PROJECT TITLE :
On Multiple Antenna Spectrum Sensing Under Noise Variance Uncertainty and Flat Fading
We investigate a spectrum sensing method based on asymptotic analysis of the discrete Fourier transform of the received multiantenna signal, possibly non-Gaussian, for flat-fading primary user signals in white noise under noise variance uncertainty. The proposed approach is based on the generalized likelihood ratio test (GLRT) paradigm for a restricted version of the problem obtained by ignoring the spatial structure of the primary users' received signals, and it permits the noise variances to be different at different antennas without requiring knowledge of their values. Simulation examples show the efficacy of the proposed approach compared with the energy detector and some existing time-domain GLRT approaches. A performance analysis of the proposed detector is carried out and verified via simulations. It is also shown that the proposed test statistic is equivalent to an existing time-domain GLRT statistic except that the latter has been derived under the assumption that received signal is Gaussian whereas we make no such assumption.
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