Estimation of nakagami distribution parameters based on signal samples corrupted with multiplicative and additive disturbances

The problem of estimating the Nakagami-m distribution parameters in noisy slowly fading channels is studied. Previous published works have mainly examined estimation based on faded samples, not including phase fluctuations, shadow fading and additive noise. In this paper, a system model which uses samples corrupted by multipath and shadow fading, phase fluctuations and noise is examined. Expressions for the probability density function and n-th order moment of noisy channel samples are presented. Moment-based estimator for operation in noisy environments is developed based on presented probability density function. The sample mean and variance of the estimator are determined. Numerical results show that this estimator has better performances then previously published estimators treating noisy samples, and superior performances over estimators designed for noiseless samples in applications where noise is present.