Abstract: In recent years, with the rapid development of mobile terminal equipment and cellular communication technology, the problem of huge increase in electricity consumption and high electricity cost becomes increasingly prominent. Aiming at the base station equipped with renewable energy sources and energy storage devices and connected to smart grid, this paper studies the real-time optimization of power allocation and energy scheduling for downlink communication in such base station, with the goal of reducing the power purchase cost of the base station. Considering the randomness of data arrival at the base station, the fluctuation of channel state, the intermittenity of renewable energy output and the time-variability of electricity price of smart grid, the power allocation and energy scheduling model of a base station in downlink communication is constructed under the constraint of energy storage causality and user maximum tolerance. Then a low-complexity real-time optimization algorithm is proposed based on the improved Lyapunov optimization theory. Through real-time allocation of transmission power and energy scheduling, the power purchase cost of the base station is minimized. At the same time, the data transmission service is guaranteed within the time delay that users can tolerate. Theoretical analysis shows that the proposed algorithm can make real-time decision only according to the current system state, and the optimization result is infinitely close to the optimal value. Finally, the simulation results show that the proposed algorithm can effectively reduce the cost of electricity purchase for network operators, and the cost of electricity purchase can be reduced by 37.1%, 29.8% and 15.7%, respectively, compared with the benchmark greedy algorithm.

Key words: power allocation, energy scheduling, Lyponov optimization, energy storage