Advancing reliability and efficiency of urban communication: Unmanned aerial vehicles, intelligent reflection surfaces, and deep learning techniques
| Autor: | Chongyang Li, Xiaohu Qiang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Heliyon, Vol 10, Iss 11, Pp e32472- (2024) |
| Druh dokumentu: | article |
| ISSN: | 2405-8440 99999641 |
| DOI: | 10.1016/j.heliyon.2024.e32472 |
| Popis: | Unmanned aerial vehicles (UAVs) have garnered attention for their potential to improve wireless communication networks by establishing line-of-sight (LoS) connections. However, urban environments pose challenges such as tall buildings and trees, impacting communication pathways. Intelligent reflection surfaces (IRSs) offer a solution by creating virtual LoS routes through signal reflection, enhancing reliability and coverage. This paper presents a three-dimensional dynamic channel model for UAV-assisted communication systems with IRSs. Additionally, it proposes a novel channel-tracking approach using deep learning and artificial intelligence techniques, comprising preliminary estimation with a deep neural network and continuous monitoring with a Stacked Bidirectional Long and Short-Term Memory (Bi-LSTM) model. Simulation results demonstrate faster convergence and superior performance compared to benchmarks, highlighting the effectiveness of integrating IRSs into UAV-enabled communication for enhanced reliability and efficiency. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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