Full Text:   <701>

Summary:  <159>

CLC number: TN92

On-line Access: 2023-07-03

Received: 2023-03-21

Revision Accepted: 2023-07-03

Crosschecked: 2023-05-15

Cited: 0

Clicked: 591

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Ping ZHANG

https://orcid.org/0000-0002-1485-5849

Xiaodong XU

https://orcid.org/0000-0003-4245-5989

Chen DONG

https://orcid.org/0000-0002-3443-1453

Kai NIU

https://orcid.org/0000-0002-8076-1867

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Frontiers of Information Technology & Electronic Engineering  2023 Vol.24 No.6 P.801-812

http://doi.org/10.1631/FITEE.2300196


Model division multiple access for semantic communications


Author(s):  Ping ZHANG, Xiaodong XU, Chen DONG, Kai NIU, Haotai LIANG, Zijian LIANG, Xiaoqi QIN, Mengying SUN, Hao CHEN, Nan MA, Wenjun XU, Guangyu WANG, Xiaofeng TAO

Affiliation(s):  State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; more

Corresponding email(s):   pzhang@bupt.edu.cn, xuxiaodong@bupt.edu.cn, dongchen@bupt.edu.cn, niukai@bupt.edu.cn

Key Words:  Model division multiple access (MDMA), Semantic communication, Multiple access


Ping ZHANG, Xiaodong XU, Chen DONG, Kai NIU, Haotai LIANG, Zijian LIANG, Xiaoqi QIN, Mengying SUN, Hao CHEN, Nan MA, Wenjun XU, Guangyu WANG, Xiaofeng TAO. Model division multiple access for semantic communications[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(6): 801-812.

@article{title="Model division multiple access for semantic communications",
author="Ping ZHANG, Xiaodong XU, Chen DONG, Kai NIU, Haotai LIANG, Zijian LIANG, Xiaoqi QIN, Mengying SUN, Hao CHEN, Nan MA, Wenjun XU, Guangyu WANG, Xiaofeng TAO",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="24",
number="6",
pages="801-812",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300196"
}

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%A Chen DONG
%A Kai NIU
%A Haotai LIANG
%A Zijian LIANG
%A Xiaoqi QIN
%A Mengying SUN
%A Hao CHEN
%A Nan MA
%A Wenjun XU
%A Guangyu WANG
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A1 - Kai NIU
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A1 - Xiaoqi QIN
A1 - Mengying SUN
A1 - Hao CHEN
A1 - Nan MA
A1 - Wenjun XU
A1 - Guangyu WANG
A1 - Xiaofeng TAO
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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 multiple access (MDMA)%29&ck%5B%5D=abstract&ck%5B%5D=keyword'>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.

面向语义通信的模分多址技术

张平1,2,3,许晓东1,2,3,董辰1,牛凯1,2,梁灏泰1,梁子键1,秦晓琦1,孙梦颖1,陈昊2,马楠1,2,许文俊1,王光宇1,陶小峰2,4
1北京邮电大学网络与交换技术国家重点实验室,中国北京市,100876
2鹏城实验室宽带通信研究部,中国深圳市,518066
3中关村泛联移动通信技术创新应用研究院,中国北京市,100876
4北京邮电大学信息与通信工程学院,中国北京市,100876
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。

关键词:模分多址(MDMA);语义通信;多址技术

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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