Special Session on Spectrum Sensing and Resource Utilization for Efficient 6G Radio Access

The capabilities of modern information and communication technologies (ICTs) provide numerous advantages for many industrial areas, such as labour automation, leisure, transport, trade, tourism, and healthcare. Scientific progress is pushing not only their development but also the convergence of current communication systems together with the emerging ones, to provide uninterrupted and satisfactory service for various applications, such as vehicle-to-vehicle (V2V) communications, enhanced mobile broadband connections, user-centric ultra-dense networks, Internet of Things (IoT), integrated space and terrestrial networks, links between unmanned aerial vehicle (UAV) assisted networks, and emergency communications.
One of the biggest challenges for realizing these applications is spectrum utilization efficiency, closely related to spectrum sensing, resource allocation and quality of user experience, node deployment density, and computationally efficient algorithms. The application of radio environment maps (REMs) has been established as an important capability in many scenarios, such as spectrum sharing for cognitive radio (CR), UAV-based spectrum monitoring, coverage prediction for optimizing communications in V2V and mobile networks. REMs enable smarter resource allocation, predicting both network state and user association. The Special Session on Spectrum Sensing and Resource Utilization for Efficient 6G Radio Access welcomes novel research that advances the fields of CR communications, REM reconstruction and UAV-assisted networks using Machine Learning (ML) and Artificial Intelligence (AI) in various deployment scenarios for beyond 5G.

This Special Session focuses on the following topics:

• Spectrum Sensing for Radio Frequency Monitoring and CR/IoT Applications
• UAV-assisted Networks
• V2V Communications
• Software-Defined Radio Applications for CR
• Spectrum Sharing and multi-Radio Access Technology Coexistence
• Multi-dimensional REM Reconstruction
• AI/ML methods for RF Signal Processing and Resource Allocation

Special Session on Sustainable Future Communication Networks and Technologies (GREENBEAT)

The project GREENBEAT is a pioneering initiative that aligns with the European Green Deal’s goals of achieving carbon neutrality by 2050 and prioritizing sustainability in economic policy. While digital technologies, especially in ICT and wireless networks, have contributed positively to sustainability, there’s a need for continuous improvement in energy efficiency and minimizing environmental impact. GREENBEAT envisions a future where technology development is aligned with societal needs and values, focusing on human-centric design and responsible resource usage. Moreover, GREENBEAT recognizes the imperative of enhancing user experience in future networks, emphasizing sustainability and trustworthiness while meeting escalating demands for data rates and capacity. By harnessing AI-aided network operations and spectrum utilization, GREENBEAT endeavors to pave the way for economically viable and sustainable deployments of 6G networks. The GREENBEAT Workshop/Special Session welcomes pivotal research that integrates cutting-edge technologies like Artificial Intelligence (AI) and Machine Learning (ML) into communication networks to enable ubiquitous, real-time, and trustworthy connectivity across devices with diverse requirements and capabilities.

This Special Session focuses on the following topics:

• AI/ML methods for intelligent signal processing in Wireless Communications
• Software-Defined Radio and Cognitive Radio Networks
• Unmanned Aerial Vehicle (UAV)-assisted Wireless Networks
• Human-centric Wireless Networks
• Multiple Access and Resource Allocation in 5G and Beyond
• Privacy Enhancing Technologies (PETs) and adversarial attacks mitigation
• Green business modeling and innovation