Chandra Sekhar, S and Sreenivas, TV (2006) Signal-to-noise ratio estimation using higher-order moments. In: Signal Processing, 86 (4). pp. 716-732.
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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 dB(2). The main feature of the MoM 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.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Elsavier Science.|
|Keywords:||Signal-to-noise ratio;Phase signal;Moments;Mean square error; Cramer–Rao bound;Instantaneous frequency.|
|Department/Centre:||Division of Electrical Sciences > Electrical Communication Engineering|
|Date Deposited:||09 Apr 2009 05:43|
|Last Modified:||19 Sep 2010 04:59|
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