基于非线性能量收集的认知WPCN性能优化

Performance Optimization of Cognitive WPCNs with Nonlinear Energy Harvesting

考虑了一个基于点对点主通信链路的认知无线供电通信网络(Wireless Powered Communication Network,WPCN),该认知WPCN由一个多天线混合接入点组成,该接入点将无线能量传输给一组低功耗无线设备,并接收来自这些无线设备的传感数据。为了解决认知WPCN中固有的用户不公平问题,同时考虑到同相/正交不平衡、非线性放大幅度和相位噪声对低成本传感器节点物理收发器的影响,提出了一个基于非线性能量收集的簇协作协议,从而平衡不同无线设备的能量消耗,提高了认知WPCN系统的吞吐量性能。为了保证主系统的性能,考虑了主系统的温度干扰约束,在三种实际网络环境下进行了仿真,结果表明,该方法能有效提高认知WPCN的吞吐量公平性,同时保证了主网络的通信质量。

A cognitive wireless powered communication network(WPCN)based on a point⁃to⁃point primary communication link is con⁃sidered,which consists of a multi⁃antenna hybrid access point that transmits wireless energy to a group of low⁃power wireless devices,and receives sensor data from these wireless devices.To solve the user unfairness inherent in cognitive WPCN,a clustering⁃cooperation protocol with nonlinear energy harvesting is proposed to balance the energy consumption of different wireless devices,with the effects of in⁃phase/orthogonal imbalance,nonlinear amplification amplitude and phase noise on the physical transceiver of low⁃cost sensor nodes being considered,thus enhancing the throughput fairness performance of cognitive WPCN system.To ensure the performance of the pri⁃mary system,the temperature interference constrain is considered,and the simulation results in three real network environments demon⁃strate that the proposed method can effectively improve the throughput fairness of cognitive WPCN and guarantee the communication quality of the primary network.