Sparse spectrum sensing with sub-block partition for cognitive radio systems

Meng Lin Ku, Xun Ru Yin

研究成果: 雜誌貢獻會議論文同行評審


Cognitive users are expected to be capable of exploring spectrum holes over a wide range of frequencies. Motivated by the sparse characteristic of underutilized spectrum, we consider sparse spectrum sensing using compressive sensing techniques for cognitive orthogonal frequency division multiplexing (OFDM) systems. The spectrum sensing problem is formulated as a multi-subcarrier detection problem, solved via the composite hypothesis testing and Neyman-Pearson criterion. Considering the availability of channel state information (CSI) at the cognitive device, two sparse spectrum sensing approaches are proposed for detecting the compressive received signals in time domain. For the purpose of complexity reduction, we further incorporate a sub-block partition scheme into the proposed approaches to leverage the spareness of the spectrum occupancy. The proposed approaches enable a flexible tradeoff between the implementation complexity and the sensing accuracy for wideband cognitive radios.

期刊IEEE Vehicular Technology Conference
出版狀態已出版 - 2014
事件2014 79th IEEE Vehicular Technology Conference, VTC 2014-Spring - Seoul, Korea, Republic of
持續時間: 18 5月 201421 5月 2014


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