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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