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Science China Information Sciences

Forced-convergence decoding for LDPC-coded modulation

Liyun Dai, Hongwen Yang, Jianxiao Fan, Wenyuan Rao

Published Nov 8, 2012• 12 citations
Publisher
DOI
10.1007/s11432-012-4710-8

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An improvement of the forced-convergence decoding algorithm is discussed. Iterative decoding schemes such as the sum-product (SP) decoding bring out excellent performance of low-density parity check (LDPC) codes. The forced-convergence (FC) decoding is also an iterative decoding algorithm obtained by modifying the SP decoding. The FC decoding succeeds to reduce the decoding complexity of the SP decoding, but the error correcting performance is severely degraded by the modification. The performance degradation of the FC decoding is expected to be mitigated if the convergence criterion used in the algorithm is appropriately modified. This paper discusses several types of modifications of the convergence criteria. Computer simulation shows that the proposed modifications improve the performance of the FC decoding algorithm.
An efficient early stopping criterion based on the evolution of the number of reliable variable nodes (NRVN) is proposed for low density parity check (LDPC) codes in this paper. This criterion can significantly reduce the average number of iterations (ANI) at low to middle signal to noise ratios (SNRs) with minimal performance degradation. Furthermore, a hybrid decoding method is presented to reduce the decoding complexity of LDPC codes by combining the proposed stopping criterion and forced convergence (FC) decoding algorithm. Compared with the classic belief propagation (BP) decoding, significant computation complexity reduction can be achieved with small computation overhead.
Abstract — Low-density parity-check (LDPC) codes have recently emerged as a viable option for forward error correction (FEC) in future wireless communications systems. One factor influencing the decision of whether to use a specific FEC technique in a system is its suitability for real time systems – and hence, its computational complexity. In this paper, we present a novel LDPC decoding architecture, where we use a threshold rule to decide whether a variable node of the LDPC decoder should update its information in subsequent iterations of the decoding process, or be considered as converged. We show that by choosing this threshold appropriately, decoding complexity can be significantly reduced with only negligible deterioration in error correction performance. I.