An adaptive signal-to-noise ratio estimator in mobile communication channels

Abstract

Representing the reception condition directly, signal-to-noise ratio (SNR) is an important parameter in mobile propagation channels, and therefore is widely used in system performance evaluations and adaptive applications. Hence, this paper puts forward a frequency domain SNR estimator in mobile communications, where we exploit the signal model with the band-limited fading channel and the additive white Gaussian noise. With the above model, the noise power spectrum density can be estimated from the periodogram of channel-plus-noise signals, subsequently leading to our SNR estimation. Moreover, in order to degrade the intrinsic spectrum leakage of fast Fourier transform in periodogram calculation, the leakage expression is derived analytically and then an adaptive process is proposed to make a tradeoff between leakage reduction and noise smoothing. We verify our algorithm by simulations and observe high accuracy in a wide range of velocities and SNRs. Additionally, unlike the conventional work, the proposed estimator is not strictly based on the assumption of specific Doppler spectral shapes except for the requirement of the band-limited channel, hence it is robust to general mobile channels.