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Throughput optimization for IRS-assisted multi-user NOMA URLLC systems

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Abstract

In this paper, we consider an intelligent reflecting surface (IRS)-assisted multi-user non-orthogonal multiple access (NOMA) ultra-reliable low-latency communication network, where an access point (AP) transmits data to multiple users with the short-packet communication (SPC) by applying the NOMA protocol. To maximize the sum throughput of all users, the transmit power of the AP and the IRS reflecting beamforming are jointly optimized. Since the data rate expression of the SPC is in a complicated form and the optimization variables are coupled with each other, the considered optimization problem is highly non-convex and challenging to solve. Based on the techniques of block coordinate ascent, semidefinite relaxation, Gaussian randomization, and successive convex approximation, we propose an efficient algorithm to obtain a high-quality solution. Simulation results show that the proposed algorithm can achieve significant throughput performance gain over some existing benchmark schemes.

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Acknowledgements

This work was supported in part by the Science and Technology Plan Project of Guangdong Province under Grant 2022A0505020008 and Grant 2022A0505050023, in part by the Natural Science Foundation of Guangdong Province under Grant 2023A1515011980, in part by the Key Program of Marine Economy Development Special Foundation of Department of Natural Resources of Guangdong Province under Grant GDNRC[2023]24, in part by the Special Support Plan for High-Level Talents of Guangdong Province under Grant 2019TQ05X409, in part by the Open Research Project Programme of the State Key Laboratory of Internet of Things for Smart City (University of Macau) under Grant SKL-IoTSC(UM)-2021-2023/ORPF/A04/2022, in part by the Open Research Fund of ISN Laboratory under Grant ISN23-12, and in part by the Open Fund Project of Jiangxi Military-Civilian Integration Beidou Navigation Key Laboratory under Grant 2022JXRH0004.

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  1. School of Information Engineering, Guangdong University of Technology, Xiaoguwei Street, Guangzhou, 510006, Guangdong Province, China

    Can Zhang, Miao Cui & Guangchi Zhang

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  1. Can Zhang
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  2. Miao Cui
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  3. Guangchi Zhang
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Correspondence to Miao Cui or Guangchi Zhang.

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Zhang, C., Cui, M. & Zhang, G. Throughput optimization for IRS-assisted multi-user NOMA URLLC systems. Wireless Netw 29, 2505–2517 (2023). https://doi.org/10.1007/s11276-023-03326-4

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