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.　©　2018,　ICST　Institute　for　Computer　Sciences,　Social　Informatics　and　Telecommunications　Engineering.