A New Way of Ultra-wideband Channel Estimation Based on Bayesian Compressive Sensing

摘要：

　　In this paper,in order to solve the problem that the sampling rate in ultra-wideband (UWB)channel estimation is too high,we discuss the applicability of Bayesian Compressive Sensing (BCS)used in UWB channel estimation.We solve the problem by using the time domain sparse of the impulse response of the UWB channel and establishing the probability model of the Compressive Sensing (CS) measurement.We accomplish the channel estimation by optimizing maximum a posteriori (MAP) of the channel.The simulation results show that the proposed scheme needs a very low sampling rate to recover the channel accurately.And the BCS algorithm has a better performance than the basis pursuit (BP) algorithm and the traditional least square (LS) algorithm in bit error rate (BER).

关键词： Channel estimation Bayesian Compressive sensing Ultra-wideband

作者: Fenlan Li Hua Wen Zhemin zhuang

作者单位: Electric Department Shantou University Shantou China,515063

会议类型: 国际会议

会议名称: the 2012 International Conference on Manufacturing Engineering and Automation (2012年制造工程与自动化国际会议(ICMEA2012))

会议地点: 广州

会议语种:英文

页码: 1334-1337

在线出版日期: 2012-11-16（万方平台首次上网日期，不代表论文的发表时间）