Probabilistic greedy pursuit for streaming compressed spectrum sensing

作     者：LU Yang GUO Wen-bin WANG Xing WANG Wen-bo 

作者机构：Key Laboratory of Universal Wireless CommunicationMinistry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2011年第18卷第5期

页      面：15-21页

核心收录：

学科分类：12[管理学] 02[经济学] 07[理学] 08[工学] 070103[理学-概率论与数理统计] 0202[经济学-应用经济学] 020208[经济学-统计学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 0835[工学-软件工程] 0714[理学-统计学（可授理学、经济学学位）] 0811[工学-控制科学与工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Fundamental Research Funds for the Central Universities(BUPT2009RC0107) the National BasicResearch Program of China(2009CB320400) the Important National Science and Technology Specific Projects(2009ZX03007-004) the Joint Funds of NSFC-Guangdong(Grant U1035001) 

主　　题：cognitive radio wide-band spectrum sensing streaming compressed sensing probabilistic greedy pursuit support confidence coefficient 

摘      要：This paper presents a probabilistic greedy pursuit （PGP） algorithm for compressed wide-band spectrum sensing under cognitive radio （CR） scenario. PGP relies on streaming compressed sensing （CS） framework, which differs from traditional CS processing way that only focuses on fixed-length signal＇s compressive sampling and reconstruction. It utilizes analog-to-information converter （AIC） to perform sub-Nyquist rate signal acquisition at the radio front-end （RF） of CR, the measurement process of which is carefully designed for streaming framework. Since the sparsity of wide-band spectrum is unavailable in practical situation, PGP introduces the probabilistic scheme by dynamically updating support confidence coefficient and utilizes greedy pursuit to perform streaming spectrum estimation, which gains sensing performance promotion progressively. The proposed algorithm enables robust spectrum estimation without the priori sparsity knowledge, and keeps low computational complexity simultaneously, which is more suitable for practical on-line applications. Various simulations and comparisons validate the effectiveness of our approach.