Friday 23rd of February 2018

Cramer-Rao Lower Bound for NDA SNR Estimation from Linear Modulation Schemes over Flat Rayleigh Fading Channel

Monia Salem

In this contribution, Cramer-Rao lower bound (CRLB) for signal-to-noise ratio (SNR) estimation is addressed from linear modulation signals considering a transmission over a fading channel. We derived the expressions of Fisher information matrix entries to assess the optimal variance of any unbiased SNR estimator. Based on Monte Carlo integration, simulation results are drawn from several constellation densities and observation window sizes. For considered modulations, it is shown that the lower bound takes higher values as long as the modulation order increases. The derived bound provides an efficient standard for evaluating the performance of any unbiased non-data aided (NDA) SNR estimator from linear modulation signals over flat Rayleigh fading channel (FRFC).

Keywords: Cramer-Rao lower bound, signal-to-noise ratio, non-data aided estimation, FRFC, complex AWGN

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Monia Salem
National Engineering School of Tunis

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