Probabilistic greedy pursuit for streaming compressed spectrum sensing

被引:0
|
作者
Lu Y. [1 ]
Guo W.-B. [1 ]
Wang X. [1 ]
Wang W.-B. [1 ]
机构
[1] Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications
来源
Journal of China Universities of Posts and Telecommunications | 2011年 / 18卷 / 05期
关键词
cognitive radio; probabilistic greedy pursuit; streaming compressed sensing; support confidence coefficient; wide-band spectrum sensing;
D O I
10.1016/S1005-8885(10)60097-0
中图分类号
学科分类号
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. © 2011 The Journal of China Universities of Posts and Telecommunications.
引用
收藏
页码:15 / 21
页数:6
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