A Real-Valued Weighted Covariance-Based Detection Method for Cognitive Radio Networks With Correlated Multiple Antennas

The weighted covariance-based detection (WCD) method for spectrum sensing (SS) can offer a reliable detection performance in the spatially correlated time-varying Rayleigh fading channel. However, it involves huge complex computations. As is well known, one complex multiplication requires two real additions and four real multiplications. To this end, we transfer the complex-valued SS problem into the real-valued SS problem and present a novel-reduced complexity WCD method in this letter, which is referred to as a real-valued WCD (RWCD) method. In particular, an asymptotic closed-form expression of the probability of detection is derived for the proposed RWCD method, which is intractable in the WCD method. Through the complexity analysis, the RWCD method can save nearly half of the computational complexity compared to the WCD method. Meanwhile, simulation results show that the proposed method achieves almost the same performance as that of the WCD method, and both outperform their competitors.