Journal on Communications ›› 2018, Vol. 39 ›› Issue (9): 43-48.doi: 10.11959/j.issn.1000-436x.2018153

• 5G and Cognitive and Cooperative Network • Previous Articles     Next Articles

EM-based blind LDPC identification in multipath channels

Yu LIU,Fanggang WANG,Jingwen ZHANG,Bo AI,Zhangdui ZHONG   

  1. State Key Lab of Rail Traffic Control and Safety,Beijing Jiaotong University,Beijing 100044,China
  • Revised:2018-08-02 Online:2018-09-01 Published:2018-10-19
  • Supported by:
    The Fundamental Research Funds for the Central Universities(2018JBM078);The National Natural Science Foundation of China(61571034);The National Natural Science Foundation of China(61725101);The Natural Science Foundation of Beijing(4182051);The Natural Science Foundation of Beijing(L172020);The Key Laboratory of Universal Wireless Communications,Ministry of Education,P.R.China(KFKT-2018102);The Major Projects of Beijing Municipal Science and Technology Commission Under Grant(Z181100003218010)

Abstract:

As the advent of cognitive radios,blind encoder identification has attracted increasingly attentions since it plays an important role.The existing works mainly focus on additive white Gaussian noise (AWGN) channel,while the blind identification in multipath scenarios has not been sufficiently investigated.Considering the blind low density parity-check (LDPC) codes identification in the presence of unknown multipath fading channel,a likelihood-based classifier was proposed using the expectation maximization (EM) algorithm to obtain the maximum likelihood estimates of the unknown parameters.Then,an average log-likelihood ratio (LLR) estimator was adopted to classify the unknown encoder.Numerical results show that the proposed algorithm provides promising identification performance in multipath channels,especially in the low signal-to-noise ratio region.

Key words: cognitive radios, multipath fading channel, blind encoder identification, LDPC, EM algorithm

CLC Number: 

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