Memory-efficient sum-product decoding of LDPC codes

Low-density parity-check (LDPC) codes perform very close to capacity for long lengths on several channels. However, the amount of memory (fixed-point numbers that need to be stored) required for implementing the message-passing algorithm increases linearly as the number of edges in the graph increas...

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Bibliographic Details
Published in:IEEE transactions on communications 2004-08, Vol.52 (8), p.1225-1230
Main Authors: Sankar, H., Narayanan, K.R.
Format: Article
Language:English
Subjects:
Additive white noise
Algorithm design and analysis
Applied sciences
Approximation algorithms
AWGN
Bipartite graph
Bit error rate
Coding, codes
Exact sciences and technology
Gaussian approximation
Information, signal and communications theory
Iterative decoding
Parity check codes
Signal and communications theory
Telecommunications and information theory
Turbo codes
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Summary:Low-density parity-check (LDPC) codes perform very close to capacity for long lengths on several channels. However, the amount of memory (fixed-point numbers that need to be stored) required for implementing the message-passing algorithm increases linearly as the number of edges in the graph increases. In this letter, we propose a decoding algorithm for decoding LDPC codes that reduces the memory requirement at the decoder. The proposed decoding algorithm can be analyzed using density evolution; further, we show how to design good LDPC codes using this. Results show that this algorithm provides almost the same performance as the conventional sum-product decoding of LDPC codes.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2004.833016