A Control-Theoretic Approach for Cell Zooming of Energy Harvesting Small Cell Networks

Dense deployment of small cell base stations (SBSs) powered by renewable energy is spotlighted as a solution of the increasing demand of communication services. How to utilize renewable energy efficiently under the temporal change of traffic loads is a brand new challenge. In this paper, we design real-time controllers for cell zooming, that is, to determine transmission power and activation/deactivation of energy harvesting SBSs. The proposed method maximizes the total number of accommodated users, considering the remaining energies of batteries. First, we solve a problem of finding a number of active SBSs that maximizes energy efficiency with full accommodation of active users. Then, we apply model predictive control to the real-time computation of an optimal transmission power. Moreover, we present an explicit formula of an approximate optimal transmission power, by simplifying the proposed method. Numerical simulations illustrate that the proposed method achieves high performance on energy efficiency with low computational effort, compared with a Q-learning-based approach.