Novel schemes to optimize sampling rate for compressed sensing

• Published in: Journal of communications and networks Vol. 17; no. 5; pp. 517 - 524
• Main Authors: Zhang, Yifan, Fu, Xuan, Zhang, Qixun, Feng, Zhiyong, Liu, Xiaomin
• Format: Journal Article
• Language: English
• Published: Seoul Editorial Department of Journal of Communications and Networks 01.10.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); 한국통신학회
• Subjects: Algorithms; Bandwidth; Cognitive radio; Compressed sensing; compression ratio; Covariance matrices; cyclostationary detection; Heuristic algorithms; Modulation; Monitoring; Sensors; 전자/정보통신공학
• ISSN: 1229-2370; 1976-5541
• DOI: 10.1109/JCN.2015.000090

The fast and accurate spectrum sensing over an ultra-wide bandwidth is a big challenge for the radio environment cognition. Considering sparse signal feature, two novel compressed sensing schemes are proposed, which can reduce compressed sampling rate in contrast to the traditional scheme. One algorithm is dynamically adjusting compression ratio based on modulation recognition and identification of symbol rate, which can reduce compression ratio. Furthermore, without priori information of the modulation and symbol rate, another improved algorithm is proposed with the application potential in practice, which does not need to reconstruct the signals. The improved algorithm is divided into two stages, which are the approaching stage and the monitoring stage. The overall sampling rate can be dramatically reduced without the performance deterioration of the spectrum detection compared to the conventional static compressed sampling rate algorithm. Numerous results show that the proposed compressed sensing technique can reduce sampling rate by 35%, with an acceptable detection probability over 0.9.