Projects per year
5G New Radio (NR) introduces several key features to support the new emerging vertical industry use-cases, mainly: (1) Different numerology that gives more flexibility in managing time slot duration, and hence satisfying different delay requirements; (2) Bandwidth part that permits dedicating parts of the bandwidth to ensure different data rate requirements. However, although 5G NR introduces several enhancements, it makes radio resource management, more precisely resource scheduling, more complex and challenging. In this paper, we address the challenge of radio resource management in 5G NR featuring network slicing. We introduce a novel scheduling solution based on Deep Reinforcement Learning (DRL) to allocate resources and numerology for UEs to satisfy their different requirements. We evaluated the solution for different network configurations and compared its performance with the maximum achievable throughput. Simulation results demonstrated the efficiency of the proposed algorithm to allocate resources and the ability to scale for larger bandwidths covering both Frequency Range 1 (FR1) and FR2, as well as serving a higher number of User Equipment (UE).
|Title of host publication||ICC 2022 - IEEE International Conference on Communications|
|Number of pages||6|
|Publication status||Published - 2022|
|MoE publication type||A4 Article in a conference publication|
|Event||IEEE International Conference on Communications - Seoul, Korea, Republic of|
Duration: 16 May 2022 → 20 May 2022
|Name||IEEE International Conference on Communications|
|Conference||IEEE International Conference on Communications|
|Country/Territory||Korea, Republic of|
|Period||16/05/2022 → 20/05/2022|
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- 1 Finished
5G!Drones: Unmanned Aerial Vehicle Vertical Applications' Trials Leveraging Advanced 5G Facilities
Taleb, T., Abada, A., Bekkouche, O., Dang, Y., Manner, J., Hireche, O., Rajasekaran, A., Hellaoui, H., Khennouche, H., Meles, M., Shahbaztabar, D., Knuuttila, O. & Sehad, N.
01/06/2019 → 30/11/2022
Project: EU: Framework programmes funding