超密集工业物联网中基于超图匹配的频谱分配方法

王琴; 昌昊天; 朱洪波

doi:10.11959/j.issn.2096-3750.2025.00401

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超密集工业物联网中基于超图匹配的频谱分配方法

理论与技术 | 更新时间：2026-01-04

- 超密集工业物联网中基于超图匹配的频谱分配方法
- Spectrum allocation and device association in ultra-dense industrial IoT via hypergraph matching
- 物联网学报 2025年9卷第4期页码：29-39
- 作者机构：
  
  1.南京邮电大学物联网研究院，江苏南京 210003
  2.江苏省无线通信与物联网重点实验室，江苏南京 210003
  3.教育部泛在网络健康服务系统工程研究中心，江苏南京 210003
- 作者简介：
  
  [ "王琴（1988‒ ），女，博士，南京邮电大学副研究员、硕士生导师，主要研究方向为物联网、工业物联网、低空智联网、频谱智能认知与管理、资源博弈共享优化。" ]
  [ "昌昊天（2000‒ ），男，南京邮电大学硕士生，主要研究方向为频谱分配、超图理论以及多址接入技术。" ]
  [ "朱洪波（1956‒ ），男，《物联网学报》执行主编，南京邮电大学教授、物联网研究院院长，中国通信学会物联网专业委员会主任，中国电子学会通信分会主任，中国（无锡）物联网研究院院长，主要研究方向为无线通信网络、移动通信与物联网。" ]
- 基金信息：
  
  国家自然科学基金重大研究计划集成项目(92367302);江苏省重点研发计划项目(BE2022068;BE2022068-2);江苏省高等学校基础科学（自然科学）研究重大项目
- DOI：10.11959/j.issn.2096-3750.2025.00401
  中图分类号：
- 收稿：2024-04-23，
  
  修回：2024-07-11，
  
  纸质出版：2025-12-10
- 稿件说明：
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王琴,昌昊天,朱洪波.超密集工业物联网中基于超图匹配的频谱分配方法[J].物联网学报,2025,09(04):29-39.

WANG Qin,CHANG Haotian,ZHU Hongbo.Spectrum allocation and device association in ultra-dense industrial IoT via hypergraph matching[J].Chinese Journal on Internet of Things,2025,09(04):29-39.
王琴,昌昊天,朱洪波.超密集工业物联网中基于超图匹配的频谱分配方法[J].物联网学报,2025,09(04):29-39. DOI： 10.11959/j.issn.2096-3750.2025.00401.

WANG Qin,CHANG Haotian,ZHU Hongbo.Spectrum allocation and device association in ultra-dense industrial IoT via hypergraph matching[J].Chinese Journal on Internet of Things,2025,09(04):29-39. DOI： 10.11959/j.issn.2096-3750.2025.00401.

摘要

随着工业物联网（IIoT

industrial Internet of things）的快速发展，网络全要素各实体间的关系更加复杂、动态、多维，现有信息交互技术难以准确描述IIoT全要素的高密度、大规模和复杂的交互关系。针对宏小区场景中网络实体间资源分配的关联关系，构建了基于超图的宏小区速率和最大化问题。在该场景中，采用非正交多址接入（NOMA

non-orthogonal multiple access）技术支持IIoT设备的多址接入，同时引入设备直连（D2D

device-to-device）通信技术以降低设备之间的干扰并提高频谱效率。在构建宏小区飞蜂窝基站及其内部设备之间的超图干扰模型时，将飞蜂窝接入点（FAP

femtocell access point）定义为顶点，干扰关系定义为边和超边，通过分析超图中的超边关系，让产生较少干扰的基站共享同一频谱，并采用基于超图的最大顶点权重团算法，实现频谱资源最优分配及频谱共享匹配。仿真结果表明，相比于基于图的资源方案，该方法可以显著提高频谱效率，并且在高密度、大规模和复杂的环境下具有较好的适应性和可扩展性，为IIoT在超密集无线网络环境下的资源分配问题提供了有效解决方案。

Abstract

With the rapid development of industrial Internet of thing (IIoT)

the relationship between all entities of the network elements became more complex

dynamic and multidimensional. It was difficult to accurately describe the high-density

large-scale and complex interaction relationship of all elements in IIoT through existing information interaction technology. Focusing on the interrelation of resource allocation among network entities in macrocell scenarios

sum-rate maximizing problem in IIoT macrocell based on hypergraph was studied and constructed. Non-orthogonal multiple access (NOMA) technology was considered in this scenario to support multiple access between industrial Internet devices. Device-to-device (D2D) communication technology was introduced to reduce interference between devices and improve spectral efficiency. When constructing the interference model among femtocells and their internal devices

the femtocell access points (FAP) were defined as vertices

and the interference relationships were defined as edges and hyperedges. By analyzing the hyperedge relationships in the hypergraph

base stations causing less interference were allowed to share the same spectrum

and a maximum vertex-weight cluster algorithm based on the hypergraph was used to achieve optimal spectrum resource allocation and spectrum sharing matching. Simulation results demonstrated that

compared to graph-based resource schemes

the proposed method significantly improves spectral efficiency and exhibits better adaptability and scalability in high-density

large-scale

and complex environments

providing an effective solution for resource allocation in IIoT under ultra-dense wireless network conditions.

关键词

Keywords

references

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