Adaptive Energy Storage Management in Green Wireless Networks

Time-varying wireless channel as well as the variability of renewable energy supply and energy prices are practically unknown in advance. To address such dynamic statistics of wireless networks, this letter develops an adaptive strategy inspired by combinatorial multiarmed bandit model for energy storage management and cost-aware coordinated load control at the base stations. The proposed strategy makes online foresighted decisions on the amount of energy to be stored in storage to minimize the average energy cost over long-time horizon. Simulation results validate the superiority of the proposed strategy over a recently proposed storage-free learning-based design.