Radio Resource Management for Joint Communication and Sensing (JCAS) Services in 6G Networks
G. Mazzola (TU Delft - Electrical Engineering, Mathematics and Computer Science)
R. Litjens – Mentor (TU Delft - Network Architectures and Services)
Kallol Das – Mentor (TNO)
Haibin Zhang – Mentor (TNO)
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Abstract
This thesis explores Radio Resource Management (RRM) techniques for Joint Communication and Sensing (JCAS) in beyond-5G/6G networks. JCAS integrates communication and sensing functionalities into a unified network, promising enhanced spectral efficiency, reduced system costs, and improved performance in various applications such as autonomous vehicles and smart cities. However, efficiently managing the dual requirements of communication and sensing in a shared network is a significant challenge, especially in dense, multi-cell environments.
The work presents a novel approach to JCAS by developing advanced resource management algorithms aimed at optimizing communication throughput and sensing accuracy, with a focus on target detection as the primary sensing task. The proposed algorithms encompass topology selection, dynamic node contribution management, and joint scheduling of sensing and communication tasks. Through extensive simulations, we analyze the trade-offs between communication and sensing performance, considering metrics such as the average and 10th percentile user throughput and probability of detection. The results demonstrate the effectiveness of the proposed strategies in managing interference and improving system performance in a cooperative multi-cell JCAS network.
This study contributes to the growing body of research on JCAS by addressing key limitations in existing works, such as the lack of cooperative sensing and the need for real-time dynamic resource allocation algorithms. The findings provide practical insights for network operators and lay the groundwork for future research into more complex JCAS applications and further optimization of resource management techniques.