Intelligent Resource Allocation for Coexisting eMBB and URLLC Traffic in 5G Industrial Networks
- Resource Type
- Conference
- Authors
- Shen, Dawei; Deng, Ziheng; Li, Minxi; Deng, Qingxu
- Source
- 2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics) ITHINGS-GREENCOM-CPSCOM-SMARTDATA-CYBERMATICS Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics), 2023 IEEE International Conferences. :462-470 Dec, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Cellular networks
Social computing
Job shop scheduling
Enhanced mobile broadband
Quality of service
Ultra reliable low latency communication
Resource management
QoS
5G
industrial applications
eMBB
URLLC
coexisting performance
resource allocation
- Language
- ISSN
- 2836-3701
The use of fifth-generation (5G) cellular networks is growing in industrial applications such as factory automation systems. 5G networks provide two essential services: Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC). eMBB services require high data rates with some lower limits, while URLLC traffic has strict latency and reliability requirements. Previous methods for scheduling eMBB and URLLC traffic have assumed that URLLC traffic always preempts eMBB traffic upon arrival, which can negatively affect the achievable eMBB data rates. Additionally, prior work has not considered ensuring minimum data rate requirements for certain eMBB traffic. This paper proposes a novel framework for network resource allocation for coexisting eMBB and URLLC traffic. The proposed framework uses a hybrid offline/online approach to ensure that the Quality of Service (QoS) requirements for eMBB and URLLC traffic are met. Our framework can meet the latency and reliability requirements of URLLC traffic while maximizing data rates for eMBB traffic in a fair way and fulfilling their minimum data rate requirements. Experimental results show that our proposed framework is more effective than the current state-of-the-art methods.