DocumentCode :
2506804
Title :
Turbo Decoding Complexity Reduction by Symbol Selection and Partial Iterations
Author :
Wu, Jinhong ; Vojcic, Branimir R. ; Wang, Zhengdao
Author_Institution :
George Washington Univ., Washington
fYear :
2007
fDate :
26-30 Nov. 2007
Firstpage :
3910
Lastpage :
3914
Abstract :
Based on an analysis on the recursive computation of the iterative maximum a posteriori (MAP) algorithm for turbo decoding, this paper considers a modified MAP scheme with reduced block lengths for symbols with unreliable detection after some initial iterations. Applying symbol selection based on cross-entropy measurement for parallel concatenated convolutional codes, we develop partial, windowed iterations for selected symbols. By omitting computations for symbols with reliable detection results, this approach significantly reduces complexity but well maintains the performance by complete iterations.
Keywords :
concatenated codes; convolutional codes; iterative decoding; maximum likelihood estimation; turbo codes; iterative maximum a posteriori algorithm; parallel concatenated convolutional codes; partial iterations; recursive computation; symbol selection; turbo decoding complexity reduction; unreliable detection; Algorithm design and analysis; Bit error rate; Concatenated codes; Convolutional codes; Degradation; Iterative algorithms; Iterative decoding; Maintenance; Radio frequency; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Telecommunications Conference, 2007. GLOBECOM '07. IEEE
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-1042-2
Electronic_ISBN :
978-1-4244-1043-9
Type :
conf
DOI :
10.1109/GLOCOM.2007.743
Filename :
4411653
Link To Document :
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