Intelligent Resource Allocation for Coexisting eMBB and URLLC Traffic in 5G Industrial Networks.

Dawei Shen, Ziheng Deng, Minxi Li,Qingxu Deng

IEEE International Conferences on Internet of Things(2023)

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摘要
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.
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关键词
QoS,5G,industrial applications,eMBB,URLLC,coexisting performance,resource allocation
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