Application of Bayesian Compressive Sensing in IR-UWB Channel Estimation

作     者：Song Liu Shaohua Wu Yang Li Song Liu;Shaohua Wu;Yang Li;Harbin Institute of Technology Shenzhen Graduate School

作者机构：Harbin Institute of Technology Shenzhen Graduate SchoolShenzhen 518055China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2017年第14卷第5期

页      面：30-37页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：sponsored by the National Natural Science Foundation of China(Grant Nos.61001092 61371102) 

主　　题：cluster Bayesian compressive sensing ultra wideband channel estimation 

摘      要：Due to the sparse nature of the impulse radio ultra-wideband(IR-UWB)communication channel in the time domain,compressive sensing(CS)theory is very suitable for the sparse channel estimation. Besides the sparse nature,the IR-UWB channel has shown more features which can be taken into account in the channel estimation process,such as the clustering structures. In this paper,by taking advantage of the clustering features of the channel,a novel IR-UWB channel estimation scheme based on the Bayesian compressive sensing(BCS)framework is proposed,in which the sparse degree of the channel impulse response is not required. Extensive simulation results show that the proposed channel estimation scheme has obvious advantages over the traditional scheme,and the final demodulation performance,in terms of Bit Error Rate(BER),is therefore greatly improved.