TY  - INPR
N2  - This paper studies multiuser immersive communications networks in which different user equipment may demand various extended reality (XR) services. In such heterogeneous networks, time-frequency resource allocation needs to be more adaptive since XR services are usually multi-modal and latency-sensitive. To this end, we develop a scalable time-frequency resource allocation method based on multi-numerology and mini-slot. To appropriately determining the discrete parameters of multi-numerology and mini-slot for multiuser immersive communications, the proposed method first presents a novel flexible time-frequency resource block configuration, then it leverages the deep reinforcement learning to maximize the total quality-of-experience (QoE) under different users’ QoE constraints. The results confirm the efficiency and scalability of the proposed time-frequency resource allocation method.
UR  - https://doi.org/10.1109/LCOMM.2024.3370915
Y1  - 2024/02/28/
JF  - IEEE Communications Letters
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
TI  - Scalable Multiuser Immersive Communications with Multi-numerology and Mini-slot
AV  - public
ID  - discovery10189450
SN  - 1089-7798
KW  - Immersive communications
KW  -  
quality of experience
KW  -  
numerology
KW  -  
mini-slot
A1  - Hu, M
A1  - Peng, J
A1  - Wang, L
A1  - Wong, KK
ER  -