Joint bandwidth allocation, trajectory design and passive beamforming for IRS-equipped UAV aided OFDMA system

Qi Zhang; Pingmu Huang; Tiejun Lv

doi:10.1117/12.2634521

4 May 2022 Joint bandwidth allocation, trajectory design and passive beamforming for IRS-equipped UAV aided OFDMA system

Qi Zhang, Pingmu Huang, Tiejun Lv

Author Affiliations +

Proceedings Volume 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021); 121720H (2022) https://doi.org/10.1117/12.2634521
Event: International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 2021, Nanchang, China

Abstract

Unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are two promising technologies which can improve the signal coverage and network throughput. However, different practical restrictions of these two technologies restrict their applications. In this paper, the maximum sum-rate is investigated in the orthogonal frequency division multiple access (OFDMA) system aided by IRS-equipped UAV. We comprehensively optimize the bandwidth allocation, the flight trajectory and the phase shift. The problem is non-convex that is difficult to solve directly. Therefore, we break down the problem into several sub-problems, and develop an alternating optimization (AO) algorithm to gradually obtain the suboptimal solution. After obtaining the BS resource block allocation solution, the successive convex approximation (SCA) technique is used to obtain the trajectory and the phase shift solution. Simulation results show that the simulation results show that the UAV-assisted OFDMA communication system equipped with IRS can greatly improve the system and speed.

Citation Download Citation

Qi Zhang, Pingmu Huang, and Tiejun Lv "Joint bandwidth allocation, trajectory design and passive beamforming for IRS-equipped UAV aided OFDMA system", Proc. SPIE 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 121720H (4 May 2022); https://doi.org/10.1117/12.2634521

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