Bandwidth Efficient Maximum Likelihood SNR Estimators for QAM Signals in Complex AWGN Channel

The signal-to-noise ratio (SNR) is often unknown to the receiver in most wireless communication systems. In order to perform various functions, SNR needs to be estimated. This paper deals with the estimation of SNR in a system that is based on quadrature amplitude modulation (QAM) signals transmitted through a complex additive white Gaussian noise (AWGN) channel. The estimator is designed for non-data-aided (NDA) and partially data-aided (PDA) scenarios using the maximum likelihood approach. The Cramer-Rao lower bound (CRLB) is also derived for the estimators. Different types of square and cross QAM have been used for performance evaluation of the NDA estimator. The PDA case has been observed for different ratios of pilot and data symbols. Performance of estimators has been compared with CRLB for all cases.