NDLI: Iterative channel equalization, channel decoding and source decoding

Content Provider	IEEE Xplore Digital Library
Author	Wang, J. Lie-Liang Yang Hanzo, L.
Copyright Year	2005
Description	Author affiliation: Sch. of Electr. & Comput. Sci., Southampton Univ., UK (Wang, J.; Lie-Liang Yang; Hanzo, L.)
Abstract	The performance of soft source decoding is evaluated over dispersive AWGN channels. By employing source codes having error-correcting capabilities, such as reversible variable-length codes (RVLC) and variable-length error-correcting (VLEC) codes, the soft-in/soft-out (SISO) source decoder benefits from exchanging information with the MAP equalizer, and effectively eliminates the intersymbol interference (ISI) after a few iterations. It was also found that the soft source decoder is capable of significantly improving the attainable performance of the turbo receiver provided that channel equalization, channel decoding and source decoding are carried out jointly and iteratively. At SER0=1/sup -4/ the performance of this three-component turbo receiver is about 2 dB better in comparison to the benchmark scheme carrying out channel equalization and channel decoding jointly, but source decoding separately. At this SER value, the performance of the proposed scheme is about 1 dB worse than that of the 1/2 -rate convolutional coded non-dispersive AWGN channel.
Starting Page	518
Ending Page	522
File Size	241349
Page Count	5
File Format	PDF
ISBN	0780388879
ISSN	15502252
DOI	10.1109/VETECS.2005.1543345
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-05-30
Publisher Place	Sweden
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Iterative decoding Intersymbol interference Dispersion Redundancy Nonlinear filters AWGN channels Equalizers Convolutional codes Additive white noise Entropy
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Computer Science Applications

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