DocumentCode
1236056
Title
Universal source controlled channel decoding with nonsystematic quick-look-in turbo codes
Author
Shamir, Gil I. ; Xie, Kai
Volume
57
Issue
4
fYear
2009
fDate
4/1/2009 12:00:00 AM
Firstpage
960
Lastpage
971
Abstract
Utilization of redundancy left in a channel coded sequence can improve channel decoding performance. Stronger improvement can usually be achieved with nonsystematic encoding. However, nonsystematic codes recently proposed for this problem are not robust to the statistical parameters governing a sequence and thus should not be used without prior knowledge of these parameters. In this work, decoders of nonsystematic quick-look-in turbo codes are adapted to extract and exploit redundancy left in coded data to improve channel decoding performance. Methods, based on universal compression and denoising, for extracting the governing statistical parameters for various source models are integrated into the channel decoder by also taking advantage of the code structure. Simulation results demonstrate significant performance gains over standard systematic codes that can be achieved with the new methods for a wide range of statistical models and governing parameters. In many cases, performance almost as good as that with perfect knowledge of the governing parameters is achievable.
Keywords
combined source-channel coding; decoding; statistical analysis; turbo codes; channel coded sequence; joint source-channel coding; nonsystematic encoding; nonsystematic quick-look-in turbo code; statistical model; universal compression; universal denoising; universal source controlled channel decoding; AWGN; Data mining; Decoding; Gas insulated transmission lines; Information theory; Noise reduction; Redundancy; Robustness; Signal to noise ratio; Turbo codes; Joint source-channel coding, quick-look-in turbo codes, universal source controlled channel decoding;
fLanguage
English
Journal_Title
Communications, IEEE Transactions on
Publisher
ieee
ISSN
0090-6778
Type
jour
DOI
10.1109/TCOMM.2009.04.070275
Filename
4814364
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