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http://dx.doi.org/10.3837/tiis.2018.08.011

A Weighted Block-by-Block Decoding Algorithm for CPM-QC-LDPC Code Using Neural Network  

Xu, Zuohong (College of Electronic Science and Engineering, National University of Defense Technology)
Zhu, Jiang (College of Electronic Science and Engineering, National University of Defense Technology)
Zhang, Zixuan (College of Computer, National University of Defense Technology)
Cheng, Qian (College of Electronic Science and Engineering, National University of Defense Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.8, 2018 , pp. 3749-3768 More about this Journal
Abstract
As one of the most potential types of low-density parity-check (LDPC) codes, CPM-QC-LDPC code has considerable advantages but there still exist some limitations in practical application, for example, the existing decoding algorithm has a low convergence rate and a high decoding complexity. According to the structural property of this code, we propose a new method based on a CPM-RID decoding algorithm that decodes block-by-block with weights, which are obtained by neural network training. From the simulation results, we can conclude that our proposed method not only improves the bit error rate and frame error rate performance but also increases the convergence rate, when compared with the original CPM-RID decoding algorithm and scaled MSA algorithm.
Keywords
CPM-QC-LDPC code; CPM-RID decoding algorithm; neural network; weights; bit error rate; frame error rate; convergence rate;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 R.G. Gallager, "Low density parity-check codes," IEEE Trans. Inf. Theory, vol. 8, no. 1, pp. 21-28, January, 1962.   DOI
2 S. Lin, "Capacity-approaching low-density parity-check codes: recent developments and applications," in Proc. of 2013 Workshop on Coding and Information Theory, January 19-20, 2013.
3 I. Tsatsaragkos and V. Paliouras, "A reconfigurable LDPC decoder optimized for 802.11n/ac applications," IEEE Transactions on Very Large Scale Integration Systems, vol. PP, no. 99, pp. 1-14, September, 2017.
4 I.E. Bocharova, B.D. Kudryashov, V. Skachek and Y. Yakimenka, "Average spectra for ensembles of LDPC codes and applications," in Proc. of IEEE International Symposium on Information Theory, pp. 361-365, June 25-30, 2017.
5 Y.Y. Tai, L. Lan, L. Zeng, S. Lin and K.A.S. Abdel-Ghaffar, "Algebraic construction of quasi-cyclic ldpc codes for the awgn and erasure channels," IEEE Trans. Commun., vol. 54, pp. 1765-1774, October, 2006.   DOI
6 J. Li, K. Liu, S. Lin and K.A.S. Abdel-Ghaffar, "Quasi-cyclic LDPC codes on two arbitrary sets of a finite field," in Proc. of IEEE International Symposium on Information Theory, pp. 2454-2458, June 29- July 4, 2014.
7 Keol Cho and Ki-Seok Chung, "Self-adaptive termination check of min-sum algorithm for LDPC decoders using the first two minima," KSII Transactions on Internet and Information Systems, vol. 11, no. 4, pp. 1987-2001, April, 2017.   DOI
8 J. Xu and K. Zhang, "A low-complexity CLSIC-LMMSE-based multi-user detection algorithm for coded MIMO systems with high order modulation," KSII Transactions on Internet and Information Systems, vol. 11, no. 4, pp. 1954-1971, April, 2017.   DOI
9 Z.X. Liu, G.X. Kang, Z.W. Si and N.B. Zhang, "Performance improvement of iterative demodulation and decoding for spatially coupling data transmission by joint sparse graph," KSII Transactions on Internet and Information Systems, vol. 10, no. 12, pp. 5964-5984, December, 2016.
10 J. Kang, Q. Huang, L. Zhang, B. Zhou and S. Lin, "Quasi-cyclic ldpc codes: an algebraic construction," IEEE Trans. Commun., vol. 58, pp. 1383-1396, May, 2010.   DOI
11 K. Liu, S. Lin and K.A.S. Abdel-Ghaffar, "A revolving iterative algorithm for decoding algebraic quasi-cyclic LDPC code," IEEE Trans. Commun., vol. 61, pp. 4816-4827, October, 2013.   DOI
12 D. Wang, L. Wang, X. Chen, A. Fei, C. Ju and Z. Wang, "Construction of QC-LDPC codes based on pre-masking and local optimal searching," IEEE Communication Letters, vol. PP, pp. 1-1, September, 2017.
13 L. Kong, L. He, P. Chen, G. Han and F. Yang, "Protograph based quasi-cyclic LDPC coding for ultra-high density magnetic recording channels," in Proc. of 2015 IEEE International Magnetics Conference, May 11-15, 2015.
14 J. Li, K. Liu, S. Lin and K.A.S. Abdel-Ghaffar, "Algebraic quasi-cyclic ldpc codes: construction, low error-floor, large girth and a reduced-complexity decoding scheme," IEEE Trans. Commun., vol.62, pp. 2626-2637, July, 2014.   DOI
15 S. Lin, K. Liu, J. Li and K.A.S. Abdel-Ghaffar, "A reduced-complexity iterative scheme for decoding quasi-cyclic low-density parity-check codes," in Proc. of 48th Annual Asilomar Conference on Signals, Systems and Computers, pp. 119-125, November 2-5, 2014.
16 J. Li, K. Liu, S. Lin and K.A.S. Abdel-Ghaffar, "Decoding of quasi-cyclic LDPC codes with section-wise cyclic structure," in Proc. of Information Theory and Applications Workshop, pp. 1-10, February 9-14, 2014.
17 E. Nachmani, E. Marciano, D. Burshtein and Y. Beery, "RNN decoding of linear block codes," Available online: http://arxiv.org/pdf/1702.07560.
18 W.R. Caid and R.W. Means, "Neural network error correcting decoders for block and convolutional codes," in Proc. of IEEE Global Telecommunications Conference, pp. 1028-1031, December 2-5, 1990.
19 A. Hamalainen and J. Henriksson, "A recurrent neural decoder for convolutional codes," in Proc. of IEEE International Conference on Communications, pp. 1305-1309, June 6-10, 1999.
20 E. Nachmani, Y. Beery and D. Burshtein, "Learning to decode linear codes using deep learning," Available online: https://arxiv.org/pdf/1607.04793.
21 A.R. Karami, M.A. Attar and H. Tavakoli, "Multi-layer perceptron neural networks decoder for LDPC codes," in International Conference on Wireless Communications, Networking and Mobile Computing, pp. 476-479, September 24-26, 2009.
22 T. Gruber, S. Cammerer, J. Hoydis and S.T. Brink, "On deep learning-based channel decoding," in Proc. of 51st Annual Conference on Information Sciences and Systems, pp. 1-6, March 22-24, 2017.
23 J. Bergstra, R. Bardenet, Y. Bengio and B. Kegl, "Algorithms for hyper-parameter optimization," in Proc. of 25th Annual Conference on Neural Information Processing Systems, pp. 2546-2554, December 17-25, 2011.