DocumentCode :
649022
Title :
High speed decoding of non-binary irregular LDPC codes using GPUs
Author :
Beermann, Moritz ; Monro, Enrique ; Schmalen, Laurent ; Vary, Peter
Author_Institution :
Leineweber GmbH, Aachen, Germany
fYear :
2013
fDate :
16-18 Oct. 2013
Firstpage :
36
Lastpage :
41
Abstract :
Low-Density Parity-Check (LDPC) codes are very powerful channel coding schemes with a broad range of applications. The existence of low complexity (i.e., linear time) iterative message passing decoders with close to optimum error correction performance is one of the main strengths of LDPC codes. It has been shown that the performance of these decoders can be further enhanced if the LDPC codes are extended to higher order Galois fields, yielding so called non-binary LDPC codes. However, this performance gain comes at the cost of rapidly increasing decoding complexity. To deal with this increased complexity, we present an efficient implementation of a signed-log domain FFT decoder for non-binary irregular LDPC codes that exploits the inherent massive parallelization capabilities of message passing decoders. We employ Nvidia´s Compute Unified Device Architecture (CUDA) to incorporate the available processing power of state-of-the-art Graphics Processing Units (GPU s).
Keywords :
Galois fields; channel coding; codecs; decoding; error correction codes; fast Fourier transforms; graphics processing units; iterative methods; logic design; parity check codes; CUDA; GPU; Nvidia´s compute unified device architecture; channel coding schemes; decoding complexity; graphics processing units; high speed decoding; higher order Galois fields; iterative message passing decoders; low-density parity-check codes; nonbinary irregular LDPC codes; optimum error correction performance; performance gain; signed-log domain FFT decoder; GPU implementation; iterative decoding; non-binary LDPC codes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Systems (SiPS), 2013 IEEE Workshop on
Conference_Location :
Taipei City
ISSN :
2162-3562
Type :
conf
DOI :
10.1109/SiPS.2013.6674477
Filename :
6674477
Link To Document :
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