標題: Dynamic Sampling Rate Adjustment for Compressive Spectrum Sensing over Cognitive Radio Network
作者: Huang, Ching-Chun
Wang, Li-Chun
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
關鍵字: Cognitive radio;dynamic system;sequential Monte Carlo;compressive spectrum sensing
公開日期: Apr-2012
摘要: In this paper, a dynamic sampling rate adjustment scheme is proposed for compressive spectrum sensing in cognitive radio network. Nowadays, compressive sensing (CS) has been proposed with a revolutionary idea to sense the sparse spectrum by using a lower sampling rate. However, many methods for compressive spectrum sensing assume that the sparse level is static and a fixed compressive sampling rate is applied over time. To adapt to time-varying sparse levels and adjust the sampling rate, we proposed to model sparse levels as a dynamic system and treat the dynamic rate selection as a tracking problem. By introducing the Sequential Monte Carlo (SMC) algorithm into a distributed compressive spectrum sensing framework, we could not only track the optimal sampling rate but determine the unoccupied channels accurately in a unified method.
URI: http://dx.doi.org/10.1109/WCL.2012.010912.110136
http://hdl.handle.net/11536/133700
ISSN: 2162-2337
DOI: 10.1109/WCL.2012.010912.110136
期刊: IEEE WIRELESS COMMUNICATIONS LETTERS
Volume: 1
Issue: 2
起始頁: 57
結束頁: 60
Appears in Collections:Articles