Optimal UAV Placement in 3D Space for Enhanced Communication Performance: A Multi-Objective Particle Swarm Optimization Approach

This paper presents an optimization framework for an Unmanned Aerial Vehicle (UAV) assisted communication system. The goal is to determine the optimal placement of the UAV in three-dimensional space (xu, yu, zu) to minimize power consumption and maximize data rate while maintaining a desired bit error rate (BER). We first establish a mathematical model that captures the relationship between the UAV’s position, power consumption, data rate, and BER, considering free space path loss. Such a mathematical model is achieved in a static network environment and by employing the Multi-objective Particle Swarm Optimization (MOPSO) algorithm, which concurrently explores the solution space, seeking the ideal position (xu, yu, zu) that balances power consumption and data rate.We then extend the proposed framework to adapt to dynamic network environments while satisfying user demands. By adjusting the proposed system for static and dynamic network conditions, our enhanced framework ensures the UAV-assisted communication system remains efficient and effective. Theoretical analysis results, demonstrated through various examples, show that our proposed solution effectively balances delay and power consumption while maintaining the desired BER in UAV networks.