认知无线电环境下无线能量通信网能效研究

doi:10.19678/j.issn.1000-3428.0050228

计算机工程 ›› 2019, Vol. 45 ›› Issue (3): 142-147. doi: 10.19678/j.issn.1000-3428.0050228

认知无线电环境下无线能量通信网能效研究

冯刚¹,覃锡忠¹,贾振红¹,牛红梅²,王哲辉²

1.新疆大学信息科学与工程学院,乌鲁木齐 830046; 2.中国移动通信集团新疆有限公司网络监控部,乌鲁木齐 830046

收稿日期:2018-01-22 出版日期:2019-03-15 发布日期:2019-03-15
作者简介:冯刚(1992—),男,硕士研究生,主研方向为认知无线电网络、绿色通信;覃锡忠(通信作者),副教授、硕士;贾振红,教授、博士;牛红梅,硕士;王哲辉,工程师。
基金资助:
中国移动通信集团新疆有限公司研究发展基金(XTM2013-2788)。

Research on Energy Efficiency of Wireless Powered Communication Network in Cognitive Radio Environment

FENG Gang¹,QIN Xizhong¹,JIA Zhenhong¹,NIU Hongmei²,WANG Zhehui²

1.College of Information Science and Engineering,Xinjiang University,Urumqi 830046,China; 2.Department of Network Monitoring,China Mobile Communications Group Xinjiang Co.,Ltd.,Urumqi 830046,China

Received:2018-01-22 Online:2019-03-15 Published:2019-03-15

摘要/Abstract

摘要：

为提高无线能量通信网的能效,建立一种认知无线电环境下的多信号源采集模型。因模型优化问题是一个非凸问题,利用分式规划原理将其转变为一个标准的凸优化问题,在此基础上,通过联合优化时间分配与功率控制并提出一种优化迭代算法,以实现系统能效的最大化。仿真结果表明,该模型系统能效较高、收敛速度较快。

关键词: 无线能量通信网, 能效, 能量采集, 认知无线电, 优化迭代算法

Abstract:

In order to improve the energy efficiency of Wireless Powered Communication Network(WPCN),a multiple signal source acquisition model in cognitive radio environment is established.Because the model optimization problem is a non-convex problem,it is transformed into a standard convex optimization problem by using fractional programming principle.On this basis,an optimization iteration algorithm is proposed to maximize the energy efficiency of the system through joint optimization of time allocation and power control.Simulation results show that the proposed model system has higher energy efficiency and faster convergence speed.

Key words: Wireless Powered Communication Network(WPCN), energy efficiency, energy harvesting, cognitive radio, optimization iterative algorithm

中图分类号:

TN925

冯刚,覃锡忠,贾振红,牛红梅,王哲辉. 认知无线电环境下无线能量通信网能效研究[J]. 计算机工程, 2019, 45(3): 142-147.

FENG Gang,QIN Xizhong,JIA Zhenhong,NIU Hongmei,WANG Zhehui. Research on Energy Efficiency of Wireless Powered Communication Network in Cognitive Radio Environment[J]. Computer Engineering, 2019, 45(3): 142-147.

http://www.ecice06.com/CN/Y2019/V45/I3/142

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