Research Article
Resource Allocation and MEAR Maximization for RIS-Aided eMBB/URLLC Traffic Multiplexing
@INPROCEEDINGS{10.1007/978-3-031-67162-3_13, author={Mengmeng Wang and Bei Liu and Xin Su}, title={Resource Allocation and MEAR Maximization for RIS-Aided eMBB/URLLC Traffic Multiplexing}, proceedings={Communications and Networking. 18th EAI International Conference, ChinaCom 2023, Sanya, China, November 18--19, 2023, Proceedings}, proceedings_a={CHINACOM}, year={2024}, month={8}, keywords={eMBB MEAR fairness URLLC RIS RB allocation}, doi={10.1007/978-3-031-67162-3_13} }- Mengmeng Wang
Bei Liu
Xin Su
Year: 2024
Resource Allocation and MEAR Maximization for RIS-Aided eMBB/URLLC Traffic Multiplexing
CHINACOM
Springer
DOI: 10.1007/978-3-031-67162-3_13
Abstract
In future sixth generation (6G) cellular networks, service requirements for enhanced mobile broadband (eMBB) and ultra-reliable and low latency Communication (URLLC) will become more stringent, resulting in severe power consumption and spectrum scarcity. This paper studies the resource allocation problem in the case of Reconfigurable Intelligent Surface (RIS) assisted coexistence of eMBB and URLLC services, to maximize the eMBB user’s minimum expected achieved rate (MEAR) while ensuring the quality of services (QoS) for URLLC users. We adopt the alternating direction multiplier method (ADMM) to optimize the RIS phase shift matrix and propose a heuristic algorithm for allocating eMBB resource blocks (RB). In addition, a proportional fairness (PF) algorithm is used to allocate URLLC services to ensure fairness among eMBB users. Compared to no RIS, simulation results show that the proposed scheme improves approximately 20(\%)MEAR, requiring only 60 RIS elements, and it has significant advantages over other schemes.
