Maximum likelihood estimation of statistical properties of composite gamma-lognormal fading channels

We propose maximum likelihood (ML) methods for estimating the parameters of composite gamma-lognormal fading channels. Newton-Raphson and expectation-maximization (EM) algorithms are developed to compute the ML estimates of the mean and variance of the shadowing component, and the Nakagami-m parameter of the fading component. We also derive Crame/spl acute/r-Rao bounds (CRBs) for the unknown parameters. Numerical simulations demonstrate the performance of the proposed method.