Channel equalization in the presence of strong interference sources

Space-time channel estimation is essential for communication systems which separate sources in the space domain in addition to time/frequency/code domains. We first develop a maximum likelihood (ML) estimator for the spatial channel transfer function in the presence of strong interference sources, for 3 different channel scenarios: no multipath, locally scattered multipath, and general multipath case. As expected, the ML estimator which assumes a planar wavefield for the signal provides superior performance over the ML solution for the general multipath case. In order to maintain robustness in the scenario, an algorithm for scenario/model determination is developed, and its performance is evaluated via simulations.