Performance versus Complexity Per Iteration for Low-Density Parity-Check Codes: An Information-Theoretic Approach

Details Performance versus Complexity Per Iteration for Low-Density Parity-Check Codes: An Information-Theoretic Approach Performance versus Complexity Per Iteration for Low-Density Parity-Check Codes: An Information-Theoretic Approach

2005-12-18

arxiv.org/abs/cs/0512075v1

Computer Science

Information Theory

Accepted for presentation in the Fourth International Symposium on Turbo Codes and Related Topics, Munich, Germany, 3--7 April

Scientific paper

The paper is focused on the tradeoff between performance and decoding complexity per iteration for LDPC codes in terms of their gap (in rate) to capacity. The study of this tradeoff is done via information-theoretic bounds which also enable to get an indication on the sub-optimality of message-passing iterative decoding algorithms (as compared to optimal ML decoding). The bounds are generalized for parallel channels, and are applied to ensembles of punctured LDPC codes where both intentional and random puncturing are addressed. This work suggests an improvement in the tightness of some information-theoretic bounds which were previously derived by Burshtein et al. and by Sason and Urbanke.

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