  Spectrum sensing is a fundamental and critical issue for opportunistic
spectrum access in cognitive radio networks. Among the many spectrum sensing
methods, the information theoretic criteria (ITC) based method is a promising
blind method which can reliably detect the primary users while requiring little
prior information. In this paper, we provide an intensive treatment on the ITC
sensing method. To this end, we first introduce a new over-determined channel
model constructed by applying multiple antennas or over sampling at the
secondary user 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 sensing algorithm, the
simplified algorithm significantly reduces the computational complexity without
losing any performance. Applying the recent advances in random matrix theory,
we then derive closed-form expressions to tightly approximate both the
probability of false alarm and probability of detection. Based on the insight
derived from the analytical study, we further present a generalized ITC sensing
algorithm which can provide flexible tradeoff between the probability of
detection and probability of false alarm. Finally, comprehensive simulations
are carried out to evaluate the performance of the proposed ITC sensing
algorithms. Results show that they considerably outperform other blind spectrum
sensing methods in certain cases.
