Decentralized Linear Transceiver Design and Signaling Strategies for Sum Power Minimization in Multi-Cell MIMO Systems

This paper considers linear downlink transceiver design for the sum power minimization problem with per-user rate constraints in a multi-cell multi-user MIMO system. This non-convex problem is divided into transmit and receive beamforming optimization steps which are iteratively repeated such that the sum power converges. The transmit beamformers are solved using a successive convex approximation method (SCA), whereas the receive beamformers are computed via the linear minimum mean square error (MMSE) criterion. In addition to centralized design, we propose two decentralized algorithms where the transmit and receive beamforming designs are facilitated by a combination of pilot and backhaul signaling. In the first algorithm, sum power is minimized by computing the transmit beamformers at each base station (BS) and the receive beamformers at each user via iterative over-the-air optimization process. BS side processing requires local effective channel state information (CSI) acquired from precoded uplink pilots. In the second algorithm, the transmit and receive beamformers are iteratively optimized at each BS requiring only local CSI obtained from antenna-specific uplink pilots. In both algorithms, transmit beamforming optimization is decoupled among the BSs via primal decomposition method, which requires scalar backhaul information exchange for decentralized processing. The performance of the proposed algorithms is evaluated via numerical examples under different system settings in static and time-correlated channel conditions.