| 引用本文: |
马文峰1，吴霞2，王聪1，田辉1，赵几航3，姚远翔1.H2H与M2M共存场景下无人机辅助上行用户调度方案[J].陆军工程大学,2023,(2):46-53
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| H2H与M2M共存场景下无人机辅助上行用户调度方案 |
| 马文峰1，吴霞2，王聪1，田辉1，赵几航3，姚远翔1 |
| (1 . 陆军工程大学 野战工程学院, 江苏 南京 210007 ; 2.31131 部队, 江苏 南京 210007 ; 3 .31603 部队, 江苏 徐州 221000) |
| 摘要:针对人类用户和物联网用户共存时利用无人机作为中继节点采集物联网设备数据的场景，提出了一种基于累积分布函数的上行用户调度方案。方案在以最大化全网节点能效为优化目标的上行联合用户关联和用户资源分配问题建模过程中，考虑多用户分集以及网络负载均衡；为了求解该问题，方案利用用户吞吐量独立同分布的特点，通过松弛整数变量，结合增广拉格朗日法和标准的次梯度法，将难解的非凸问题转化为凸函数，再利用交替方向乘子法对凸问题进行分解并交替迭代优化，最终实现系统能效最大化并得到最优调度方案。仿真结果表明，该方案在全网效能和负载均衡方面优于现有方案。 |
| 关键词: 异构网络 用户调度 无人机 物联网 能量效率 |
| DOI：10.12018/j .issn.2097-0730.20220407006 |
| 投稿时间：2022-04-07 |
| 基金项目:国家自然科学基金(62001515 ,61771486 ,62103441) ; 江苏省博士后科研资助计划(2019K090) |
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| UAV-Assisted Uplink User Scheduling Scheme in H2H and M2M Coexistence Scenarios |
| MA Wenfeng1 , WU Xia2 , WANG Cong1 , TIAN Hui1 , ZHAO Jihang3 , YAO Yuanxiang1 |
| (1 . College of Field Engineering,Army Engineering University of PLA,Nanjing 210007 ,China;
2. Unit 31131 of PLA,Nanjing 210007 ,China; 3 . Unit 31603 of PLA,Xuzhou 221000,China) |
| Abstract: Aiming at the scenarios where UAVs are used as relay nodes to collect the data of internet of things （IoT） devices when human-to-human (H2H) and machine-to-machine (M2M) users coexist, an uplink user scheduling scheme based on the cumulative distribution function is proposed. Multi-user diversity and network load balancing are considered in the modeling process of uplink joint user association and user resource allocation with the optimization goal of maximizing the energy efficiency of nodes in the entire network. In order to solve the problem, the scheme utilizes the characteristics of independence and identical distribution of user throughput, relaxes integer variables, combines the augmented Lagrangian method and the standard subgradient method, transforms the difficult non-convex problem into a convex function, then uses the alternating direction multiplier method to decompose the convex problem and alternately iteratively optimizes it, and finally realizes the maximum energy efficiency of the system and obtains the optimal scheduling scheme. Simulation results indicate that the scheme is superior to existing schemes in terms of network performance and load balancing. |
| Key words: heterogeneous network user scheduling UAV Internet of Things energy efficiency |
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