Maximum Likelihood Estimator of SNR for QAM Signals in AWGN Channel

The signal-to-noise ratio (SNR) is unknown to the receiver in most wireless communication applications, and its estimation is often required. This paper deals with the estimation of SNR in a wireless communication system employing quadrature amplitude modulation (QAM) signals in complex additive white Gaussian noise (AWGN) channel. The estimator has been designed using the maximum likelihood approach for data-aided scenario. The Cramer-Rao lower bound (CRLB) has also been derived for the estimator. The results have been observed for different square and cross QAM constellations, and for different packet lengths. The obtained results confirm the efficacy of the ML estimator with respect to CRLB.