The pathwise MIMO Interfering Broadcast Channel

Interference alignment (IA) through beamforming in MIMO Interfering Broadcast Channels (IBC) allows to handle multi-cell interference with low latency. However, with multiple antennas on both ends, the MIMO setting requires global Channel State Information at the Transmitter (CSIT) (i.e. CSIT from the other transmitters (Tx) also). Though global CSIT can be organized within a cluster, it leads to significant fast CSIT acquisition overhead. In this paper we focus on the (dominant) multipath components in the MIMO propagation channels with only the slow fading components known to the Tx, corresponding to a structured form of covariance CSIT. The pathwise approach allows for a decomposition of the alignment tasks between Tx and receivers (Rx), leading to the sufficiency of local pathwise CSIT plus limited coordination overhead. To optimize Ergodic Weighted Sum Rate at finite SNR, we exploit the uplink/downlink duality to design the Tx beamformers as MMSE filters, in which averaging over complex path amplitudes leads to pathwise filters. We furthermore explore a relation between the difference of convex (DC) functions programming and the Weighted Sum MSE (WSMSE) approaches, indicating significant convergence speed potential for the former, and allowing a fixing of the latter for the case of partial CSIT.