Blind Spectrum Sensing by Information Theoretic Criteria

Information theoretic criteria (ITC) based spectrum sensing is a promising blind method which can reliably detect the primary users while requiring little prior information in cognitive radio networks. In this paper, we provide an intensive treatment on the ITC sensing. We first introduce a new over-determined channel model constructed by applying multiple antennas in order to make the ITC applicable. Then, a simplified ITC sensing algorithm is introduced, which needs to compute and compare only two decision values. Compared with the original ITC (OITC) sensing algorithm, the simplified algorithm significantly reduces the computational complexity without losing any performance. Furthermore, applying the recent advances in random matrix theory, we derive closed-form expressions to tightly approximate both the probability of false alarm and probability of detection. Finally, comprehensive simulations are carried out to evaluate the performance of the proposed ITC sensing algorithms. Results show that they considerably outperform existing blind spectrum sensing methods in certain cases.