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NOMA-based Resource Allocation for RIS-assisted Multi-UAV Systems

Feng, W; Tang, J; Wu, Q; Zhang, X; Jin, S; Tang, B; Wong, KK; (2022) NOMA-based Resource Allocation for RIS-assisted Multi-UAV Systems. In: IEEE International Conference on Communications. (pp. pp. 4553-4558). IEEE: Seoul, Republic of Korea. Green open access

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Abstract

This paper investigates a reconfigurable intelligent surface (RIS)-aided unmanned aerial vehicles (UAVs) system with non-orthogonal-multiple access (NOMA), where the transmit signals from multiple UAVs to ground users are strengthened through a RIS. An innovative framework is designed to minimize the total power consumption of the system, by jointly optimizing the position of UAVs, RIS reflection coefficients, active beamforming vectors and decoding order. To solve this problem, we first consider the sub-solution of the UAV's location which can be achieved via the successive convex approximation (SCA) and maximum ratio transmission (MRT). By applying the Gaussian randomization procedure, we then yield the closed-form solution for RIS phase coefficients. Subsequently, the transmit power is obtained by the standard convex optimization methods. Finally, a dynamic-order decoding scheme is proposed to optimize the decoding order. Simulation results show that the resource allocation scheme can obviously reduce the total power consumption compared to the benchmark schemes.

Type: Proceedings paper
Title: NOMA-based Resource Allocation for RIS-assisted Multi-UAV Systems
Event: ICC 2022 - IEEE International Conference on Communications
Dates: 16 May 2022 - 20 May 2022
ISBN-13: 9781538683477
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ICC45855.2022.9838927
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: NOMA, Power demand, Array signal processing, Simulation, Benchmark testing, Autonomous aerial vehicles, Decoding
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10157238
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