The Ideal MIMO Channel: Maximizing Capacity in Sparse Multipath with Reconfigurable Arrays

While the intense research on multi-antenna (MIMO) wireless communication channels was pioneered by results based on an i.i.d. channel model representing a rich multipath environment, there is growing experimental evidence that physical wireless channels exhibit a sparse multipath structure, even at relatively low antenna dimensions. In this paper, we propose a model for sparse multipath channels and study coherent MIMO capacity as a function of SNR for a fixed number of antennas. In a recent work, we had shown that the spatial distribution of the sparse multipath has a significant impact on capacity and had also characterized the optimal distribution (the ideal MIMO channel) that maximizes capacity at any operating SNR. In this paper, we refine these results and develop a framework for maximizing MIMO capacity at any SNR by systematically adapting the array configurations (antenna spacings) at the transmitter and receiver to the level of sparsity. Surprisingly, three canonical array configurations are sufficient for near-optimum performance over the entire SNR range. In a scattering environment with randomly distributed paths, the capacity gain due to optimal configuration is directly proportional to the number of antennas at low SNR's. Numerical results based on a realistic physical model are presented to illustrate capacity gains with reconfigurable antenna arrays