Wideband Spectrum Detection using Compressed Sampling under Fading Channel Environments
Efficient spectrum detection is essential to Cognitive Radio systems. In this paper, a novel spectrum detection method based on Bayesian compressed sampling is proposed. Firstly, the sparsity of the received signal under fading channel is studied. Then, Bayesian compressed sampling(BCS) is introduced to the spectrum detection for wideband cognitive radio system, and the spectrum components can be reconstructed adaptively through relevance vector machine. The simulation results show that the proposed method have good performance on spectrum reconstruction quality in fading channel environments and is robust to channel noise as well, meanwhile the signal can be acquired at sub-Nyquist sampling rate.
dynamic spectrum access cognitive radio spectrum detection Bayesian compressed sampling
Lina Qi Shucong Jiang Zongliang Gan Hongbo Zhu
Nanjing University of Posts and Telecommunications Wireless Communication Lab Nanjing, China
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
1616-1619
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）