An Analytical Characterization of Maximum Likelihood Signal-to-Noise Ratio Estimation

In this work, the maximum-likelihood estimation of the signal-to-noise ratio is analytically characterized. In particular, the useful and the noise power are modelled by a X
²
-distribution, whereas the resulting signal-to-noise ratio is described in items of a non-central F-distribution. In addition, to better evaluate the estimator efficiency, the Cramer-Rao bound is computed. Finally, in order to completely verify the analytical characterization, the transmit-receive chain has been simulated, and the numerical results are compared to the analytical formulas