Title of Paper:Low Complexity Compressive Wideband Spectrum Sensing in Cognitive Radio

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Date of Publication:2018-01-01

Included Journals:CPCI-S

Page Number:1-5

Key Words:cognitive radio (CR); spectrum sensing; sub-Nyquist sampling; cyclostationary feature detection

Abstract:The capability of cognitive radio (CR) is realized by spectrum sensing. However, with the increase of signal bandwidth and the complexity of communication environment, traditional spectrum sensing has been facing a considerable challenge. Cyclic spectrum sensing techniques work well under noise uncertainty, but also require high-rate sampling. For realizing robust sub-Nyquist cyclostationary feature detection, we propose to reconstruct the conjugate cyclic spectrum of signals from a frequency domain representation at sub-Nyquist sampling rate. By investigating the link between the conjugate cyclic spectrum and the entries of the shifted conjugate correlation matrix, we transform the reconstruction of the cyclic spectrum into a solution to the correlation matrix. Further, a new reduced complexity method for reconstructing useful shifted conjugate correlation between frequency shifted versions of signals is presented. Simulations show that the proposed method has a high probability of detection and reconstruction accuracy against both noise uncertainty and sampling rate reduction.