Recently, non-binary low-density parity-check (NB-LDPC) codes starts to show their superiority in achieving significant coding gains when moderate codeword lengths are adopted. However, the overwhelming decoding compl...
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Recently, non-binary low-density parity-check (NB-LDPC) codes starts to show their superiority in achieving significant coding gains when moderate codeword lengths are adopted. However, the overwhelming decoding complexity keeps NB-LDPC codes from being widely employed in modern communication devices. This paper proposes a hybrid message-passing decoding algorithm which consumes very low computational complexity. It achieves competitive error performance compared with conventional Min-max algorithm. Simulation result on a (255,174) cyclic code shows that this algorithm obtains at least 0.5 dB coding gain over other state-of-the-art low-complexity NB-LDPC decoding algorithms. A partial-parallel NB-LDPC decoder architecture for cyclic NB-LDPC codes is also developed based on this algorithm. Optimization schemes are employed to cut off hard decision symbols in RAMs and also to store only part of the reliability messages. In addition, the variable node units are redesigned especially for the proposed algorithm. Synthesis results demonstrate that about 24.3% gates and 12% memories can be saved over previous works.
Non-binary low-density parity-check (NB-LDPC) codes can achieve better error-correcting performance than their binary counterparts at the cost of higher decoding complexity when the codeword length is moderate. The re...
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Non-binary low-density parity-check (NB-LDPC) codes can achieve better error-correcting performance than their binary counterparts at the cost of higher decoding complexity when the codeword length is moderate. The recently developed iterative reliability-based majority-logic NB-LDPC decoding has better performance-complexity tradeoffs than previous algorithms. This paper first proposes enhancement schemes to the iterative hard reliability-based majority-logicdecoding (IHRB-MLGD). Compared to the IHRB algorithm, our enhanced (E-) IHRB algorithm can achieve significant coding gain with small hardware overhead. Then low-complexity partial-parallel NB-LDPC decoder architectures are developed based on these two algorithms. Many existing NB-LDPC code construction methods lead to quasi-cyclic or cyclic codes. Both types of codes are considered in our design. Moreover, novel schemes are developed to keep a small proportion of messages in order to reduce the memory requirement without causing noticeable performance loss. In addition, a shift-message structure is proposed by using memories concatenated with variable node units to enable efficient partial-parallel decoding for cyclic NB-LDPC codes. Compared to previous designs based on the Min-max decoding algorithm, our proposed decoders have at least tens of times lower complexity with moderate coding gain loss.
Non-binary low-density parity-check (NB-LDPC) codes usually exhibit much better performance than their binary counterparts. Among NB-LDPC decoding algorithms, the iterative reliability-based majority-logicdecoding (M...
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Non-binary low-density parity-check (NB-LDPC) codes usually exhibit much better performance than their binary counterparts. Among NB-LDPC decoding algorithms, the iterative reliability-based majority-logicdecoding (MLGD) algorithms are attractive for their low computation complexity, at the cost of performance degradation. In this brief, based on the improved iterative soft reliability-based (IISRB)-MLGD algorithm, we propose a clipped-modified (CM)-IISRB algorithm, which achieves better decoding performance with lower computational complexity. First, two modifications are introduced to the IISRB algorithm, which considerably reduces the decoding complexity with negligible performance loss. Second, an unsaturated-clipping method that facilitates significant performance improvement is presented. Simulation results show that the new algorithm outperforms the IISRB by about 0.2dB for the 256-ary (255, 175) example code. Moreover, based on a new storage reduction method, an optimized architecture is developed for the CM-IISRB algorithm. Synthesis results demonstrate that the proposed decoder can achieve very low hardware complexity, comparable to that of the iterative hard reliability-based (IHRB) decoder.
In this paper, a new low-complexity gradient-descent based iterativemajority-logic decoder (GD-MLGD) is proposed for decoding One-Step majority-logic Decodable (OSMLD) codes. We give a formulation of the decoding pro...
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In this paper, a new low-complexity gradient-descent based iterativemajority-logic decoder (GD-MLGD) is proposed for decoding One-Step majority-logic Decodable (OSMLD) codes. We give a formulation of the decoding problem of binary OSMLD codes, as a maximization problem of a derivable objective function. The optimization problem is solved using a pseudo gradient-descent algorithm, which performs iteratively an update towards the optimal estimated codeword been transmitted, based on the first-order partial derivatives of each variable calculated in the previous iteration. The proposed decoding scheme achieves a fast convergence to an optimum codeword compared to other decoding techniques reviewed in this paper, at the cost of lower computational complexity. The quantized version (QGD-MLGD) is also proposed in order to further reduce the computational complexity. Simulation results show that the proposed decoding algorithms outperform all the existing majority-logicdecoding schemes, and also various gradient-descent based bit-flipping algorithms, and performs nearly close to the belief propagation sum-product (BP-SP) decoding algorithm of LDPC codes, especially for high code lengths, providing an efficient trade-off between performance and decoding complexity. Moreover, the proposed quantized algorithm has shown to perform better than all the existing decoding techniques. The proposed decoding algorithms have shown to be suitable for ultra reliable, low latency and energy-constrained communication systems where both high performances and low-complexity are required. (C) 2020 Elsevier B.V. All rights reserved.
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