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IRS辅助的边缘智能系统中基于数据重要性感知的资源分配
引用本文:田辉,倪万里,王雯,郑景桁,贺硕.IRS辅助的边缘智能系统中基于数据重要性感知的资源分配[J].北京邮电大学学报,2020,43(6):51-58.
作者姓名:田辉  倪万里  王雯  郑景桁  贺硕
作者单位:1. 北京邮电大学 网络与交换技术国家重点实验室, 北京 100876;2. 郑州大学 信息工程学院, 郑州 450001
基金项目:国家重点研发计划项目(2019YFC1511400)
摘    要:针对智能反射面(IRS)辅助的边缘智能系统中模型参数汇聚的问题,提出一种基于数据重要性感知的资源分配算法.利用凸优化和分支定界等方法交替优化用户的发射功率、传输次数和智能反射面的相移矩阵.仿真结果表明,所提算法能够基于本地数据的重要性差异有效汇聚分布式智能体的模型参数,并最大化加权和速率.

关 键 词:智能反射面  模型汇聚  重要性感知  资源分配  
收稿时间:2020-09-02

Data-Importance-Aware Resource Allocation in IRS-Aided Edge Intelligent System
TIAN Hui,NI Wan-li,WANG Wen,ZHENG Jing-heng,HE Shuo.Data-Importance-Aware Resource Allocation in IRS-Aided Edge Intelligent System[J].Journal of Beijing University of Posts and Telecommunications,2020,43(6):51-58.
Authors:TIAN Hui  NI Wan-li  WANG Wen  ZHENG Jing-heng  HE Shuo
Affiliation:1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;2. School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China
Abstract:In order to solve the problem of model aggregation in intelligent reflecting surface (IRS) aided edge intelligent system, a data-importance-aware resource allocation algorithm is proposed by using convex optimization and branch-and-bound methods to alternately design the user's uplink power, transmission time, and the phase shifts of IRS. Simulation results show that the proposed algorithm can effectively aggregate the model parameters of the distributed agents based on the importance difference of local data, and can maximize the uplink weighted sum rate.
Keywords:intelligent reflecting surface  model aggregation  importance aware  resource allocation  
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