Local mean signal estimation over Nakagami-m fading channels
Accurate and fast algorithms for the local mean signal level estimation are very important for the successful implementation of many wireless communication enabling techniques such as handoff, power control, and adaptive gain control schemes. In this paper, we present on-line simple-to-implement (i) minimum variance unbiased and (ii) maximum likelihood estimators for the local mean signal power estimation in the decibel domain. We consider a generalized Nakagami-m fading environment and show that these estimators are asymptotically efficient in the number of samples and in the fading parameter in. Numerical and simulation results confirm that these estimators outperform the sample mean estimator and quickly approach the Cramer-Rao lower bounds. Copyright (C) 2006 John Wiley & Sons, Ltd.
local mean signal maximum likelihood estimators cramer-rao lower bound wireless channel estimation nakagami fading channels minimum variance unbiased estimators