A Novel Spectrum Sensing for Cognitive Radio Networks With Noise Uncertainty

被引：20
|
作者：
Sun, Mengwei [1 ,2 ]
Zhao, Chenglin [1 ]
Yan, Su [3 ]
Li, Bin [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Informat Sci & Engn, Beijing 100876, Peoples R China
[2] Univ Durham, Sch Engn & Comp Sci, Durham DH1 3LE, England
[3] State Radio Monitoring Ctr Testing Ctr, Beijing 100041, Peoples R China
来源：
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2017年 / 66卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Dynamic noise variance; joint estimation; marginalized adaptive particle filtering (MAPF); spectrum sensing (SS); FLAT-FADING CHANNELS;
D O I：
10.1109/TVT.2016.2596789
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：
This correspondence investigates a joint spectrum sensing scheme in cognitive radio (CR) networks with unknown and dynamic noise variance. A novel Bayesian solution is proposed to recover the dynamic noise variance and detect the occupancy of primary frequency band simultaneously. The states of primary users are detected based on particle filtering technology, and then the noise parameters are tracked by using finite-dimensional statistics for each particle based on marginalized adaptive particle filtering. Simulation results are provided to validate that the proposed method can improve the sensing performance significantly and target the dynamic noise variance accurately.
引用
收藏
页码：4424 / 4429
页数：6
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