Estimators for K Factor and Local Average SNR Using Noisy Correlated Samples

The problem of estimating the K parameter and the local average signal-to-noise ratio in a noisy Ricean fading channel is studied. Unlike previous estimators where independent or noiseless channel samples are assumed, in this paper, novel estimators are designed to operate with noisy correlated channel samples. Both data-aided and non-data-aided designs are considered. The performances of the new estimators are examined in detail. Numerical results are presented to show their good performances in a realistic Ricean fading channel.