Sum-rate maximization and energy-cost minimization for renewable energy empowered base-stations using zero-forcing beamforming

Zero-forcing (ZF) beamforming is a practical linear transmission scheme that eliminates inter-user interference in the downlink of a multiuser multiple-input single-output (MISO) wireless system. By considering base-stations (BSs) that are supported by renewable energy, this work examines offline and online ZF beamforming designs based on two different objectives, namely, sum-rate maximization and energy-cost minimization. For offline policies, the channel states and the energy arrivals are assumed to be known a priori for all time instants whereas, in the online policies, only causal information is available. The designs are subject to energy causality and energy storage constraints, i.e., the constraint that energy cannot be used before it arrives and the constraint that the stored energy cannot exceed the maximum battery storage capacity. In the sum-rate maximization problem, the base-station is assumed to be supported only by renewable energy and the goal is to maximize the sum rate over all users by a predetermined deadline. The optimization of the ZF beamforming direction and power allocation can be decoupled, and the solutions can be found exactly. In the energy-cost minimization problem, the base-station is assumed to be supported by both renewable and power-grid energy, and the goal is to minimize the cost of purchasing grid energy subject to quality-of-service constraints at the users. The problem can be formulated as a convex optimization problem and can be solved efficiently using off-the-shelf solvers. Offline solutions are first obtained and the intuitions gained from their results are used to derive effective online policies. The effectiveness of the proposed policies are demonstrated through computer simulations.