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Bayesian optimization of queuing-based multi-channel URLLC scheduling

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journal contribution
posted on 22.09.2022, 11:03 authored by Wenheng ZhangWenheng Zhang, Mahsa DerakhshaniMahsa Derakhshani, Gan Zheng, Chung Shue Chen, Sangarapillai LambotharanSangarapillai Lambotharan

This paper studies the allocation of shared resources between ultra-reliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB) in the emerging 5G and beyond cellular networks. In this paper, we design a unique queuing mechanism for the joint eMBB/URLLC system. The aim is to flexibly schedule URLLC traffic to enhance the total eMBB throughput and the reliability of URLLC packets (i.e., the probability of not dropping URLLC packets in each mini-slot) while maintaining a satisfactory transmission latency as per the 3GPP requirements. Precisely, by deriving the steady-state probabilities of URLLC queue backlog analytically, we formulate a stochastic optimization problem to maximize the total normalized eMBB throughput and the URLLC utility. Due to the stochastic nature of the objective function, it is expensive to evaluate it for any set of inputs, and thus the Bayesian optimization is applied to obtain the optimal results of such a black-box objective function. Numerical results demonstrate that the proposed queuing mechanism never violates the latency requirement of the URLLC services but improves the reliability. It also enhances the total normalized eMBB throughput as compared to the method without queuing.


Royal Academy of Engineering under the Leverhulme Trust Research Fellowship scheme (Derakhshani-LTRF1920\16\67)

Leverhulme Trust Research Project Grant under grant number RPG-2017-129

Unlocking Potentials of MIMO Full-duplex Radios for Heterogeneous Networks (UPFRONT)

Engineering and Physical Sciences Research Council

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Communications Signal Processing Based Solutions for Massive Machine-to-Machine Networks (M3NETs)

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  • Mechanical, Electrical and Manufacturing Engineering

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IEEE Transactions on Wireless Communications


Institute of Electrical and Electronics Engineers


AM (Accepted Manuscript)

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For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) license to any Author Accepted Manuscript version arising.

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Dr Mahsa Derakhshani. Deposit date: 21 September 2022