SNR Estimation for a Non-Coherent Binary Frequency Shift Keying Receiver

This paper deals with the problem of estimating the average signal-to-noise ratio (SNR) for a communication system employing non-coherent binary frequency shift keying (NCBFSK) over fading channels with white Gaussian noise (AWGN). The maximum likelihood (ML) estimator and one using data statistics have been derived and simulated for various scenarios including data-aided (DA), non-data aided (NDA) and joint estimation using both the data and pilot sequences. We also derive the Cramer-Rao bound (CRB) for the estimators. The results show that for a particular region of interest (e.g. high SNR or low SNR) and depending upon the availability of pilot sequence, a particular SNR estimation scheme is suitable.