This paper envisions a future cellular network where base stations (BSs) are powered by multiple types of energy sources, such as those from the traditional power grid, solar energy, and wind energy. This means that the BSs can reduce their carbon footprints if they have enough green energy stored in their batteries. Otherwise, BSs can be switched to on-grid energy to serve mobile users. Such reduction of the BSs’ power consumption is crucial to green cellular networks, since BSs consume more than 50% of the total energy of cellular networks. In order to reduce the on-grid energy consumption of cellular networks during the peak traffic hours, this work studied the green energy optimization (GEO) problem to balance the energy consumption among BSs. To solve the problem, this paper decomposed the GEO problem into two sub-problems, in the time dimension and the spatial dimension, respectively, the multi-stage energy allocation (MEA) problem and the multi-BSs energy balancing (MEB) problem based on the characteristics of green energy generation and mobile traffic. The authors provided theoretical analysis and extensive simulations to demonstrate that the proposed scheme is able to save a significant amount of on-grid energy.
This paper has also been recommended as a "Distinguished Paper" in the IEEE ComSoc MMTC Reviewer Letter in February 2014.