QoE-Driven Multiple UAVs-Mounted Reconfigurable Intelligent Surface Communication

In this letter, we investigate a new reconfigurable intelligent surface (RIS) aided unmanned aerial vehicle (RUAV) system. Specifically, a multiple-RUAV (mRUAV) scenario is considered, where a new hybrid quality-of-experience (HQoE) metric jointly considering energy efficiency, relative data rate quality and transmission delay is designed. The objective of the proposed system is to maximize HQoE by jointly optimizing the transmit power of base station (BS), the beamformers at BS and RUAVs, and the positions of RUAVs. For handling this non-convex optimization problem, we first optimize the positions of RUAVs by a sphere estimation based particle swarm optimization (SEPSO) algorithm, and then apply the block coordinate descent (BCD) algorithm on the other variables. Simulation results show that the proposed system can outperform existing solutions.

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Publication Details

Journal
IEEE Communications Letters
Published
2024-10-16
DOI
https://doi.org/10.1109/lcomm.2024.3481963
Citations
1
Primary Topic
Optical Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
0.21
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article

QoE-Driven Multiple UAVs-Mounted Reconfigurable Intelligent Surface Communication

Jianchao Chen, Ming Jiang, Haowen Xu
1 citations
IEEE Communications Letters
Optical Wireless Communication Technologies
0.21
article

QoE-Driven Multiple UAVs-Mounted Reconfigurable Intelligent Surface Communication

Jianchao Chen, Ming Jiang, Haowen Xu
article en
1 citations

Abstract

In this letter, we investigate a new reconfigurable intelligent surface (RIS) aided unmanned aerial vehicle (RUAV) system. Specifically, a multiple-RUAV (mRUAV) scenario is considered, where a new hybrid quality-of-experience (HQoE) metric jointly considering energy efficiency, relative data rate quality and transmission delay is designed. The objective of the proposed system is to maximize HQoE by jointly optimizing the transmit power of base station (BS), the beamformers at BS and RUAVs, and the positions of RUAVs. For handling this non-convex optimization problem, we first optimize the positions of RUAVs by a sphere estimation based particle swarm optimization (SEPSO) algorithm, and then apply the block coordinate descent (BCD) algorithm on the other variables. Simulation results show that the proposed system can outperform existing solutions.

IEEE Communications LettersVol. 28(12)
Sun Yat-sen University (CN)
Affordable and clean energy
Openalex Percentile: Top 47%
Optical Wireless Communication Technologies
0.21
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QoE-Driven Multiple UAVs-Mounted Reconfigurable Intelligent Surface Communication — Jianchao Chen, Ming Jiang, et al. · IEEE Communications Letters (2024) | TGRS Research Map | TGRS