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International Conference on Information Communication and Management (ICICM)

A Configurable Approximation Min-Sum Decoding Algorithm for Low Density Parity Check Codes

Ruizhen Wu, Lin Wang, Mingming Wang

Published Aug 23, 2019• 0 citations
Publisher

Abstract

A configurable approximation Min-sum decoding algorithm for LDPC is proposed in this paper. The degradation factor of BP to MS is found and optimized based on Jacobian Logarithm and hardware working mode. The decoding algorithm is configurable to satisfy different environment's need and will only need update the variable memory. The simulation is based on LDPC NR 3GPP 38.212 release and the comparison results showed the proposed configurable approximation Min-sum decoding algorithm have a better BER performance. The hardware of this proposed algorithm is based on Min-sum decoder and the extra cost is only a shifter and an adder besides the configurable memory.

DOI
10.1145/3357419.3357422

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A configurable approximation Min-sum decoding algorithm for LDPC is proposed in this paper. The degradation factor of BP to MS is found and optimized based on Jacobian Logarithm and hardware working mode. The decoding algorithm is configurable to satisfy different environment's need and will only need update the variable memory. The simulation is based on LDPC NR 3GPP 38.212 release and the comparison results showed the proposed configurable approximation Min-sum decoding algorithm have a better BER performance. The hardware of this proposed algorithm is based on Min-sum decoder and the extra cost is only a shifter and an adder besides the configurable memory.
A check nodes correction approximate Min-sum decoding algorithm for LDPC is proposed in this paper. The degradation factor of BP to MS is found to do expansion and optimization based on hardware working manner. The decoding algorithm summarized a correction approximate algorithm based on different SNR situations and hardware implementation. The simulation is based on LDPC NR 3GPP 38.212 release and the comparison results showed the proposed check nodes correction approximate Min-sum decoding algorithm can have a better BER and iteration time performance. The hardware of this proposed algorithm is based on Min-sum decoder and the extra cost is only a shifter and an adder besides the memory.
To improve the decoding performance of Low Density Parity Check(LDPC) code,an efficient decoding algorithm based on min-sum algorithm is proposed. The proposed algorithm analyzes the check node update equation and at the view of probability to form an approximation min-sum equation. It adopts a dynamic normalization factor to improve the decoding performance. Detailed simulation results and comparisons with Belief Propagation(BP) algorithm show that,with little decoding performance loss,the proposed algorithm not only decreases computational load,but also improves decoding efficiency.
A sectional degree match approximate Min-sum decoding algorithm for LDPC is proposed in this paper. The degradation factor from BP to MS is analyzed and a proposal to offset it, is explained, with expansion and optimization based on principles of hardware implementation. The decoding algorithm summarizes three correction approximate algorithms considering different LLR values, matrix degrees and rules of hardware implementation. Simulation is following LDPC NR 3GPP 38.212 release and the comparison results demonstrate that the proposed sectional degree match approximate Min-sum decoding algorithm has a better BER and less iteration time. The hardware implementation of this algorithm is strived from Min-Sum decoder and the extra cost is minor besides the memory.
A modified Min-Sum algorithm for low-density parity check codes is proposed in this paper. The inaccurate check node messages of the Min-Sum algorithm compared to the belief propagation (BP) algorithm are compensated by modified variable node messages, which is different from the normalized Min-Sum algorithm. The modified factor is obtained before decoding program and only one extra multiplication is needed in one cycle. So the increased complexity is fairly low. The simulation results show that the bit error rate (BER) and average number of iteration of the modified Min-Sum algorithm are very close to the BP algorithm, the modified algorithm can improve the BER performance compared to the Min-Sum algorithm while added complexity slightly.
Based on the min-sum decoding algorithm,a kind of iterative decoding algorithm for low-density parity-check(LDPC) codes,named configurable min-sum decoding algorithm(CMS),was proposed.During the horizontal step in the CMS decoding algorithm,it took a configurable optimal correction factor added the absolute minimum to replace the absolute sub-minimum so that it could omit the process of calculating the sub-minimum and simplify the complexity of decoding.Simulation results show that the CMS algorithm can achieve a performance very close to that of the MS algorithm with the optimal correction factors,making it a good candidate for practical systems.The optimal correction factors were obtained at different SNRs by Monte Carlo simulation and theoretical analysis,and the results were found to be in good agreement.
To improve performance and reduce computation complexity of the low-density parity-check (LDPC) codes, a min-sum based differential decoding algorithm is proposed. The main principle is that the messages passing in the bipartite graph of the codes are the probability differences and the updates of the check nodes adopt min sum algorithm. Simulation results show that the proposed algorithm can achieve about 0.4dB performance gain over the UMP BP-Based decoding algorithm at bit error rate (BER) of under an additive white Gaussian noise (AWGN) channel. And it can obtain good performance very close to that of the BP decoding algorithm with much lower complexity.