On the Spatial Predictability of Communication Channels

In this paper, we are interested in fundamentally understanding the spatial predictability of wireless channels. We propose a probabilistic channel prediction framework for predicting the spatial variations of a wireless channel, based on a small number of measurements. By using this framework, we then develop a mathematical foundation for understanding the spatial predictability of wireless channels. More specifically, we characterize the impact of different environments, in terms of their underlying parameters, on wireless channel predictability. We furthermore show how sampling positions can be optimized to improve the prediction quality. Finally, we show the performance of the proposed framework in predicting (and justifying the predictability of) the spatial variations of real channels, using several measurements in our building.