TY - GEN
T1 - Deep Reinforcement Learning for Downlink Scheduling in 5G and beyond Networks
T2 - 34th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2023
AU - Seguin, Michael
AU - Omer, Anjali
AU - Koosha, Mohammad
AU - Malandra, Filippo
AU - Mastronarde, Nicholas
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The coexistence of a wide variety of different applications with diverse Quality of Service (QoS) and Quality of Experience (QoE) requirements calls for more sophisticated radio resource scheduling in 5G and beyond (5GB) networks compared to previous generations. To address this challenge, a growing body of research has explored deep reinforcement learning (DRL) to solve the radio resource scheduling problem. In this paper, we review representative literature on the topic of downlink scheduling for 5GB networks using DRL, with emphasis on fine-grained approaches that directly allocate resource blocks (RBs) to user equipments (UEs). We conclude by discussing four ways to improve upon this early-stage research and identify some open problems that must be solved to make DRL a viable solution to the downlink scheduling problem in 5GB networks.
AB - The coexistence of a wide variety of different applications with diverse Quality of Service (QoS) and Quality of Experience (QoE) requirements calls for more sophisticated radio resource scheduling in 5G and beyond (5GB) networks compared to previous generations. To address this challenge, a growing body of research has explored deep reinforcement learning (DRL) to solve the radio resource scheduling problem. In this paper, we review representative literature on the topic of downlink scheduling for 5GB networks using DRL, with emphasis on fine-grained approaches that directly allocate resource blocks (RBs) to user equipments (UEs). We conclude by discussing four ways to improve upon this early-stage research and identify some open problems that must be solved to make DRL a viable solution to the downlink scheduling problem in 5GB networks.
UR - https://www.scopus.com/pages/publications/85178254621
U2 - 10.1109/PIMRC56721.2023.10293754
DO - 10.1109/PIMRC56721.2023.10293754
M3 - Conference contribution
AN - SCOPUS:85178254621
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
BT - 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 September 2023 through 8 September 2023
ER -