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Journal of PLA University of Science and Technology

Uniformly reweighted iterative decoding algorithm in BICM-ID system

Duan Linli

Published Jan 1, 2014• 0 citations
OpenAlex

Abstract

The LDPC coded bit-interleaved coded modulation iterative decoding(BICM-ID)system was modeled by a normal factor graph.From the angle of the message update rule,uniformly reweighted belief propagation algorithm(URW-BP)and belief propagation algorithm(BP)are unified and interpreted as message passing algorithm by variation method.Combining the local nature of BP with the improved performance of URW-BP in graphs with cycles,the uniformly reweighted iterative decoding algorithm(URID)was derived and the impact of edge appearance probabilities(EAP)on its performance discussed. Simulation results for AWGN and Rayleigh fading channel and different modulation illustrate the performance improvement of URID compared with other iterative decoding algorithms such as BP and DifferenceMap BP(DMBP)algorithm.

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The LDPC coded bit-interleaved coded modulation iterative decoding(BICM-ID)system was modeled by a normal factor graph.From the angle of the message update rule,uniformly reweighted belief propagation algorithm(URW-BP)and belief propagation algorithm(BP)are unified and interpreted as message passing algorithm by variation method.Combining the local nature of BP with the improved performance of URW-BP in graphs with cycles,the uniformly reweighted iterative decoding algorithm(URID)was derived and the impact of edge appearance probabilities(EAP)on its performance discussed. Simulation results for AWGN and Rayleigh fading channel and different modulation illustrate the performance improvement of URID compared with other iterative decoding algorithms such as BP and DifferenceMap BP(DMBP)algorithm.
Low density parity check (LDPC) codes are one of the most popular channel codes.Based on traditional sum-product and max-product algorithms, various modified algorithms are tried to improve the performance of LDPC codes in terms of error rate, complexity and latency.Uniformly rweighted belief propagation (URW-BP) algorithm can offer better performance than traditional algorithm especially for regular LDPC codes.linear programming (LP) decoder is also competitive to traditional message passing algorithm.We describe two traditional message passing decoders, four reweighted message passing decoders based on URW-BP and LP decoder in this paper.Reweighted decoders can outperform traditional decoders especially when iteration number is limited.Considering complexity and latency, reweighted max product decoder of version 2 (R-MPD-II) is the most promising decoder.CONTENTS 4.3 Short regular LDPC codes . . . . . . . .
In this paper, we propose an improved iterative demapping/decoding method for short length low-density paritycheck (LDPC) coded bit-interleaved coded modulations (BICM). For short length LDPC, there exist cycles in the bipartite graph, thereby leading to the high correlation among the extrinsic information of bits out from BP decoder. Based on the Gaussian assumption of the extrinsic log-likelihood ratios (LLRs)delivered by BP decoder, we multiply the extrinsic output of the decoder by a scaling factor and then pass it as a priori information to the demodulator for the next iteration. In this way, we can decrease the correlation of coded bits within the symbol and thus reduce the error propagation. Simulation results show that the proposed method can achieve noticeable performance gains for short length LDPC coded BICM-ID with a minor computation complexity increase.
In this paper we propose a novel message passing algorithm which exploits the existence of short cycles to obtain performance gains by reweighting the factor graph. The proposed decoding algorithm is called variable factor appearance probability belief propagation (VFAP-BP) algorithm and is suitable for wireless communications applications with low-latency and short blocks. Simulation results show that the VFAP-BP algorithm outperforms the standard BP algorithm, and requires a significantly smaller number of iterations when decoding either general or commercial LDPC codes.
In this paper a new message passing algorithm, which takes advantage of both tree-based re-parameterization and the knowledge of short cycles, is introduced for the purpose of decoding LDPC codes with short block lengths. The proposed algorithm is called variable factor appearance probability belief propagation (VFAP-BP) algorithm and is suitable for wireless communications applications, where both good decoding performance and low-latency are expected. Our simulation results show that the VFAP-BP algorithm outperforms the standard BP algorithm and requires a significantly smaller number of iterations than existing algorithms when decoding both regular and irregular LDPC codes.
In this paper, the decoding algorithm of low-density parity-check (LDPC) codes is analyzed, and a new decoding algorithm based on the belief propagation (BP) algorithm to eliminate the influence of cycles in the factor graph is proposed. In the traditional BP algorithm, the cycles of factor graph sends message back to its source, and this decreases the decoding performance. The new algorithm records each cycle's path and length of each node, and cuts off the path by which message is propagated when the message comes back. It can advance the decoding performance by protect the message of good quality be propagated as widely as possible. Our results of simulation show that the performance of new algorithm is not worse than that of traditional BP algorithm in the low SNR channel and the new algorithm significantly outperform traditional BP algorithm in good channel condition.
A novel belief propagation(BP) decoding algorithm for convolutional low-density parity-check codes is proposed.The proposed algorithm raises the efficiency of updating the variable information by applying feedback information at each decoding iteration and employs the weighting factor to reduce the error propagation caused by the cycles in the Tanner graph,thus yielding a faster convergence of the decoding.Simulation results show that an error performance better than that of the existing belief propagation algorithm can be achieved,while the 5/8 decoding delay and the computation complexity are effectively reduced.Compared with the existing BP,the proposed algorithm achieves a gain of 0.16dB at the BER of 10-6 with the same number of iterations.