SUBSECTION-AVERAGE CYCLOSTATIONARY FEATURE DETCTION IN COGNITIVE RADIO

被引：0
|
作者：
Lin, Yingpei [1 ]
He, Chen [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200030, Peoples R China
来源：
2008 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND SIGNAL PROCESSING, VOLS 1 AND 2 | 2007年
关键词：
Cognitive radio; Spectrum sensing; Cyclostationary feature detection; Cyclic spectrum; Cyclic autocorrelation;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Spectrum sensing plays an important role in cognitive radios because the secondary users need to continuously monitor the spectrum for the presence of primary user. In this paper, we mainly investigated the cyclostationary feature spectrum detection in cognitive radios. Our analysis shows that cyclostationary feature detection requires partial information of the primary user and high computation cost although it is robust to interference in low SNR. We propose a novel strategy for spectrum sensing based on cyclostationary feature detection. Our new approach can effectively decrease the computational complexity and improve the performance of the inhibition of noise interference. At last, numerical results are provided in order to illustrate the advantages of our new technique.
引用
收藏
页码：604 / 608
页数：5
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