Demo: Real-Time Semantic Communications with a Vision Transformer

Hanju Yoo, Taehun Jung, Linglong Dai, Songkuk Kim, Chan Byoung Chae

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Semantic communications are expected to enable the more effective delivery of meaning rather than a precise transfer of symbols. In this paper, we propose an end-To-end deep neural network-based architecture for image transmission and demonstrate its feasibility in a real-Time wireless channel by implementing a prototype based on a field-programmable gate array (FPGA). We demonstrate that this system outperforms the traditional 256-quadrature amplitude modulation system in the low signal-To-noise ratio regime with the popular CIFAR-10 dataset. To the best of our knowledge, this is the first work that implements and investigates real-Time semantic communications with a vision transformer.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665426718
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022 - Seoul, Korea, Republic of
Duration: 2022 May 162022 May 20

Publication series

Name2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
Volume2022-January

Conference

Conference2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
Country/TerritoryKorea, Republic of
CitySeoul
Period22/5/1622/5/20

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Control and Optimization

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