Performance Analysis of Cooperative-Aerial-IRS-Assisted Heterogeneous Networks

Unmanned-aerial-vehicle (UAV) communications assisted by aerial intelligent reflecting surfaces (A-IRSs) have emerged as a highly regarded technology aiming to increase the communication capacity of cellular networks and improve user communication quality. However, the performance of combining UAV-carried A-IRSs with heterogeneous cellular networks (HetNets) has not been fully investigated. In this article, we develop a novel framework to analyze the downlink (DL) performance of an UAV-carried cooperative A-IRSs-enhanced HetNet. First, we model the cascaded fading of the A-IRS-assisted communication channel as a mixture of gamma variables and approximate its distribution function by using the moment matching method. Next, we obtain the exact closed-form expressions of the user-association probability and the probability density function (PDF) of the distance between any user and its serving BS. Then, we derive the Laplace transform of the received signal and the interference power of all types of users for our proposed A-IRS deployment strategy. Finally, we derive analytic expressions of the DL coverage probability and the energy efficiency of UAV networks, which are validated by the simulation results. The results demonstrate that our proposed theoretical framework significantly enhances the precision of analysis, and aligns closely with real-world scenarios. We also show the performance enhancement brought by cooperative A-IRSs, the advantages of our proposed A-IRS deployment strategy within HetNet, as well as the impact of the interference introduced by A-IRSs on direct transmissions.

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Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-10-17
DOI
https://doi.org/10.1109/jiot.2024.3482313
Citations
8
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
10.39

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article

Performance Analysis of Cooperative-Aerial-IRS-Assisted Heterogeneous Networks

Ran Tao, Yue Wu, Wuling Liu, Xiaoli Chu et al.
8 citations
IEEE Internet of Things Journal
UAV Applications and Optimization
10.39
article

Performance Analysis of Cooperative-Aerial-IRS-Assisted Heterogeneous Networks

Ran Tao, Yue Wu, Wuling Liu, Xiaoli Chu, Jiliang Zhang, Jie Zhang
article en
8 citations

Abstract

Unmanned-aerial-vehicle (UAV) communications assisted by aerial intelligent reflecting surfaces (A-IRSs) have emerged as a highly regarded technology aiming to increase the communication capacity of cellular networks and improve user communication quality. However, the performance of combining UAV-carried A-IRSs with heterogeneous cellular networks (HetNets) has not been fully investigated. In this article, we develop a novel framework to analyze the downlink (DL) performance of an UAV-carried cooperative A-IRSs-enhanced HetNet. First, we model the cascaded fading of the A-IRS-assisted communication channel as a mixture of gamma variables and approximate its distribution function by using the moment matching method. Next, we obtain the exact closed-form expressions of the user-association probability and the probability density function (PDF) of the distance between any user and its serving BS. Then, we derive the Laplace transform of the received signal and the interference power of all types of users for our proposed A-IRS deployment strategy. Finally, we derive analytic expressions of the DL coverage probability and the energy efficiency of UAV networks, which are validated by the simulation results. The results demonstrate that our proposed theoretical framework significantly enhances the precision of analysis, and aligns closely with real-world scenarios. We also show the performance enhancement brought by cooperative A-IRSs, the advantages of our proposed A-IRS deployment strategy within HetNet, as well as the impact of the interference introduced by A-IRSs on direct transmissions.

IEEE Internet of Things JournalVol. 12(4)
East China University of Science and Technology (CN), Nanjing University of Information Science and Technology (CN), Suzhou Research Institute (CN), Aerospace Information Research Institute (CN), State Key Laboratory of Synthetical Automation for Process Industries, University of Sheffield (GB), Northeastern University (CN)
National Natural Science Foundation of China, Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology, National Mobile Communications Research Laboratory, Southeast University
Openalex Percentile: Top 2%
UAV Applications and Optimization
10.39
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