passing detection algorithms polynomial complexity detection
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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