Advancing reliability and efficiency of urban communication: Unmanned aerial vehicles, intelligent reflection surfaces, and deep learning techniques.
Heliyon
; 10(11): e32472, 2024 Jun 15.
Article
en En
| MEDLINE
| ID: mdl-38912507
ABSTRACT
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.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Heliyon
Año:
2024
Tipo del documento:
Article
País de afiliación:
China
Pais de publicación:
Reino Unido