RIS-Assisted UAV for IoT Data Harvesting

被引:0
|
作者
Abualhayja'a, Mohammad [1 ]
Centeno, Anthony [1 ]
Butt, M. Majid [2 ]
Sehier, Philippe [3 ]
Dinh-Hieu Tran [3 ]
Imran, Muhammad Ali [1 ]
Mohjazi, Lina [1 ]
机构
[1] Univ Glasgow, James Watt Sch Engn, Glasgow, Lanark, Scotland
[2] Nokia, Dallas, TX USA
[3] Nokia, Paris, France
关键词
Unmanned aerial vehicles; reconfigurable intelligent surfaces; IoT; reinforcement learning;
D O I
10.1109/ICCWORKSHOPS59551.2024.10615408
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Future Internet-of-Things (IoT) networks are expected to rely heavily on unmanned aerial vehicles (UAVs) for data collection, as they can meet the demands for massive connectivity and energy efficiency. UAVs' ability to move closer to the IoT devices can enhance data rates and mitigate energy consumption in energy-limited IoT devices. UAVs and reconfigurable intelligent surfaces (RISs) are anticipated to witness extensive deployment in future wireless networks, aiming to enhance both spectrum and energy efficiency. In this work, an RIS-assisted UAV IoT data collection framework is presented and optimised to maximise the performance in terms of the number of served IoT devices. The proposed algorithm is a promising approach to address the growing demand for efficient data collection in IoT networks. Our results demonstrate significant improvements in data collection efficiency, with about a 50% increase in the number of served devices.
引用
收藏
页码:816 / 821
页数:6
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