Compressed sensing based deconvolution algorithm for time-domain UWB channel modeling  

作　　者：LI De-jian LI Bin ZHOU Zheng ZHAI Shi-jun 

机构地区：[1]Key Laboratory of Universal Wireless Communications,Ministry of Education,Beijing University of Posts and Telecommunications,Beijing 100876,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2012年第1期62-68,共7页中国邮电高校学报（英文版）

基　　金：supported by Important National Science & Technology Specific Projects (2009ZX03006-009);the MIKE (The Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2011-C1090-1111-0007);the BUPT excellent Ph.D.students foundations (CX201122)

摘　　要：Extracting the parameters of the multipath with high accuracy can be achieved by using high-resolution algorithm for time-domain ultra wideband （UWB） channel modeling. The CLEAN algorithm has been used as such a high-resolution algorithm for UWB time-domain characterization. This paper presents a compressed sensing （CS） based high-resolution deconvolution algorithm for time-domain UWB channel modeling. UWB wireless channels are a prime example of long and sparse channel impulse response （CIR）. Furthermore, the dictionary of parameterized waveforms that closely matches the waveform of multipath leads to that the UWB channel measurement signal is more compactly represented. By adjusting the parameter of dictionary, CIRs of different resolutions can be obtained. The matching pursuit （MP） algorithm is used as the signal reconstruction method for CS and outputs the CIR directly. We also demonstrated that if the dictionary of CS is designed specifically, MP is an equivalent of single template CLEAN. Finally, the computation complexity of CS-MP is analyzed and comparison of MP and CLEAN is performed. Simulation results show that compared to CLEAN, the proposed CS-MP deconvolution algorithm can achieve a comparable performance with much fewer samplings.Extracting the parameters of the multipath with high accuracy can be achieved by using high-resolution algorithm for time-domain ultra wideband （UWB） channel modeling. The CLEAN algorithm has been used as such a high-resolution algorithm for UWB time-domain characterization. This paper presents a compressed sensing （CS） based high-resolution deconvolution algorithm for time-domain UWB channel modeling. UWB wireless channels are a prime example of long and sparse channel impulse response （CIR）. Furthermore, the dictionary of parameterized waveforms that closely matches the waveform of multipath leads to that the UWB channel measurement signal is more compactly represented. By adjusting the parameter of dictionary, CIRs of different resolutions can be obtained. The matching pursuit （MP） algorithm is used as the signal reconstruction method for CS and outputs the CIR directly. We also demonstrated that if the dictionary of CS is designed specifically, MP is an equivalent of single template CLEAN. Finally, the computation complexity of CS-MP is analyzed and comparison of MP and CLEAN is performed. Simulation results show that compared to CLEAN, the proposed CS-MP deconvolution algorithm can achieve a comparable performance with much fewer samplings.

关 键 词：compressed sensing DECONVOLUTION channel modeling matching pursuit UWB 

分 类 号：TN957.52[电子电信—信号与信息处理] TU312.1[电子电信—信息与通信工程]