面向语义通信的模分多址技术

张平; 许晓东; 董辰; 牛凯; 梁灏泰; 梁子键; 秦晓琦; 孙梦颖; 陈昊; 马楠; 许文俊; 王光宇; 陶小峰

doi:10.1631/FITEE.2300196

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面向语义通信的模分多址技术

常规文章 | Updated：2023-07-03

- 面向语义通信的模分多址技术
  Cover Article
- Model division multiple access for semantic communications
- 信息与电子工程前沿（英文） 2023年24卷第6期页码：801-812
- Affiliations：
  
  1.State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  2.Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen 518066, China
  3.ZGC Institute of Ubiquitous-X Innovation and Applications, Beijing 100876, China
  4.School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
- Author bio：
  
  †E-mail: pzhang@bupt.edu.cn;
  xuxiaodong@bupt.edu.cn;
  ‡Corresponding authors
- Funds：
  
  National Key R&D Program of China(2022YFB2902102)
- DOI：10.1631/FITEE.2300196
  中图分类号： TN92
- 收稿：2023-03-21，
  
  录用：2023-05-15，
  
  网络出版：2023-06-02，
  
  纸质出版：2023-06-0
- Accepted：
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张平, 许晓东, 董辰, 等. 面向语义通信的模分多址技术[J]. 信息与电子工程前沿（英文）, 2023,24(6):801-812.

Ping ZHANG, Xiaodong XU, Chen DONG, et al. Model division multiple access for semantic communications[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(6): 801-812.
张平, 许晓东, 董辰, 等. 面向语义通信的模分多址技术[J]. 信息与电子工程前沿（英文）, 2023,24(6):801-812. DOI： 10.1631/FITEE.2300196.

Ping ZHANG, Xiaodong XU, Chen DONG, et al. Model division multiple access for semantic communications[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(6): 801-812. DOI： 10.1631/FITEE.2300196.

摘要

在多用户系统中，系统资源应分配给不同用户。在传统通信系统中，系统资源通常包括时间、频率、空间和功率，因此广泛使用诸如时分多址（TDMA）、频分多址（FDMA）、空分多址（SDMA）、码分多址（CDMA）、非正交多址（NOMA）之类多址技术。在被认为是下一代通信系统新范式的语义通信中，我们从语义角度，以基于模型的人工智能方法，从信源中提取高维语义域特征，并针对信源和信道特征联合构建模型信息空间。从模型信息空间中挖掘语义信息的共性化和个性化信息，提出一种新的基于语义域资源的多址技术，称为模分多址（MDMA）。从信息论角度，证明模分多址比传统多址技术获得更多性能提升。仿真结果表明，模分多址比传统多址技术节省更多带宽资源，并且在低信噪比条件下，在加性高斯白噪声（AWGN）信道中，相比非正交多址具有至少5 dB的性能优势。

Abstract

In a multi-user system

system resources should be allocated to different users. In traditional communication systems

system resources generally include time

frequency

space

and power

so multiple access technologies such as time division multiple access (TDMA)

frequency division multiple access (FDMA)

space division multiple access (SDMA)

code division multiple access (CDMA)

and non-orthogonal multiple access (NOMA) are widely used. In semantic communication

which is considered a new paradigm of the next-generation communication system

we extract high-dimensional features from signal sources in a model-based artificial intelligence approach from a semantic perspective and construct a model information space for signal sources and channel features. From the high-dimensional semantic space

we excavate the shared and personalized information of semantic information and propose a novel multiple access technology

named model division multiple access (MDMA)

which is based on the resource of the semantic domain. From the perspective of information theory

we prove that MDMA can attain more performance gains than traditional multiple access technologies. Simulation results show that MDMA saves more bandwidth resources than traditional multiple access technologies

and that MDMA has at least a 5-dB advantage over NOMA in the additive white Gaussian noise (AWGN) channel under the low signal-to-noise (SNR) condition.

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