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IEEE Communications Letters

Adaptive-Normalized/Offset Min-Sum Algorithm

Xiaofu Wu, Yue Song, Ming Jiang, Chunming Zhao

Published Jul 1, 2010• 63 citations
Publisher

Abstract

An adaptive-normalized/offset min-sum (AN-/AO-MS) algorithm for decoding low-density parity-check (LDPC) codes is proposed. Unlike the normalized/offset min-sum (NMS/OMS) algorithm, the normalization/offset factor is adaptively adjusted according to the state of check nodes in each iteration. Simulation results show that the proposed AN-/AO-MS algorithm can perform better than the NMS/OMS algorithm while still preserving the low complexity of the min-sum algorithm.

DOI
10.1109/lcomm.2010.07.100508

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An adaptive-normalized/offset min-sum (AN-/AO-MS) algorithm for decoding low-density parity-check (LDPC) codes is proposed. Unlike the normalized/offset min-sum (NMS/OMS) algorithm, the normalization/offset factor is adaptively adjusted according to the state of check nodes in each iteration. Simulation results show that the proposed AN-/AO-MS algorithm can perform better than the NMS/OMS algorithm while still preserving the low complexity of the min-sum algorithm.
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In this paper, we present an improvement on the normalized min-sum (NMS) decoding algorithm for low density parity check codes. The modified NMS (M-NMS) algorithm introduces a more efficient adjustment for check node update computation. Taking the sub-minimum value among extrinsic information from the variable nodes into consideration, we make the correction factor varies with different iterations. Results show that, compared with standard min-sum (MS) and NMS decoding algorithms, the proposed method not only offers a better performance but also achieves a lower error floor in the high SNR region.