天基信息传输高效低复杂度LDPC译码算法研究

doi:10.12382/bgxb.2022.1044

摘要/Abstract

摘要：

军事卫星通信由于需满足信息实时性、传输速率高、通信容量大以及符合星间链路信道的时变特性等要求,通常采用高编码增益、高吞吐量的信道编码方案。低密度奇偶校验(Low-Density Parity-Check, LDPC)码由于具备接近Shannon极限的优异纠错性能和可并行计算的特性成为卫星通信主导信道编码标准之一。目前卫星通信接收机的译码器模块设计仍存在诸如无法实时在线判断迭代停止、系统吞吐量受限、大量判决电路影响核心译码电路的低功耗和实时性等问题。考虑上述问题,以因子图模型为基础,针对空间数据系统咨询委员会(Consultative Committee for Space Data Systems, CCSDS)标准深空通信码型,将校验节点归一化满足概率进化图案与LDPC译码器状态紧密耦合,给出可实时在线判断迭代停止的最优停止准则,实现高性能、低复杂度的停止准则译码算法设计。当优先考虑高吞吐量时,误码率(Bit Error Rate, BER)性能退化0.13dB,中低信噪比平均迭代次数(Average Number of Iteration, ANI)降低50%以上;当优先考虑纠错性能时,BER性能仅退化0.02dB,同时大幅降低ANI。该译码算法为高效低复杂度LDPC译码器设计提供有效解决方案。

关键词: 卫星通信, 低密度奇偶校验码, 因子图模型, 停止准则, 迭代消息传递算法

Abstract:

Military satellite communication is required to fulfill the need of real-time information transmission, high transmission rate, large communication capacity and adaptability to the time-varying characteristics of inter-satellite links, so the channel coding schemes with high coding gain and high throughput are adopted. Low-density parity-check (LDPC) code has become one of the main channel coding standards for its excellent error-correction performance which can approximately achieve the Shannon limit and its parallel computing capability. However, there are still some problems in its decoder module design of satellite communication receiver, such as failure of real-time online stopping judgement on iterative decoding, limited system throughput, and excessive decision circuits that reduce the power and real-time performance of decoding circuit. This paper adopts the CCSDS coding standards for deep space communication, and proposes the design of an iterative decoding stopping criterion algorithm based on a factor graph model. The algorithm tightly couples the evolution of normalized syndrome satisfaction probability with the state of LDPC decoder, so as to achieve high performance and low complexity. The results show that, when high throughput is preferentially considered, the bit error rate (BER) performance is degraded by 0.13dB, and meanwhile the average number of iterations (ANI) in medium and low SNRs is reduced by more than 50%; when error-correcting performance is preferentially considered, BER performance is only degraded by 0.02dB. Whereas, the ANI is greatly reduced. The proposed algorithm serves as an effective solution for the design of low complexity and high efficiency LDPC decoder.

Key words: satellite communication, low-density parity-check code, factor graph model, stopping criterion, iterative message-passing algorithm

中图分类号:

TN911.22

周可歆, 丁旭辉, 吕德东, 卜祥元, 安建平. 天基信息传输高效低复杂度LDPC译码算法研究[J]. 兵工学报, 2024, 45(4): 1176-1185.

ZHOU Kexin, DING Xuhui, LÜ Dedong, BU Xiangyuan, An Jianping. Research on LDPC Decoding Algorithm with High Efficiency and Low Complexity for Space-based Information Transmission[J]. Acta Armamentarii, 2024, 45(4): 1176-1185.

图/表 10

图1 LDPC因子图模型

Fig.1 Factor graph model of LDPC

图2 添加停止准则的LDPC译码因子图模型

Fig.2 Factor graph model of LDPC decoding with stop criterion

图3 可译码型情况下p(G(·))进化图谱

Fig.3 Evolution of p(G(·)) in the case of decodable data type

图4 不同类型数据帧的p(G(·))进化图谱

Fig.4 Evolution of p(G(·)) of different data frames

图5 不同信噪比下不同码型的概率统计

Fig.5 Proportion of different data frames with different signal-to-noise ratios

图6 CCSDS深空通信LDPC码型的停止准则因子图模型

Fig.6 Factor graph model of LDPC decoding with stop criterion for CCSDS deep space communication

图7 LDPC译码器整体系统架构设计

Fig.7 Hardware architecture of LDPC decoder

图8 不同参数对LDPC译码BER、FER性能影响

Fig.8 The effect of parameters on BER and FER performances

图9 不同参数对LDPC译码BER、ANI性能影响

Fig.9 The effect of parameters on BER and ANI performances

图10 最优停止准则译码算法ANI性能对比结果

Fig.10 ANI performance of optimal stop criterion decoding algorithm

参考文献 25

[1]	尹江丽, 王莉. 军用卫星通信系统效能评估指标体系研究[J]. 兵工自动化, 2008, 27(6):9-11.
	YIN J L, WANG L. Research on effectiveness evaluation index system of military satellite communication system[J]. Ordnance Industry Automation, 2008, 27(6):9-11. (in Chinese)
[2]	黄惠明, 常呈武. 天地一体化天基骨干网络体系架构研究[J]. 中国电子科学研究院学报, 2015, 10(5):460-467, 491.
	HUANG H M, CHANG C W. Architecture research on space-based backbone network of space-ground integrated networks[J]. Journal of China Academy of Electronics and Information Technology, 2015, 10(5):460-467, 491. (in Chinese)
[3]	宋炜琳, 杨道宁. 基于星间链路的卫星导航系统星地业务信息传输规划调度方法研究[J]. 兵工学报, 2019, 40(8):1627-1633. doi: 10.3969/j.issn.1000-1093.2019.08.010
	SONG W L, YANG D N. Research on GNSS satellite-ground service information transmission scheduling method based on inter-satellite link[J]. Acta Armamentarii, 2019, 40(8):1627-1633. (in Chinese) doi: 10.3969/j.issn.1000-1093.2019.08.010
[4]	朱立东. 国外军事卫星通信发展及新技术综述[J]. 无线电通信技术, 2016, 42(5):1-5, 34.
	ZHU L D. Review on development and new technologies of military satellite communications aboard[J]. Radio Communications Technology, 2016, 42(5):1-5, 34. (in Chinese)
[5]	胡君. 卫星移动通信信道研究及性能仿真[D]. 成都: 电子科技大学, 2005.
	HU J. Research and performance simulation of mobile satellite communication channel model[D]. Chengdu: University of Electronic Science and Technology of China, 2005. (in Chinese)
[6]	MACKAY D J C, NEAL R M. Near Shannon limit performance of low density parity check codes[J]. Electronics Letters, 1996, 32(18):1645-1646.
[7]	SIPSER M, SPIELMAN D A. Expander codes[J]. IEEE Transactions on Information Theory, 1996, 42(6): 1710-1722.
[8]	DELSARTE P. On subfield subcodes of modified Reed-Solomon codes (Corresp.)[J]. IEEE Transactions on Information Theory, 1975, 21(5):575-576.
[9]	BERROU C,GLAVIEUX A and THITIMAJSHIMA P. Near Shannon limit error-correcting coding and decoding: Turbo-codes[C]// Proceedings of 1993 IEEE International Conference on Communications. Geneva, Switzerland: IEEE, 1993:1064-1070.
[10]	BERROU C, GLAVIEUX A. Near optimum error correcting coding and decoding: turbo-codes[J]. IEEE Transactions on Communications, 1996, 44(10): 1261-1271.
[11]	GALLAGER R. Low-density parity-check codes[J]. IRE Transactions on Information Theory, 1962, 8(1): 21-28.
[12]	杨友福, 刘建伟, 张其善, 等. 卫星信道编码技术及新发展[J]. 通信技术, 2008, 41(7): 30-33, 36.
	YANG Y F, LIU J W, ZHANG Q S, et al. Technology and development of satellite channel coding[J]. Communications Technology, 2008, 41(7):30-33, 36. (in Chinese)
[13]	ÁLVAREZ Á, FERNANDEZ V, MATUZ B. An efficient NB-LDPC decoder architecture for space telecommand links[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2021, 68(4): 1213-1217.
[14]	DING X H, AN J P, ZHAO Z, et al. Low-density parity-check coded direct sequence spread spectrum receiver based on analog probabilistic processing[J]. IEEE Transactions on Vehicular Technology, 2021, 70(7):6355-6370.
[15]	JAYASOORIYA S, SHIRVANIMOGHADDAM M, ONG L, et al. A new density evolution approximation for LDPC and multi-edge type LDPC codes[J]. IEEE Transactions on Communications, 2016, 64(10): 4044-4056.
[16]	ASHIKHMIN A, KRAMER G and BRINK S T. Extrinsic information transfer functions: model and erasure channel properties[J]. IEEE Transactions on Information Theory, 2004, 50(11): 2657-2673.
[17]	YUAN B, PARHI K K. Early stopping criteria for energy-efficient low-latency belief-propagation polar code decoders[J]. IEEE Transactions on Signal Processing, 2014, 62(24): 6496-6506.
[18]	KIM T, PARK J, HEO J. Stopping criterion for LDPC decoder based on PEXIT CHART Analysis[C]// Proceedings of IEEE Wireless Communications and Networking Conference. Seoul, Korea (South): IEEE, 2020:1-6.
[19]	HAN G J, LIU X C. A unified early stopping criterion for binary and nonbinary LDPC codes based on check-sum variation patterns[J]. IEEE Communications Letters, 2010, 14(11): 1053-1055.
[20]	MATSUMOTO W. Blind synchronization with enhanced sum-product algorithm for low-density parity-check codes[C]// Proceedings of the 5th International Symposium on Wireless Personal Multimedia Communications. Honolulu, HI, US: IEEE, 2002: 966-970.
[21]	XIA T, WU H C, JIANG H. New stopping criterion for fast low-density parity-check decoders[J]. IEEE Communications Letters, 2014, 18(10): 1679-1682.
[22]	LOELIGER H A. An introduction to factor graphs[J]. IEEE Signal Processing Magazine, 2004, 21:28-41.
[23]	WIBERG N, LOELIGER H A, KOTTER R. Codes and Iterative Decoding on General Graphs[C]// Proceedings of 1995 IEEE International Symposium on Information Theory. Whistler, Canada: IEEE, 1995:468.
[24]	KSCHISCHANG F R, FREY B J. Iterative decoding of compound codes by probability propagation in graphical models[J]. IEEE Journal on Selected Areas in Communications, 1998, 16(2): 219-230.
[25]	RICHARDSON T J, URBANKE R L. The capacity of low-density parity-check codes under message passing decoding[J]. IEEE Transactions on Information Theory, 2001, 47(2): 599-618.