Abstract
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 con-sumption 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.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE International Conference on Communications Workshops, ICC Workshops 2024 |
| Editors | Matthew Valenti, David Reed, Melissa Torres |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 816-821 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350304053 |
| DOIs | |
| State | Published - 2024 |
| Externally published | Yes |
| Event | 2024 Annual IEEE International Conference on Communications Workshops, ICC Workshops 2024 - Denver, United States Duration: 9 Jun 2024 → 13 Jun 2024 |
Publication series
| Name | 2024 IEEE International Conference on Communications Workshops, ICC Workshops 2024 |
|---|
Conference
| Conference | 2024 Annual IEEE International Conference on Communications Workshops, ICC Workshops 2024 |
|---|---|
| Country/Territory | United States |
| City | Denver |
| Period | 9/06/24 → 13/06/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- IoT
- Unmanned aerial vehicles
- reconfigurable intel-ligent surfaces
- reinforcement learning
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