Title: Opportunistic Downlink Interference Alignment for Multi-Cell MIMO Networks,
Abstract: In this paper, we propose an opportunistic downlink interference alignment
(ODIA) for interference-limited cellular downlink, which intelligently combines
user scheduling and downlink IA techniques. The proposed ODIA not only
efficiently reduces the effect of inter-cell interference from other-cell base
stations (BSs) but also eliminates intra-cell interference among spatial
streams in the same cell. We show that the minimum number of users required to
achieve a target degrees-of-freedom (DoF) can be fundamentally reduced, i.e.,
the fundamental user scaling law can be improved by using the ODIA, compared
with the existing downlink IA schemes. In addition, we adopt a limited feedback
strategy in the ODIA framework, and then analyze the number of feedback bits
required for the system with limited feedback to achieve the same user scaling
law of the ODIA as the system with perfect CSI. We also modify the original
ODIA in order to further improve sum-rate, which achieves the optimal multiuser
diversity gain, i.e., $\log\log N$, per spatial stream even in the presence of
downlink inter-cell interference, where $N$ denotes the number of users in a
cell. Simulation results show that the ODIA significantly outperforms existing
interference management techniques in terms of sum-rate in realistic cellular
environments. Note that the ODIA operates in a non-collaborative and decoupled
manner, i.e., it requires no information exchange among BSs and no iterative
beamformer optimization between BSs and users, thus leading to an easier
implementation.