Hybrid Smoothing Method (HSM) in Cyclostationary Signal Detection for Cognitive Radio

被引:0
|
作者
Norouzi, Mandana [1 ]
Guenther, Brent [2 ]
Wu, Zhiqiang [2 ]
Zhou, Chi [1 ]
机构
[1] IIT, Dept Elect & Comp Engn, Chicago, IL 60616 USA
[2] Wright State Univ, Dept Elect & Comp Engn, Dayton, OH 45435 USA
来源
2011 IEEE VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL) | 2011年
关键词
Cognitive radio; Spectrum sensing; Cyclostationary signal detection; Time Smoothing algorithm; Frequency Smoothing algorithm;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
One of the major challenging issues in wireless communication is spectrum scarcity. In order to better utilize the licensed spectrum, the concept of cognitive radio has been introduced in which unlicensed users (secondary users) sense the spectrum and use the available bandwidth for their own transmission. One of the methods for detecting licensed users is through cyclostationary processing, which is based on the estimation of the spectral correlation function of the received signal. In this paper a new method for the detection of licensed users is proposed. The proposed Hybrid Smoothing Method (HSM) combines pre-existing time smoothing and frequency smoothing algorithms in cyclostationary processing in a cascading format. HSM estimates the SCF of the received signal and then sets a threshold for its decision. The threshold to switch from frequency smoothing to time smoothing in HSM is set by Neyman-Pearson lemma. Simulation results show that HSM not only works in a noisy environment but also outperforms a standalone time or frequency smoothing algorithm in terms of probability of signal detection
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页数:5
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