An EM Approach for Cooperative Spectrum Sensing in Multiantenna CR Networks

In this paper, a cooperative wideband spectrum sensing scheme based on the expectation-maximization (EM) algorithm is proposed for the detection of a primary user (PU) system in multiantenna cognitive radio (CR) networks. Given noisy signal observations from N secondary users (SUs) over multiple subbands at a fusion center (FC), prior works on cooperative spectrum sensing often use the set of received subband energy as decision statistics over the sensing interval. However, to achieve satisfactory performance, knowledge of the channel state information (CSI) and the noise variances at all the SUs is required by these algorithms. To overcome this limitation, our proposed method, which is referred to as joint detection and estimation (JDE), adopts the EM algorithm to jointly detect the PU signal and estimate the unknown channel frequency responses and noise variances over multiple subbands in an iterative manner. Various aspects of this proposed EM-JDE scheme are investigated, including a reliable initialization strategy to ensure convergence under practical conditions and a distributed implementation to reduce communication overhead. Under the assumption of perfect estimation for the channel frequency responses and noise variances, we further show that the proposed EM-JDE converges to the maximum-likelihood (ML) solution, which serves as an upper bound on its performance. Monte Carlo simulations over Rayleigh fading channels show that the proposed scheme significantly improves the performance of spectrum detection by exploiting the diversity of the spatially distributed SUs with multiple antennas.