ZHANG Zhengyu, LOU Jinming, JIN Mengdi, YAO Yuan, ZHU Jingguo. Application of Maximum Entropy Theorem in Channel Estimation[J]. Chinese Journal of Electronics, 2020, 29(2): 361-370. doi: 10.1049/cje.2020.01.015
Citation: ZHANG Zhengyu, LOU Jinming, JIN Mengdi, YAO Yuan, ZHU Jingguo. Application of Maximum Entropy Theorem in Channel Estimation[J]. Chinese Journal of Electronics, 2020, 29(2): 361-370. doi: 10.1049/cje.2020.01.015

Application of Maximum Entropy Theorem in Channel Estimation

doi: 10.1049/cje.2020.01.015
Funds:  This work is supported by the National Key Research and Development Project (No.2017YCF0803404).
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  • Corresponding author: ZHU Jingguo (corresponding author) was born in 1977. He is a researcher of Chinese Academy of Sciences, member of Photoelectric Professional Committee of Aerospace Society. He is mainly engaged in the research of novel laser detection theory, ultra-wideband wireless communication system, as well as the application and development of laser detection technology. (Email:zhujingguo@ime.ac.cn)
  • Received Date: 2019-05-28
  • Rev Recd Date: 2019-08-11
  • Publish Date: 2020-03-10
  • Scholars have been highly concerned with the blind channel estimation of multi-carrier modulation transmission systems, and the decoding process of block codes is usually closely related to channel parameters. Therefore, the accurate estimation of channel parameters is an important method to ensure communication accuracy. According to the transmission characteristics of multi-carrier modulated transmission channels, this paper uses the maximum likelihood theorem and the maximum entropy theorem to put forward a blind channel estimation method based on the proposed received signals. In order to verify the effect of this method, this research utilizes the BP decoding algorithm, which is used in LDPC coding, to calculate the symbol error rate and analyze the estimated effect of the transmission system. The simulation results show that the proposed method can estimate channel parameters effectively, and that the symbol error rate of LDPC decoding is almost similar to that of non-blind channel estimation. This implies that the proposed channel estimation method can effectively improve both channel utilization and transmission efficiency.
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  • Chen Zhi, Wang Yan and Cai Min, “An improved algorithm based on DFT channel estimation in OFDM”, Journal of University of South China (Science and Technology), Vol.32, No.3, pp.51-53, 2018.
    Guan Rui, “Research on sim-OFDM scheme for visible light communications”, Ph.D. Thesis, Nanjing: Southeast University, 2018.
    Qi Zhen-hao, “Research on channel estimation in wavelet packet multi-carrier modulation system”, Ph.D. Thesis, Tianjin University, 2006. (in Chinese)
    Tang Rui, “Research on encoding and decoding algorithm of LDPC code”, Ph.D. Thesis, Chengdu: University of Electronic Science and Technology, 2018. (in Chinese)
    Zhou Hua, Zhao Liang and Li Cheng-qian, “Two correction factors based residual belief propagation algorithm for LDPC codes”, Modern Electronics Technique, Vol.42, No.11, pp.15-18 and 23, 2019. (in Chinese)
    Saeed Gazor, Mostafa Derakhtian and Ali Akbar Tadaion, “Computationally efficient maximum likelihood sequence estimation and activity detection for MPSK signals in unknown flat fading channels”, IEEE Signal Processing Letters, Vol.17, No.10, pp.1-5, 2010.
    Tian Feng, Zhang Jun, Ran You-hua, et al., “Model comparison of mountain torrent disaster risk assessment in different spatial scale”, Arid Land Geography, Vol.42, No.3, pp.560-569, 2019.
    ZHOU Yang, YI Yu-jun and YANG Yu-feng, “Predicting geographical distributions of homonoia riparia Lour by using maximum entropy”, Water Resources and Hydropower Engineering, Vol.50, No.5, pp.73-81, 2019.
    LI Zheng-liang, ZU Yun-fei, FAN Wen-liang, et al., “Reliability analysis of multi-components in structural system based on the adaptive point estimate method and the principle of maximum entropy”, Engineering Mechanics, Vol.36, No.5, pp.166-175, 2019.
    Guo Yan-bing, Miao Ling-juan and Zhang Xi, “Spoofing detection and mitigation in a multi-correlator GPS receiver based on the maximum likelihood principle”, Sensors (Basel, Switzerland), Vol.19, No.1, pp.1-17, 2018.
    Zhao Shou-jiang, Liu Qiao-jing and Chen Ting, “On the large deviation principle for maximum likelihood estimator of α-brownian bridge”, Statistics and Probability Letters, Vol.138, pp.1-17, 2018.
    QIU Shang-fei, XUE Lun-sheng and CHEN Xi-hong, “An improved channel estimation method for OFDM /OQAM system”, Radio Engineering, Vol.48, No.11, pp.925-929, 2018.
    Jia Ke-jun, Hao Li and Zhang Shou-qin, “Design performance analysis of asymmetrically clipped optical multi-carrier code division multiple access system in visible light communications”, Acta Optica Sinica, Vol.39, No.2, pp.31-42, 2019.
    Song Tie-cheng, You Xiao-hu and Shen Lian-feng, “Highspeed single-carrier system based on signal processing method of OFDM system”, Journal of Southeast University, Vol.32, No.2, pp.151-155, 2002.
    Zhou Yue-hai, Cao Xiu-ling and Chen Dong-sheng, “Joint sparse recovery estimation for long delay extended underwater acoustic channel”, Journal of Communications, Vol.37, No.2, pp.165-172, 2016.
    Zhang Qing-hui and Feng Bin, “Design of blind image perception system based on edge detection”, Transducerand Microsystem Technologies, Vol.38, No.6, pp112-114, 2019.
    Guo Zheng, Yan Du-feng, Xu Li-jun, et al., “Frame synchronization for underwater acoustic communication based on maximum likelihood estimation”, Acta Acustica, Vol.43, No.3, pp.283-290, 2018.
    Ge Yu-feng and Wang Biao, “Dynamic OMP channel tracking algorithm for OFDM underwater acoustic communication systems”, Technical Acoustics, Vol.38, No.1, pp.53-57, 2019.
    Ye Xin-rong, Zhu Wei-ping and Meng Qing-min, “Sparse channel estimation method for OFDM systems based on SAMP reconstruction algorithm”, Signal Processing, Vol.28, No.3, pp.92-96, 2012.
    Bao Ren-zhi, “Research on TDOA-based underwater source localization under multipath condition”, Ph.D. Thesis, Guangzhou: South China University of Technology, 2018.
    Zhang Xiao-dong, Dong Wei-guang and Guo Jun-feng, “Compressed sensing wind power converter voltage signal compression method based on transform”, Journal of Guangxi University (Natural Science), Vol.46, No.6, pp.55-62, 2016.
    LIU Zheng and LIU Ben-yong, “Scale-invariant feature transform algorithm based on image depth information, erroneous match point pair elimination”, Journal of Computer Application, Vol.34, No.12, pp54-59, 2019.
    Hang LIU, Guo Wen-bin and Sun Zhuo, “Adaptive kalman filtered compressive sensing for streaming signals”, IEEE 78th Vehicular Technology Conference, pp.1-5, 2013.
    Yu Li-jun and Cheng Yao-rong, “Study of optimal fitting method for probability density function of traffic flow”, Journal of Changsha Communications, Vol.18, No.2, pp.80-82, 2002.
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