Maximum Likelihood Parameter Estimation of Nakagami-Gamma Shadowed Fading Channels

In this paper, we investigate the performance of the maximum likelihood (ML) method to estimate the parameters of compound Nakagami-gamma shadowed fading channels. We derived analytically the ML estimates of the Nakagami-gamma distribution by using the expectation-maximization (EM) algorithm. Numerical simulations demonstrate the outperformance of the EM algorithm in terms of accuracy versus the moment-based estimation technique. Moreover, the EM iterations converge to the global optimum.