Signal-to-noise ratio estimation using higher-order moments

Authors:
S. Chandra Sekhar;T. V. Sreenivas
Affiliations:
Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore, Karnataka, India;Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore, Karnataka, India
Venue:
Signal Processing
Year:
2006

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Abstract

We consider the problem of estimation of the signal-to-noise ratio (SNR) of an unknown deterministic complex phase signal in additive complex white Gaussian noise. The phase of the signal is arbitrary and is not assumed to be known a priori unlike many SNR estimation methods that assume phase synchronization. We show that the moments of the complex sequences exhibit useful mean-ergodicity properties enabling a "method-of-moments" (MoM)-SNR estimator. The Cramer-Rao bounds (CRBs) on the signal power, noise variance and logarithmic-SNR are derived. We conduct experiments to study the efficiency of the SNR estimator. We show that the estimator exhibits finite sample super-efficiency/inefficiency and asymptotic efficiency, depending on the choice of the parameters. At 0 dB SNR, the mean square error in log-SNR estimation is approximately 2 dB2. The main feature of theMoM estimator is that it does not require the instantaneous phase/frequency of the signal, a priori. Infact, the SNR estimator can be used to track the instantaneous frequency (IF) of the phase signal. Using the adaptive pseudo-Wigner-Ville distribution technique, the IF estimation accuracy is the same as that obtained with perfect SNR knowledge and 8-10 dB better compared to the median-based SNR estimator.