Real Additive White Gaussian Noise Research Articles

Quasi-Concavity for Gaussian Multicast Relay Channels.

Standard upper and lower bounds on the capacity of relay channels are cut-set (CS), decode-forward (DF), and quantize-forward (QF) rates. For real additive white Gaussian noise (AWGN) multicast relay channels with one source node and one relay node, these bounds are shown to be quasi-concave in the receiver signal-to-noise ratios and the squared source-relay correlation coefficient. Furthermore, the CS rates are shown to be quasi-concave in the relay position for a fixed correlation coefficient, and the DF rates are shown to be quasi-concave in the relay position. The latter property characterizes the optimal relay position when using DF. The results extend to complex AWGN channels with random phase variations.

Blind SNR estimation for limited time series

Abstract A blind SNR estimation method for discrete data is presented. The original noise-free data is assumed to follow a known signal model with an unknown attenuation. The SNR in noisy data is estimated using a polynomial fit obtained from the correlative characteristics between SNR and variance fractal dimension values. The bias and the “standard error” (root mean square error) of the estimator are used as performance measures. The simulated performance of the estimator for a specific signal model with real additive white Gaussian noise assumption is compared to that of a published decision-aided (nonblind) SNR estimator.

A comparison of SNR estimation techniques for the AWGN channel

The performances of several signal-to noise ratio (SNR) estimation techniques reported in the literature are compared to identify the best estimator. The SNR estimators are investigated by the computer simulation of baseband binary phase-shift keying (PSK) signals in real additive white Gaussian noise (AWGN) and baseband 8-PSK signals in complex AWGN. The mean square error is used as a measure of performance. In addition to comparing the relative performances, the absolute levels of performance are also established; the simulated performances are compared to a published Cramer-Rao bound (CRB) for real AWGN and a CRB for complex AWGN that is derived here. Some known estimator structures are modified to perform better on the channel of interest. Estimator structures for both real and complex channels are examined.