Establishing temporary networks for disaster relief using UAV swarms

He, Shilan

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https://hdl.handle.net/2142/124602 Copy

Description

Title

Establishing temporary networks for disaster relief using UAV swarms

Author(s)

He, Shilan

Issue Date

2024-05-01

Director of Research (if dissertation) or Advisor (if thesis)

Caesar, Matthew Chapman

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Unmanned Aerial Vehicles
• Deep Reinforcement Learning
• Communication Networks
• Multi-agent Systems

Language

eng

Abstract

Natural disasters can destroy communications infrastructure, introducing challenges for timely rescue. Unmanned Aerial Vehicles (UAVs) can act as aerial base stations to provide temporary communication services for ground users. In complex environments, obstacles such as trees and buildings can impede signal propagation, thus reducing communication quality. This thesis introduces an innovative approach using UAVs' observations of the surrounding obstacles to make informed decisions on the movement for improved user coverage. We use Deep Reinforcement Learning (DRL) within a multi-agent setting to optimize UAV swarm movements for establishing reliable communication networks in disaster-affected urban environments. This approach allows UAVs to dynamically adjust their positions for near-optimal user coverage, representing a significant advancement in disaster response technologies. By integrating real-time observations of obstacles and leveraging cooperative strategies among UAVs, the proposed method enhances Line-of-Sight (LoS) connections essential for effective communication coverage. Simulation results demonstrate that UAVs equipped with the proposed DRL-based decision-making framework achieve significantly improved communication coverage in urban scenarios characterized by diverse obstacles and user distributions. Additionally, our strategy enables UAVs to achieve coverage with shorter travel distances, enhancing operational efficiency.

Graduation Semester

2024-05

Type of Resource

Text

Handle URL

https://hdl.handle.net/2142/124602

Copyright and License Information

Copyright 2024 Shilan He

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