Estimation of Ricean K parameter and local average SNR from noisy correlated channel 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 most previous estimators where independent channel samples are assumed, in this paper, novel estimators that assume correlated channel samples are proposed. Both data-aided and non-data-aided designs are considered. The performances of the new estimators are examined. Several design issues are discussed. Numerical results are presented to show their good performances in a realistic Ricean fading channel