Parametrization of the Local Scattering Function Estimator for Vehicular-to-Vehicular Channels

Non wide-sense stationary (WSS) uncorrelated-scatterering (US) fading processes are observed in vehicular communications. To estimate such a process under additive white Gaussian noise we use the local scattering function (LSF). In this paper we present an optimal parametrization of the multitaper-based LSF estimator. We do this by quantizing the mean square error (MSE). For that purpose we use the structure of a two-dimensional Wiener filter and optimize the parameters of the estimator to obtain the minimum MSE (MMSE). We split the observed fading process in WSS regions and analyze the influence of the estimator parameters on the MMSE under different lengths of the stationarity regions and signal-to-noise ratio values. The analysis is performed considering three different scenarios representing different scattering properties. We show that there is an optimal combination of estimator parameters for different lengths of stationarity region and signal-to-noise ratio values which provides a minimum MMSE.