Yamamoto Sota, Nakazato Jin, Tran Gia Khanh
Department of Electrical and Electronic Engineering, School of Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8552, Japan.
Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan.
Sensors (Basel). 2024 Mar 21;24(6):2006. doi: 10.3390/s24062006.
In the era of Industry 5.0, advanced technologies like artificial intelligence (AI), robotics, big data, and the Internet of Things (IoT) offer promising avenues for economic growth and solutions to societal challenges. Digital twin technology is important for real-time three-dimensional space reproduction in this transition, and unmanned aerial vehicles (UAVs) can support it. While recent studies have explored the potential applications of UAVs in nonterrestrial networks (NTNs), bandwidth limitations have restricted their utility. This paper addresses these constraints by integrating millimeter wave (mmWave) technology into UAV networks for high-definition video transmission. Specifically, we focus on coordinating intelligent reflective surfaces (IRSs) and UAV networks to extend coverage while maintaining virtual line-of-sight (LoS) conditions essential for mmWave communication. We present a novel approach for integrating IRS into Beyond 5G/6G networks to enhance high-speed communication coverage. Our proposed IRS selection method ensures optimal communication paths between UAVs and user equipment (UE). We perform numerical analysis in a realistically modeled 3D urban environment to validate our approach. Our results demonstrate significant improvements in the received SNR for multiple UEs upon the introduction of IRSs, and they confirm the feasibility of coverage extension in mmWave UAV networks.
在工业5.0时代，人工智能（AI）、机器人技术、大数据和物联网（IoT）等先进技术为经济增长提供了充满希望的途径，并为社会挑战提供了解决方案。数字孪生技术对于这一转型过程中的实时三维空间再现至关重要，而无人机（UAV）可以为其提供支持。虽然最近的研究探索了无人机在非地面网络（NTN）中的潜在应用，但带宽限制限制了它们的效用。本文通过将毫米波（mmWave）技术集成到无人机网络中以进行高清视频传输来解决这些限制。具体而言，我们专注于协调智能反射面（IRS）和无人机网络，以在保持毫米波通信必不可少的虚拟视距（LoS）条件的同时扩展覆盖范围。我们提出了一种将IRS集成到超5G/6G网络中的新颖方法，以增强高速通信覆盖范围。我们提出的IRS选择方法可确保无人机与用户设备（UE）之间的最佳通信路径。我们在逼真建模的3D城市环境中进行数值分析，以验证我们的方法。我们的结果表明，引入IRS后，多个UE的接收信噪比有显著提高，并且证实了毫米波无人机网络中扩展覆盖范围的可行性。
