Pilot-symbol-aided channel estimation in time and frequency

Abstract

The potentials of pilot-symbol-aided channel estimation in two dimensions are explored for mobile radio and broadcasting applications. In order to procure this goal, the discrete shift-variant 2-D Wiener filter is analyzed given an arbitrary sampling grid, an arbitrary (but possibly optimized) selection of observations, and the possibility of model mismatch. In addition, the classical scheme using two separate 1-D FIR filters is analysed. Filtering in two dimensions is revealed to outperform filtering in just one dimension with respect to overhead, mean-square error performance and latency. Conceptually, the discrete shift-variant 2-D Wiener filter is the optimal linear estimator for the given problem, however, two cascaded orthogonal 1-D filters are simpler to implement and virtually as good as true 2-D filters. Analytical results are presented, verified by Monte-Carlo simulations.