Abstract
Harvesting energy from the environment is a method to improve the energy utilization efficiency. However, most renewable energy has a poor stability due to the weather and the climate. The reliability of the communication systems will be influenced to a large extent. In this paper, an energy-efficient downlink resource allocation problem is investigated in the energy harvesting communication systems by exploiting wireless power transfer technology. The resource allocation problem is formulated as a mixed-integer nonlinear programming problem. The objective is to maximize the energy efficiency while satisfying the energy causality and the data rate requirement of each user. In order to reduce the computational complexity, a suboptimal solution to the optimization problem is obtained by employing a quantum-behaved particle swarm optimization (QPSO) algorithm. Simulation results show that the QPSO algorithm has a higher energy efficiency than the traditional particle swarm optimization (PSO) algorithm.
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