The Wideband Spectrum Sensing Based on Compressed Sensing and Interference Temperature Estimation

Future cognitive radios will be capable of scanning a wide band of frequencies, in the order of a few GHz, and the employment of adaptive waveforms according to the estimated spectrum of the licensed systems challenges traditional spectral estimation methods, which typically operate at or above Nyquist rates. We research the problem of estimating the spectrum of the wide-band signal received at the cognitive radio sensing receiver using compressed sensing coupled with interference temperature estimation to determine the spectrum occupancy of the licensed system. First, we achieve coarse identifica-tion of frequency boundaries of each sub-band via compressed sensing tech-niques at a Sub-Nyquist rate, which is much less than Nyquist rate. Then we use MTM-SVD method to compute the interference temperature value of each subband, and compare these values with threshold. The multitaper spectrum estimation has high accuracy and near-optimality. And the simulation result shows that we can achieve the interference temperature estimation of each sub-band accurately.