Capacity Scaling of Multi-User MIMO with Limited Feedback in a Multi-Cell Environment

We demonstrate that the fundamental capacity scaling law of multiple-input multiple-output radio systems, being proportional to the minimum of the number of receive and transmit antennas, holds also for the interference-limited multi-user multi-cell downlink scenario. It can be realized by using a sophisticated combination of physical and medium access control layer algorithms. The algorithms have low complexity and require no coherent channel state information at the transmitter. Instead, limited feedback on the effective channel quality is provided via a low-rate control channel. Our set of algorithms offers a fixed grid of beams at the transmitter, where the terminals can select the best beam set. Further, we use receivers exploiting the instantaneous knowledge of the interference at the terminal side. A score-based scheduler, which asymptotically reaches proportional fairness, is used to switch adaptively between multi-user diversity and multi-user multiplexing, in a frequency-selective manner. We provide many insights into the synergy between these algorithms from multi-cell simulations in a hexagonal cellular deployment.