User-centric energy efficiency fairness in backscatter-assisted wireless powered communication network

Yinghui YE; Liqin SHI; Guangyue LU

doi:10.11959/j.issn.1000-436x.2020133

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User-centric energy efficiency fairness in backscatter-assisted wireless powered communication network

Papers | 更新时间：2024-06-05

- User-centric energy efficiency fairness in backscatter-assisted wireless powered communication network
- Journal on Communications Vol. 41, Issue 7, Pages: 84-94(2020)
- 作者机构：
  
  西安邮电大学陕西省信息通信网络及安全重点实验室，陕西西安 710121
- 作者简介：
- 基金信息：
  
  The Science and Technology Innovation Team of Shaanxi Province(2017KCT-30-02);The National Natural Science Foundation of China(61901370)
- DOI：10.11959/j.issn.1000-436x.2020133
  CLC： TN92
- Online First：2020-07，
  
  Published：25 July 2020
- 稿件说明：
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Yinghui YE, Liqin SHI, Guangyue LU. User-centric energy efficiency fairness in backscatter-assisted wireless powered communication network[J]. Journal on Communications, 2020, 41(7): 84-94.
DOI：

Yinghui YE, Liqin SHI, Guangyue LU. User-centric energy efficiency fairness in backscatter-assisted wireless powered communication network[J]. Journal on Communications, 2020, 41(7): 84-94. DOI： 10.11959/j.issn.1000-436x.2020133.

摘要

针对反向散射辅助的无线供能通信网络中由于信道质量差异导致的用户能效不公平问题，提出了一种基于最大最小准则的资源分配方法。首先，考虑用户服务质量与能量因果约束，并以最大最小化用户能效为目标，将优化问题建模为混合整数非凸分式规划问题。其次，利用广义分式规划理论将其转化为一个混合整数非凸减式优化问题，并通过引入松弛变量、反证法和辅助变量将非凸减式问题进一步转化为一个等价的凸问题。最后，提出一种迭代算法来获取原优化问题的最优解。实验仿真验证了所提迭代算法的快速收敛性，并证明了所提资源分配方法能够有效地保障用户能效公平性。

Abstract

In order to address the unfair user-centric energy efficiency (EE) problem caused by channel difference in the backscatter-assisted wireless powered communication network

a resource allocation scheme was proposed.Firstly

a mixed integer nonconvex fractional programming problem was formulated to maximize the minimum user-centric EE

subject to the quality of service and energy-causality constraints.Based on the generalized fractional programming theory

the original problem was transformed into a mixed integer nonconvex subtraction problem.With the aid of the slack variable

the proof by contradiction

the auxiliary variable and the mixed integer nonconvex subtraction problem were further transformed into an equivalent convex problem.Finally

an iterative algorithm was proposed to obtain the optimal solutions.Computer simulations validated the quick convergence of the proposed iterative algorithm

and that the developed resource allocation scheme efficiently guarantees the fairness among users in terms of EE.

关键词

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references

张平 , 牛凯 , 田辉 , 等 . 6G 移动通信技术展望 [J ] . 通信学报 , 2019 , 40 ( 1 ): 141 - 148 .

ZHANG P , NIU K , TIAN H , et al . Technology prospect of 6G mobile communications [J ] . Journal on Communications , 2019 , 40 ( 1 ): 141 - 148 .

ZHANG L , LIANG Y , NIYATO D . 6G visions:mobile ultra-broadband,super Internet-of-things,and artificial intelligence [J ] . China Communications , 2019 , 16 ( 8 ): 1 - 14 .

CHOI K W , GINTING L , AZIZ A A , et al . Toward realization of long-range wireless-powered sensor networks [J ] . IEEE Wireless Communications , 2019 , 26 ( 4 ): 184 - 192 .

徐勇军 , 胡圆 , 李国权 , 等 . 异构携能通信网络顽健资源分配算法 [J ] . 通信学报 , 2019 , 40 ( 7 ): 186 - 196 .

XU Y J , HU Y , LI G Q , et al . Robust resource allocation algorithm for heterogeneous wireless network with SWIPT [J ] . Journal on Communications , 2019 , 40 ( 7 ): 186 - 196 .

王公仆 , 熊轲 , 刘铭 , 等 . 反向散射通信技术与物联网 [J ] . 物联网学报 , 2017 , 1 ( 1 ): 67 - 75 .

WANG G P , XIONG K , LIU M , et al . Backscatter communication technology and Internet of things [J ] . Chinese Journal on Internet of Things , 2017 , 1 ( 1 ): 67 - 75 .

YE Y , SHI L , HU R , et al . Energy-efficient resource allocation for wirelessly powered backscatter communications [J ] . IEEE Communications Letters , 2019 , 23 ( 8 ): 1418 - 1422 .

谢天怡 , 吕斌 , 杨真真 . 反向散射通信辅助的认知无线能量通信网络的时间分配研究 [J ] . 信号处理 , 2018 , 34 ( 1 ): 98 - 106 .

XIE T Y , LYU B , YANG Z Z . Time allocation optimization in backscatter assisted cognitive wireless powered communication networks [J ] . Journal of Signal Processing , 2018 , 34 ( 1 ): 98 - 106 .

HUYNH N V , HOANG D T , LU X , et al . Ambient backscatter communications:a contemporary survey [J ] . IEEE Communications Surveys Tutorials , 2018 , 20 ( 4 ): 2889 - 2922 .

HOANG D T , NIYATO D , WANG P , et al . Ambient backscatter:a new approach to improve network performance for RF-powered Cognitive Radio Networks [J ] . IEEE Transactions on Communications , 2017 , 65 ( 9 ): 3659 - 3674 .

HOANG D T , NIYATO D , WANG P , et al . Optimal time sharing in RF-powered backscatter cognitive radio networks [C ] // 2017 IEEE International Conference on Communications . Piscataway:IEEE Press , 2017 : 1 - 6 .

LYU B , GUO H , YANG Z , et al . Throughput maximization for hybrid backscatter assisted cognitive wireless powered radio networks [J ] . IEEE Internet of Things Journal , 2018 , 5 ( 3 ): 2015 - 2024 .

KIM S H , KIM D I . Hybrid backscatter communication for wireless-powered heterogeneous networks [J ] . IEEE Transactions on Wireless Communications , 2017 , 16 ( 10 ): 6557 - 6570 .

LU X , JIANG H , NIYATO D , et al . Wireless-powered device-to-device communications with ambient backscattering:performance modeling and analysis [J ] . IEEE Transactions on Wireless Communications , 2018 , 17 ( 3 ): 1528 - 1544 .

LU X , LI G , JIANG H , et al . Performance analysis of wireless-powered relaying with ambient backscattering [C ] // 2018 IEEE International Conference on Communications . Piscataway:IEEE Press , 2018 : 1 - 6 .

KISHORE R , GURUGOPINATH S , SOFOTASIOS P C , et al . Opportunistic ambient backscatter communication in RF-powered cognitive radio networks [J ] . IEEE Transactions on Cognitive Communications and Networking , 2019 , 5 ( 2 ): 413 - 426 .

POULLIE P , BOCEK T , STILLER B . A survey of the state-of-the-art in fair multi-resource allocations for data centers [J ] . IEEE Transactions on Network and Service Management , 2018 , 15 ( 1 ): 169 - 183 .

VALENTA C R , DURGIN G D . Harvesting wireless power:survey of energy-harvester conversion efficiency in far-field,wireless power transfer systems [J ] . IEEE Microwave Magazine , 2014 , 15 ( 4 ): 108 - 120 .

BOSHKOVSKA E , NG D W K , ZLATANOV N , et al . Practical non-linear energy harvesting model and resource allocation for SWIPT systems [J ] . IEEE Communications Letters , 2015 , 19 ( 12 ): 2082 - 2085 .

ISMAIL M , ZHUANG W , SERPEDIN E , et al . A survey on green mobile networking:from the perspectives of network operators and mobile users [J ] . IEEE Communications Surveys Tutorials , 2015 , 17 ( 3 ): 1535 - 1556 .

YANG H , YE Y , CHU X . Max-min energy-efficient resource allocation for wireless powered backscatter networks [J ] . IEEE Wireless Communications Letters , 2020 , 9 ( 5 ): 688 - 692 .

JIA Y , ZHAO M , ZHOU W . Joint user association and eICIC for max-min fairness in hetnets [J ] . IEEE Communications Letters , 2016 , 20 ( 3 ): 546 - 549 .

ZHENG L , CAI D W H , TAN C W . Max-min fairness rate control in wireless networks:optimality and algorithms by perron-frobenius theory [J ] . IEEE Transactions on Mobile Computing , 2018 , 17 ( 1 ): 127 - 140 .

DINKELBACH . On nonlinear fractional programming [J ] . Manage , 1967 , 13 ( 7 ): 492 - 498 .

BOYD S , VANDENBERGHE L . Convex optimization [M ] . Cambridge : Cambridge University PressPress , 2004 .

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