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dc.contributor.authorYin, Wotao
Wen, Zaiwen
Li, Shuyi
Meng, Jia (Jasmine)
Han, Zhu
dc.date.accessioned 2018-06-19T17:46:42Z
dc.date.available 2018-06-19T17:46:42Z
dc.date.issued 2011-01
dc.identifier.citation Yin, Wotao, Wen, Zaiwen, Li, Shuyi, et al.. "Dynamic Compressive Spectrum Sensing for Cognitive Radio Networks." (2011) https://hdl.handle.net/1911/102179.
dc.identifier.urihttps://hdl.handle.net/1911/102179
dc.description.abstract In the recently proposed collaborative compressive sensing, the cognitive radios (CRs) sense the occupied spectrum channels by measuring linear combinations of channel powers, instead of sweeping a set of channels sequentially. The measurements are reported to the fusion center, where the occupied channels are recovered by compressive sensing algorithms. In this paper, we study a method of dynamic compressive sensing, which continuously measures channel powers and recovers the occupied channels in a dynamic environment. While standard compressive sensing algorithms must recover multiple occupied channels, a dynamic algorithm only needs to recover the recent change, which is either a newly occupied channel or a released one. On the other hand, the dynamic algorithm must recover the change just in time. Therefore, we propose a least-squared based algorithm, which is equivalent to l0 minimization. We demonstrate its fast speed and robustness to noise. Simulation results demonstrate effectiveness of the proposed scheme.
dc.format.extent 6 pp
dc.title Dynamic Compressive Spectrum Sensing for Cognitive Radio Networks
dc.type Technical report
dc.date.note January 2011
dc.identifier.digital TR11-04
dc.type.dcmi Text


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