Energy efficiency maximization resource allocation algorithm in wireless-powered backscatter communication network

Yongjun XU; Bowen GU; Qianbin CHEN; Jinzhao LIN

doi:10.11959/j.issn.1000-436x.2020132

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Energy efficiency maximization resource allocation algorithm in wireless-powered backscatter communication network

Correspondences | 更新时间：2024-06-05

- Energy efficiency maximization resource allocation algorithm in wireless-powered backscatter communication network
- Journal on Communications Vol. 41, Issue 10, Pages: 202-210(2020)
- 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：
- 基金信息：
  
  The National Natural Science Foundation of China(61601071);The Natural Science Foundation of Chongqing(cstc2019jcyj-xfkxX0002);The Graduate Scientific research innovation Project of Chongqing(CYS20251);The Graduate Scientific research innovation Project of Chongqing(CYS20253)
- DOI：10.11959/j.issn.1000-436x.2020132
  CLC： TN918.82
- Online First：2020-10，
  
  Published：25 October 2020
- 稿件说明：
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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：

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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