Data-Aided Signal-to-Noise-Ratio (SNR) estimation is considered for
time selective fading channels whose time variation is described by a
polynomial time model. The inherent estimation accuracy limitations
associated with the problem are quantified via a CramerRao Bound analysis.
A maximum likelihood type class of estimators is proposed and its exact,
non-asymptotic performance is computed. The standard, constant channel
SNR estimator performance is determined in the presence of channel
polynomial order mismatch. Simulations results are presented which verify
the effectiveness of the technique as well as its performance advantage over
previously proposed methods.