北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2021, Vol. 44 ›› Issue (6): 26-32.doi: 10.13190/j.jbupt.2021-096

• 论文 • 上一篇    下一篇

认知反向散射网络通信容量公平的资源优化

高晓娜, 卢光跃, 叶迎晖, 昝金枚   

  1. 西安邮电大学 陕西省信息通信网络及安全重点实验室, 西安 710121
  • 收稿日期:2021-05-26 出版日期:2021-12-28 发布日期:2021-12-28
  • 通讯作者: 叶迎晖(1991—),男,副教授,E-mail:connectyyh@126.com. E-mail:connectyyh@126.com
  • 作者简介:高晓娜(1996—),女,硕士生.
  • 基金资助:
    陕西省教育厅科研计划项目(21JK0914);陕西省重点科技创新团队计划基金资助项目(2017KCT-30-02);陕西省高校科协青年人才托举计划项目(20210121)

Throughput Fairness Guarantee in Cognitive Backscattering Networks

GAO Xiao-na, LU Guang-yue, YE Ying-hui, ZAN Jin-mei   

  1. Shaanxi Key Laboratory of Information Communication Network and Security, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
  • Received:2021-05-26 Online:2021-12-28 Published:2021-12-28

摘要: 为保证认知反向散射通信网络中物联网节点通信容量的公平性,提出一种基于最大最小准则的资源分配方案. 在考虑物联网节点动态电路能耗模型与非线性能量收集模型的基础上,通过联合优化发射功率、反射及时间分配系数构建一个最大最小物联网节点通信容量的非凸多维资源分配问题. 首先,采用反证法、连续凸近似及辅助变量等方法将原问题转换为凸优化问题;然后提出一种迭代算法来求解转换问题. 仿真结果表明,所提的资源分配方案在提升物联网节点通信容量的同时保障了节点通信的公平性.

关键词: 反向散射, 资源分配, 能量收集, 电路能耗, 公平性

Abstract: To guarantee the throughput fairness among Internet of things (IoT) nodes in cognitive backscatter communication networks, a resource allocation scheme based on max-min criterion is proposed. Based on the dynamic circuit energy consumption model and the nonlinear energy harvesting model of IoT nodes, a non-convex multi-dimensional resource allocation problem is formulated, in which the communication capacity is maximized by jointly optimizing the transmitting power, reflection coefficient and time division. First, the contradiction, successive convex approximation and auxiliary variables method are used to transform the original problem into a convex optimization problem. Then, an iterative algorithm is proposed to solve the transformed problem. Simulation results show the proposed resource allocation scheme improves the communication capacity of IoT nodes while guaranteeing the throughput fairness among IoT nodes.

Key words: backscatter communications, resource allocation, energy harvesting, dynamic energy consumption, fairness

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