Semantic Communication based Complexity Scalable M2M Video Transmission System for Resource Constrained Devices in Wireless Channels

The use of multimedia services for everyday activities such as pictures, streaming, broadcasting, teleconferencing, video on-demand, and peer-to-peer video sharing has undergone unprecedented growth in recent years. It has been forecasted that in 2024 almost 95% of global data traffic will either be image or video, which is mainly fueled by vast numbers

of consumer communication devices being introduced to the market, coupled with the users' higher consumption

of multimedia services. Crucially, the quality of the received media is of prime importance to users, as well as service providers, irrespective of where they are generated from and how the users are connected to the service. Since these users are increasingly mobile, providing the necessary capacity to handle this ever-increasing media traffic poses

significant challenges for the future communications infrastructure, especially in mobile-wireless systems where spectrum capacity and device resources (e.g., battery capacity) are limited. A key emerging challenge with this surge in multimedia traffic is one of the biggest problems in sustainability. The

increasingly complex nature of information and communication technologies (ICT) has led to an enormous increase in resource demands. Sustainability needsto be applied pervasively across all areas of ICT and bring about a significant overall reduction in the negative impact of ICT on the environment. Harnessing novel approaches to modeling,

materials, manufacturing, and power management are all necessary to implement this vision. The systemic nature of ICT means it is ideally placed to undergo a complete reformation in its practices. A key requirement for this

transformation is minimizing the energy footprint of wireless networks such as B5G and 6G systems under ever increasing traffic load with such surging multimedia traffic. Furthermore, due to the millions of resource constrained devices connected to the network in the recent past and most of them are either transmitting or receiving images or

videos, further amplified the multimedia traffic on wireless networks. These services and networks are also supposed to

support intelligent and adaptive operations using complex and pervasive artificial intelligence (AI) and machine learning (ML) control frameworks, which even increases resource consumption. Accordingly, the efficiency of AI/ML and the quantification of its actual gains when properly employed is a very interesting and open research question. On the

service consumption side, devices such as Wireless Sensor Networks (WSN) and Internet of Things (IoT) have limited system resources such as bandwidth, and energy capacity, endangering the robustness of digital services under different constraints. In that regard, resource efficiency for sustainability and robustness has become an important research

topic for sustainable B5G and 6G intelligent networks.