A renewable energy cooperation scheme for OFDM systems using evolutionary many-objective optimization algorithm

Energy harvesting has drawn more and more attention because of the requirement of the green communication. It is well known that energy harvesting is one of the most important technologies of the green communication. Due to the intermittency of the renewable energy and the different space of the Base stations (BSS), the renewable energy cooperation is necessary to improve the renewable energy efficiency. In this paper, we propose a renewable energy cooperation scheme among different BSS, in which one BS can collect (share) energy from (to) another BSS. It is obvious that the energy cooperation efficiency will be improved when the number of the BSS that join the cooperation scheme is large. In this paper, our objective is to minimize the networks delay of each BS. To minimize the networks delay, it is reasonable that each BS hopes to transfer its energy to another BSS as little as possible, and collects energy from another BSS as much as possible. Thus, the objective of each BS are conflicting. We formulate the joint optimization problem into a many-objective mixed integer optimization problem which is difficult to optimize. We adopt the evolutionary many-objective algorithm based on decomposition and reference distance to optimize the problem. Simulation results show that the effectiveness of the algorithm.