Next Generation Multimodal Semantic Communication Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 494

Special Issue Editors

The State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, China
Interests: multimodal data fusion; cross-modal information retrieval; multimedia semantic communication

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Guest Editor
The State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, China
Interests: multimedia big data analysis; cognitive radio; interference mitigation; resource allocation; deep reinforcement learning; graph convolutional network; dynamic graph; end-to-end learning model

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Guest Editor
Information Department, Beijing University of Technology, Beijing 100124, China
Interests: future network; multimodal network transmission optimization

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Guest Editor
Department of Informatics, University of Oslo, 0316 Oslo, Norway
Interests: mobile edge computing; artificial intelligence
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Special Issue Information

Dear Colleagues, 

In the era of Internet of Everything, communication plays an important role in the collaborative computing tasks of multiple sensors and computing resources. It is necessary to study multimodal semantic communication in the future IoT paradigm, which dynamically adjusts the multimodal information (image, text, video, etc.) transmission strategy adapted to the task objective and the underlying changes in the communication environments.

In recent years, with the rapid development of deep learning, mobile edge computing, deep reinforcement learning, semantic communication, and other fields, traditional communication techniques have not been able to meet the requirements of large bandwidth and low delay in the next generation networks. Meanwhile, the semantic communication framework has shown its potential advantages in many fields, such as video conferencing and remote sensing, etc. Therefore, new algorithms, including multimodal data semantic understanding and processing, joint source-channel coding, etc., should be explored.

The main aim of this Special Issue is to seek high-quality submissions that highlight emerging theories and applications with advanced multimodal semantic communication networks and address recent breakthroughs from a theoretical and practical perspective. The topics of interest include, but not limited to:

  • Cross-modal semantic analysis;
  • Context awareness algorithms based on multimodal data;
  • Task-oriented multimodal data transmission;
  • Multitask semantic communications;
  • Multimodal data fusion;
  • Joint source-channel coding;
  • Multimodal remote sensing data processing;
  • AI-driven semantic communication networks.

Dr. Jie Guo
Prof. Dr. Bin Song 
Dr. Ru Huo
Dr. Dapeng Lan
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • multimodal data fusion
  • semantic communication
  • semantic understanding
  • joint optimization algorithms

Published Papers

There is no accepted submissions to this special issue at this moment.
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