Intelligent UAV Deployment for a Disaster-Resilient Wireless Network.

Area of Science:

• Wireless Communication
• Network Engineering
• Aerial Networks

Background:

• Terrestrial networks face coverage gaps during emergencies or overload.
• Unmanned Aerial Vehicles (UAVs) offer a flexible solution as aerial base stations (ABSs).
• Optimizing UAV deployment is crucial for effective network connectivity.

Purpose of the Study:

• To develop an efficient method for optimal UAV ABS placement and user assignment.
• To maximize total spectral efficiency (TSE) while ensuring quality of service (QoS).
• To minimize energy consumption for UAV ABS operations.

Main Methods:

• Utilized K-means clustering for 2D ABS positioning and user assignment.
• Employed a stable marriage approach for UE-to-ABS assignment.
• Investigated two altitude optimization methods: exhaustive search and Particle Swarm Optimization (PSO).
• Considered air-to-ground channel characteristics, co-channel interference, and energy constraints.

Main Results:

• The PSO approach yielded higher TSE than exhaustive search in dense networks.
• Both proposed methods achieved up to 8-fold energy savings compared to naive placement.
• PSO demonstrated comparable energy consumption for ABS movements to exhaustive search.

Conclusions:

• The proposed K-means and stable marriage approach provides an efficient method for UAV ABS deployment.
• PSO is an effective optimization technique for UAV altitude, enhancing network performance.
• Significant energy savings are achievable with optimized UAV ABS placement strategies.