Multiantenna based spectrum sensing via Friedman test for cognitive radio

Several multiantenna based spectrum sensing detectors have been presented for overcoming noise uncertainty by exploiting antenna correlation. However, these detectors degrade seriously when the antenna correlation is low or the noises through antennas are correlated (i.e. spatial colored noise), and even fail to perform sensing when primary signals through antennas are uncorrelated (i.e., antenna uncorrelation). In order to address this issue, in this paper, we present a Friedman test based spectrum sensing detector which compares the power of the received signals through antennas and hence it needs no priori information of the noise and the primary signal. In addition, the decision threshold level of the presented detector is not related to the number of samples, but related only to the number of antennas and the required false alarm probability. Finally, the performance of the proposal is verified by numerical simulations.