Channel estimation for backscatter communication systems with retrodirective arrays

被引:0
|
作者
Mu, Yunping [1 ]
Yao, Chaochao [2 ]
Fan, Dian [3 ]
Xu, Yongjun [4 ]
Wang, Gongpu [1 ]
Milosevic, Marjan [5 ]
Ai, Bo [6 ,7 ]
机构
[1] Beijing Jiaotong Univ, Minist Educ, Engn Res Ctr Network Management Technol High Speed, Sch Comp & Informat Technol, Beijing, Peoples R China
[2] Ant Financial Serv Grp, Shanghai, Peoples R China
[3] China Acad Informat & Commun Technol, Beijing 100191, Peoples R China
[4] Chongqing Univ Posts & Telecommun, Sch Commun & Informat Engn, Chongqing, Peoples R China
[5] Univ Kragujevac, Fac Tech Sci Cacak, Cacak, Serbia
[6] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
[7] Beijing Jiaotong Univ, Beijing Engn Res Ctr High Speed Railway Broadband, Beijing, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
AWGN channels; backscatter; Bayes methods; channel estimation; internet of things; PERFORMANCE;
D O I
10.1049/cmu2.12777
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Backscatter communications, which originated from World War II, have been widely applied in the logistics domain, and recently attract emerging interest from both academic and industrial circles. Here, the backscatter communication systems equipped with retrodirective arrays that can re-transmit the impinging signals back toward the direction of incidence are studied so as to reduce the power loss of the signals. Specifically, the authors consider the tag is equipped with retrodirective arrays to improve reliability and enhance communication range. The probability density function of channel coefficients is then derived. Next, a channel estimator based on Bayesian theory is proposed to acquire the modulus values of channel parameters and calculate its Bayesian Cramer-Rao Lower Bound. Finally, simulation results are provided to corroborate these theoretical studies. Here, the authors consider the tag is equipped with retrodirective arrays to improve reliability and enhance communication range. The probability density function of channel coefficients is then derived. Next, a channel estimator based on Bayesian theory is proposed to acquire the modulus values of channel parameters and calculate its Bayesian Cramer-Rao Lower Bound. image
引用
收藏
页码:671 / 678
页数:8
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