Dynamic Compressive Spectrum Sensing for Cognitive Radio Networks

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dc.contributor.authorYin, Wotaoen_US
dc.contributor.authorWen, Zaiwenen_US
dc.contributor.authorLi, Shuyien_US
dc.contributor.authorMeng, Jia (Jasmine)en_US
dc.contributor.authorHan, Zhuen_US
dc.date.accessioned2018-06-19T17:46:42Zen_US
dc.date.available2018-06-19T17:46:42Zen_US
dc.date.issued2011-01en_US
dc.date.noteJanuary 2011en_US
dc.description.abstractIn 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.en_US
dc.format.extent6 ppen_US
dc.identifier.citationYin, Wotao, Wen, Zaiwen, Li, Shuyi, et al.. "Dynamic Compressive Spectrum Sensing for Cognitive Radio Networks." (2011) <a href="https://hdl.handle.net/1911/102179">https://hdl.handle.net/1911/102179</a>.en_US
dc.identifier.digitalTR11-04en_US
dc.identifier.urihttps://hdl.handle.net/1911/102179en_US
dc.language.isoengen_US
dc.titleDynamic Compressive Spectrum Sensing for Cognitive Radio Networksen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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