Optimal resource allocation for smart-grid powered MIMO broadcast channels

A novel framework is proposed for optimal resource management in multi-input multi-output (MIMO) downlink systems with smart-grid capabilities. Practical models are put forth to account for the stochastic renewable energy sources (RES), dynamic energy prices, as well as random wireless channels. Capitalizing on these models, a resource allocation task is formulated as an optimization problem that aims at maximizing the weighted sum-rate of MIMO broadcast channels. In addition to storage units accommodating the RES variability, a budget constraint is imposed for the worst-case energy transaction cost. Leveraging the information-theoretic uplink-downlink duality and Lagrange dual based subgradient method, an efficient algorithm is tailored to obtain the optimal strategy.