Recognition of non-drilled polar codes based on soft decision

被引：0

作者：

Wu Z. ^{[1
]}

Zhong Z. ^{[2
]}

Zhang L. ^{[1
]}

Dan B. ^{[3
]}

机构：

[1] The School of Aviation Support, Naval Aviation University, Yantai

[2] The School of Basis of Aviation Science, Naval Aviation University, Yantai

[3] The School of Coastal Defense, Naval Aviation University, Yantai

来源：

Tongxin Xuebao/Journal on Communications | 2020年 / 41卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Code length; Frozen bit position; Information bit position; Polar code; Recognition; Soft decision;

D O I：

10.11959/j.issn.1000-436x.2020254

中图分类号：

学科分类号：

摘要：

In order to solve the problem of the blind recognition of polar codes, the theorem 1 and theorem 2 were proved firstly, which reflects the relationship between length and rate of actual polar codes, and then theorem 3 which could distinguish frozen bit and information bit positions was also proved. Based on these three theorems, the codewords matrixes and Kronecker matrixes were constructed by traversing the possible code length values. Then the information bits were traversed to detect the check relationship between the codewords and the suspected dual space. In order to detect the check relationship, log likelihood ratio was introduced, based on its characteristics and optimal criteria, the code rate and information bit positions were estimated. The simulation results show that the conclusions of the three theorems are consistent with the results. At the same time, the proposed algorithm has a strong error tolerance. Under 6.5 dB and code length of 1024, the rate of recognition can reach more than 98%. © 2020, Editorial Board of Journal on Communications. All right reserved.

引用

页码：60 / 71

页数：11

共 26 条

[1]

CLUZEAU M, FINIASZ M., Recovering a code's length and synchronization from a noisy intercepted bitstream, 2009 IEEE International Symposium on Information Theory, pp. 2737-2741, (2009)

[2]

RAMABADRAN S, MADHU A, KUMAR S, Et al., Blind recognition of LDPC code parameters over erroneous channel conditions, IET Signal Processing, 13, 1, pp. 86-95, (2019)

[3]

SHARMA A, PILLAI N R., Blind recognition of parameters of linear block codes from intercepted bit stream, 2016 International Conference on Computing, Communication and Automation, pp. 1262-1266, (2016)

[4]

LIU J, ZHANG L M, ZHAN C., Blind recognition of linear block codes based on matrix analysis, Systems Engineering and Electronics, 39, 2, pp. 404-409, (2017)

[5]

BONVARD A, HOUCKE S, GAUTIER R, Et al., Classification based on Euclidean distance distribution for blind identification of error correcting codes in noncooperative contexts, IEEE Transactions on Signal Processing, 66, 10, pp. 2572-2583, (2018)

[6]

ZHENG R R, WANG L X., Recognition method of cyclic codes based on code weight distribution probability variance, Journal of Terahertz Science and Electronic Information Technology, 11, 5, pp. 792-796, (2013)

[7]

YANG X J, WEN N C., A blind method of cyclic codes based on rank function and euclide arithmetic, Journal of Circuits and Systems, 17, 5, pp. 120-129, (2012)

[8]

WU Z J, ZHANG L M, ZHONG Z G, Et al., Blind recognition of cyclic codes at low SNR, Acta Electronica Sinica, 48, 3, pp. 478-485, (2020)

[9]

ARTI D Y, SARAVANAN V, ANIMESH K., Blind recognition of binary cyclic codes from unsynchronized bitstream, IEEE Transactions on Communications, 64, 7, pp. 2693-2706, (2016)

[10]

MARAZIN M, GAUTIER R, BUREL G., Blind recovery of k/n rate convolutional encoders in a noisy environment, EURASIP Journal on Wireless Communications and Networking, 1, pp. 168-177, (2011)

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