Semantic Communications for High Volume Multimedia Content Delivery in 6G
March 21st, 2023 (GMT)
Department of Computer and Information Sciences, University of Strathclyde
Prof. Anil Fernando received the B.Sc. (Hons.) degree (First Class) in electronics and telecommunication engineering from the University of Moratuwa, Sri Lanka, in 1995, and the M.Sc. in Communications (Distinction) from the Asian Institute of Technology, Bangkok, Thailand in 1997 and Ph.D. in Computer Science (Video Coding and Communications) from the University of Bristol, UK in 2001. He is a professor in Video Coding and Communications at the Department of Computer and Information Sciences, University of Strathclyde, UK. He leads the video coding and communication research team at Strathclyde. He has worked on major national and international multidisciplinary research projects and led most of them. He has published over 400 papers in international journals and conference proceedings and published a book on 3D video broadcasting. He has been working with all major EU broadcasters, BBC, and major European media companies/SMEs in the last decade in providing innovative media technologies for British and EU citizens. His main research interests are in Video coding and Communications, Machine Learning (ML) and Artificial Intelligence (AI), Semantic Communications, Signal Processing, Networking and Communications, Interactive Systems, Resource Optimizations in 6G, Distributed Technologies, Media Broadcasting and Quality of Experience (QoE).
Mrs. Maheshi Lukumarambage
Mr. Yasith Ganearachchi
Mr. Vishnu Gowrisetty
Background:
Implementation of Semantic Communications for the general communications system is a Key challenge in the journey towards 6G. While promising significant improvements in channel bandwidth efficiency to go beyond what is generally considered as Shannon theory based communications, Semantic communications create new opportunities to modern high bandwidth applications. The need for a highly efficient communication model has become of paramount importance due to the exponential growth in data traffic on image transfers, streaming, video conferencing, and online learning, which consumes a significant amount of system resources and necessitates longer transmission and processing times. This workshop focuses on introducing the theory of Semantic communication in relation to multimedia content in a mobile communications system.
Goal/Rationale:
In conventional transmission systems, data transmission happens in bit level, where the source is converted into a bit sequence to be transmitted. This data would be text, audio, images, or video. At the receiver end, the bit sequence which represents the original source is recovered to represent the original data. There are many compression techniques developed to transmit data over limited bandwidth channels, but all existing compression and transmission techniques function within the Shannon capacity limit.
In contrast to the conventional transmission model, Semantic Communication models convey only the necessary information required for a specified task. Semantic communications convey the Semantic meanings of the original source over the physical communication channel and the receiver intelligently decodes the Semantic meaning of the transmitted labels to recover the source data. For instance, in image transmission, Semantic communication employs Semantic feature extraction of the original images which are of importance to a specified task.
Furthermore, proliferation of video-based machine-to-machine, machine-to-human, and human-to-machine communications (such as automated driving, factory automation, gaming, IoT, and remote sensing) further stresses the already bandwidth limited channel and new ways of designing of the communication systems to be employed. This workshop explains how Semantic communication can help in resolving these emerging problems in high volume media transmissions in limited bandwidth applications.
Scope and Information for Participants:
The objective of this workshop is to introduce Semantic communication theory and its importance in current high volume low bandwidth applications specially in mobile communications. During the session, potential practical applications of Semantic communication, its current limitations, and future direction will be discussed. In contrast to the conventional communication applications and data compression techniques, an increasing share of data content is analyzed by machines rather than humans, and hence the importance to optimize the transmission and compression techniques to suit the machines are discussed.
We expect to present our study on Semantic communication-based image transmission system architecture based on Generative Adversarial Network (GAN) which emphasizes the impact of the physical channel characteristics, specifically the channel noise and quantization noise, in Semantic communication systems used for image transmission.
Further, we will present a theoretical architecture that will utilize Semantic communication for the transmission of video content over a wireless communication channel.
Implementation of Semantic Communications for the general communications system is a key challenge in the journey towards 6G. While promising significant improvements in channel bandwidth efficiency to go beyond what is generally considered as Shannon theory-based communications, Semantic communications create new opportunities to modern high bandwidth applications. The need for a highly efficient communication model has become of paramount importance due to the exponential growth in data traffic on image transfers, streaming, video conferencing, and online learning, which consumes a significant amount of system resources and necessitates longer transmission and processing times. The objective of this workshop is to introduce Semantic communication theory and its importance in current high volume low bandwidth applications in mobile communications. During the session potential practical applications of Semantic communication, its current limitations, and future direction will be discussed. In contrast to the conventional communication applications and data compression techniques, an increasing share of data content is analyzed by machines rather than humans, and hence the importance to optimize the transmission and compression techniques to suit the machines also will be discussed.
University of Strathclyde, Glasgow, G1 1XQ, UK.
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