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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 42-577
Full Name: Yipeng Liu
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: No. 2006, Xiyuan Avenue, Western High-Tech, Chengdu
Country: CHINA
Tel: 86-1388093506
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E-mail address: liuyipeng@uestc.edu.cn
Other E-mails: liuyipeng.uestc@gmail.com
Title of the Paper: Robust Compressive Wideband Spectrum Sensing with Sampling Distortion
Authors as they appear in the Paper: Yipeng Liu and Qun Wan
Email addresses of all the authors: liuyipeng@uestc.edu.cn,wanqun@uestc.edu.cn
Number of paper pages: 10
Abstract: Too high sampling rate is the bottleneck to wideband spectrum sensing for cognitive radio (CR). As the survey shows that the sensed signal has a sparse representation in frequency domain, compressed sensing (CS) can be used to transfer the sampling burden to the digital signal processor. But the standard sparse signal recovery ways do not consider the distortion in the analogue to information converter (AIC) which randomly samples the received signal with sub-Nyquist rate. In practice various non-ideal physical effects would lead to distortion in AIC. Here we model the sampling distortion as a bounded additive noise. An anti-sampling-distortion constraint (ASDC) in the form of a mixed §¤2 and §¤1 norm is deduced from the sparse signal model with bounded sampling error. And the sparse constraint is in the form of minimization of the §¤1 norm of the estimated signal. Then we combine the sparse constraint with the ASDC to get a novel robust sparse signal recovery oper!
ator with sampling distortion. Numerical simulations demonstrate that the proposed method outperforms standard sparse wideband spectrum sensing in accuracy, denoising ability, etc.
Keywords: cognitive radio, wideband spectrum sensing, compressive sensing, sparse signal recovery, basis pursuit, analogue to information converter, sampling distortion
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