Spectrum Sensing Based On Incomplete-data

With the appearance and development of cognitive radio(CR),researches of spectrum detection algorithm continually increase.But with the rapid development of wireless communication technology,the signal bandwidth is wider.Sampling hardware doesn't satisfy the requirement of sampling rate.Meanwhile,the radio environment becomes more complicated.Therefore,sampling data is often incomplete.Spectrum sensing based on incomplete-data is researched in this paper.First of all,cognitive radio,spectrum sensing,incomplete-data detection,compressed sensing and spectrum detection based on phase difference are introduced.The causes of incomplete-data mainly includes that sampling rate of sampling hardware doesn't meet the needs of ultra-wide bandwidth signals and the radio environment is complex.Compressed sensing could reduce the demand for sampling rate.Spectrum detection based on phase difference could resist the complex radio environment,such as noise uncertainty and multipath fading.Therefore,compressed sensing and spectrum sensing based on phase difference are chosen to be used for incomplete-data detection.A joint rapid spectrum scanning and signal feature recognition scheme is proposed.It achieves spectrum sensing and signal feather recognition,so as to realize the full sensing on the radio environment.Meanwhile,the reconstruction of original signal is not a must.The relationship between SCF and the compressed samples is deduced in matrix form,which makes it possible to avoid the reconstruction of original signal.SCF for spectrum sensing could be reconstruction from samplings.It reduces the complexity of the combination of compressed sensing and cyclostationary detection.Through careful analysis,the strong dependence of inner sparsity and outer sparsity on modulation mode and symbol rate is discovered.Therefore,modulation mode and symbol rate would affect the compression gain.On this basis,an adaptive algorithm for compression gain adjustment based on modulation mode and symbol rate is proposed.The compression gain is determined based on modulation mode and symbol rate,which can improve the compression gain by 30%and 35%respectively.Through careful analysis,it is noted that the difference of the PD's distributions between noise-perturbed signal and Gaussian noise is obvious.On this basis,a spectrum sensing algorithm based on the variance of phase difference(PDVD)is formulated,which solves the problem that traditional spectrum sensing schemes based on amplitude are susceptive to the noise uncertainty and Rayleigh fading.Simulation and field measurement results prove that PDVD could achieve a 24 dB performance gain compared to energy detection when the sampling length K=500.At last,disadvantages and possible directions for future research are outlined about compressed sensing and spectrum sensing algorithm based on the variance of phase difference.