Efficient Deployment of Multi-UAVs in Massively Crowded Events

Area of Science:

• Wireless communication networks
• Aerial base station deployment
• Optimization algorithms

Background:

• Unmanned Aerial Vehicles (UAVs) are increasingly used as aerial base stations for wireless coverage.
• Efficient 3D placement is crucial for maximizing coverage and minimizing power consumption.
• Existing methods may not be optimal for both small and large coverage areas.

Purpose of the Study:

• To investigate the efficient 3D placement of UAVs as aerial base stations.
• To minimize transmit power for single UAVs in small coverage areas.
• To maximize coverage area and density for multiple UAVs in large coverage areas.

Main Methods:

• Particle Swarm Optimization (PSO) and K-means with Ternary Search (KTS) algorithms for single UAV placement.
• Circle Packing Theory (CPT) for optimizing multiple UAV placement in square, rectangular, and circular regions.
• Formulation of UAV altitude placement to minimize transmit power.

Main Results:

• PSO algorithm achieved a 1/5 reduction in transmit power compared to KTS for single UAVs.
• Optimal UAV deployment in large areas (square, rectangle, circle) achieved maximum coverage densities of 78.5%, 82.5%, and 80.3% respectively.
• Maximum coverage density does not always correlate with a higher number of UAVs.

Conclusions:

• The PSO algorithm offers superior performance in minimizing transmit power for single UAV aerial base stations.
• CPT provides an effective framework for optimizing multi-UAV deployment to maximize coverage in various large-scale regions.
• Strategic UAV altitude and placement are key to achieving efficient wireless coverage with reduced power demands.