智能网联环境下面向语义通信的资源分配

陈九九; 郭彩丽; 冯春燕; 刘传宏

doi:10.11959/j.issn.2096-3750.2022.00279

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智能网联环境下面向语义通信的资源分配

理论与技术 | 更新时间：2024-06-05

- 智能网联环境下面向语义通信的资源分配
- Resource allocation for the semantic communication in the intelligent networked environment
- 物联网学报 2022年6卷第3期页码：47-57
- 作者机构：
  
  1. 北京邮电大学先进信息网络北京实验室，北京 100876
  2. 北京邮电大学网络体系构建与融合北京市重点实验室，北京 100876
- 作者简介：
  
  [ "陈九九（1994- ），男，北京邮电大学博士生，主要研究方向为车联网资源分配、语义通信、强化学习算法等" ]
  [ "郭彩丽（1977- ），女，博士，北京邮电大学教授、博士生导师，主要研究方向为语义通信、无线移动通信技术、认知无线电、信号检测与估值、车联网、可见光通信、视觉智能计算、社交跨媒体数据挖掘与分析等" ]
  [ "冯春燕（1963- ），女，博士，北京邮电大学教授、博士生导师，主要研究方向为无线通信信息传输与处理、宽带通信网络理论与技术、社交网络分析和信息检索、电信大数据分析与挖掘等" ]
  [ "刘传宏（1998- ），男，北京邮电大学博士生，主要研究方向为深度学习、语义通信、资源分配等" ]
- 基金信息：
  
  北京市自然科学基金资助项目;The Beijing Natural Science Foundation(4202049);中央高校基本科研业务费专项资金资助项目;The Fundamental Research Funds for the Central Universities(2021XD-A01-1)
- DOI：10.11959/j.issn.2096-3750.2022.00279
  中图分类号： TN929.5
- 纸质出版日期：2022-09-30，
  
  网络出版日期：2022-09，
- 稿件说明：
移动端阅览
陈九九, 郭彩丽, 冯春燕, 等. 智能网联环境下面向语义通信的资源分配[J]. 物联网学报, 2022,6(3):47-57.

JIUJIU CHEN, CAILI GUO, CHUNYAN FENG, et al. Resource allocation for the semantic communication in the intelligent networked environment. [J]. Chinese journal on internet of things, 2022, 6(3): 47-57.
陈九九, 郭彩丽, 冯春燕, 等. 智能网联环境下面向语义通信的资源分配[J]. 物联网学报, 2022,6(3):47-57. DOI： 10.11959/j.issn.2096-3750.2022.00279.

JIUJIU CHEN, CAILI GUO, CHUNYAN FENG, et al. Resource allocation for the semantic communication in the intelligent networked environment. [J]. Chinese journal on internet of things, 2022, 6(3): 47-57. DOI： 10.11959/j.issn.2096-3750.2022.00279.

摘要

传统的资源分配方法难以满足智能网联环境下各种业务准确理解大量多媒体数据语义的需求。针对该挑战，以智能任务导向的车联网场景为例，首先，提出了两种面向语义通信的资源分配优化准则；然后，针对不同维度的资源，综述了面向语义通信的资源分配模型与算法；构建了面向语义通信的图像数据集，在车联网仿真场景下分析了所研究资源分配方法的性能优势；最后，给出了语义通信资源分配的未来挑战。

Abstract

Traditional resource allocation methods are difficult to meet the needs of various services to accurately understand the semantics of a large amount of multimedia data in the intelligent networked environment.Facing with this challenge

taking intelligent task-oriented internet of vehicles scenarios as an example

two resource allocation optimization criteria for the semantic communication were firstly proposed.Then

according to different dimensions of resources

the models and algorithms of the resource allocation for the semantic communication were described.Then

a semantic communication-oriented image dataset was constructed

and the performance advantages of the proposed resource allocation methods in the simulation scenario of the internet of vehicles were analyzed.Finally

the future challenges of the resource allocation for the semantic communication were presented.

关键词

语义通信资源分配智能网联优化准则强化学习

Keywords

semantic communicationresources allocationintelligent networked connectionoptimization criteriareinforcement learning

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