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基于能效最大的无线供电反向散射网络资源分配算法
Energy efficiency maximization resource allocation algorithm in wireless-powered backscatter communication network
- 通信学报 2020年41卷第10期 页码：202-210
- 作者机构：
1. 重庆邮电大学通信与信息工程学院，重庆 400065
2. 重庆邮电大学-伦敦布鲁内尔大学交叉创新研究院，重庆 400065
- 作者简介：
[ "徐勇军（1986- ），男，湖北赤壁人，博士，重庆邮电大学副教授、硕士生导师，主要研究方向为反向散射通信、异构无线网络传输技术等" ]
[ "谷博文（1996- ），男，新疆昌吉人，重庆邮电大学硕士生，主要研究方向为反向散射通信、异构无线网络、边缘计算等" ]
[ "陈前斌（1967- ），男，四川南充人，博士，重庆邮电大学教授、博士生导师，主要研究方向为无线通信与网络" ]
[ "林金朝（1966- ），男，四川蓬溪人，博士，重庆邮电大学教授、博士生导师，主要研究方向为无线通信传输技术、BAN 与信息处理技术等" ]
- 基金信息：国家自然科学基金资助项目(61601071);重庆市自然科学基金资助项目(cstc2019jcyj-xfkxX0002);重庆市研究生科研创新基金资助项目(CYS20251);重庆市研究生科研创新基金资助项目(CYS20253)
DOI：10.11959/j.issn.1000-436x.2020132
中图分类号： TN918.82-
网络出版日期：2020-10，
纸质出版日期：2020-10-25
- 稿件说明：
移动端阅览
徐勇军, 谷博文, 陈前斌, 等. 基于能效最大的无线供电反向散射网络资源分配算法[J]. 通信学报, 2020,41(10):202-210.
Yongjun XU, Bowen GU, Qianbin CHEN, et al. Energy efficiency maximization resource allocation algorithm in wireless-powered backscatter communication network[J]. Journal on communications, 2020, 41(10): 202-210.
徐勇军, 谷博文, 陈前斌, 等. 基于能效最大的无线供电反向散射网络资源分配算法[J]. 通信学报, 2020,41(10):202-210. DOI： 10.11959/j.issn.1000-436x.2020132.
Yongjun XU, Bowen GU, Qianbin CHEN, et al. Energy efficiency maximization resource allocation algorithm in wireless-powered backscatter communication network[J]. Journal on communications, 2020, 41(10): 202-210. DOI： 10.11959/j.issn.1000-436x.2020132.
摘要
为缓解物联网节点数量增长带来的能耗问题，提出了基于能效最大化的多载波无线供电反向散射网络资源分配算法。首先，考虑发射功率门限和最小收集能量约束，构建了发射功率、传输时间、反射系数和收集能量分配系数联合优化的多变量非线性资源分配模型。然后，基于Dinkelbach方法和变量替换法，将原非凸资源分配问题转化为凸优化问题。同时，利用拉格朗日对偶理论获得解析解。仿真结果表明，与纯反向散射算法和纯能量收集算法相比，所提算法具有较好的能效。
Abstract
In order to alleviate the energy consumption problem caused by the increasing number of Internet of things (IoT) nodes
an energy-efficient (EE) maximization based resource allocation algorithm was proposed for multi-carrier wireless-powered backscatter communication network.Firstly
a multivariable and nonlinear resource allocation model was formulated to jointly optimize transmit power
transmission time
reflection coefficient
and energy-harvesting allocation coefficient
where the maximum transmit power constraint of the power station and the minimum harvested energy constraint at the backscatter device were considered.Then
the original non-convex optimization problem was transformed into a convex one which was solved by using Dinkelbach’s method and the variable substitution approach.Furthermore
the analytical solution of the resource allocation problem was obtained based on Lagrange dual theory.Simulation results verify that the proposed algorithm has better EE by comparing it with the existing algorithm under pure backscatter mode and algorithm under the harvested-then-transmit mode.
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references
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