A Low-Computation Compressive Wideband Spectrum Sensing Algorithm Based on Multirate Coprime Sampling

被引：2

作者：

Ren, Shiyu ^{[1
]}

Zeng, Zhimin ^{[1
]}

Guo, Caili ^{[1
]}

Sun, Xuekang ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, Beijing Lab Adv Informat Networks, Beijing, Peoples R China

来源：

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2017年 / E100A卷 / 04期

关键词：

wideband spectrum sensing; multirate coprime sampling; folded spectrum; PURSUIT;

D O I：

10.1587/transfun.E100.A.1060

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Compressed sensing (CS)-based wideband spectrum sensing has been a hot topic because it can cut high signal acquisition costs. However, using CS-based approaches, the spectral recovery requires large computational complexity. This letter proposes a wideband spectrum sensing algorithm based on multirate coprime sampling. It can detect the entire wideband directly from sub-Nyquist samples without spectral recovery, thus it brings a significant reduction of computational complexity. Compared with the excellent spectral recovery algorithm, i.e., orthogonal matching pursuit, our algorithm can maintain good sensing performance with computational complexity being several orders of magnitude lower.

引用

页码：1060 / 1065

页数：6

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