Energy-Efficient Trajectory Optimization for UAV-Based Hybrid FSO/RF Communications with Buffer Constraints

Area of Science:

• Wireless Communication Systems
• Robotics and Control Systems
• Optical Engineering

Background:

• Hybrid free-space optical (FSO)/radio frequency (RF) systems offer enhanced communication capabilities.
• Unmanned aerial vehicles (UAVs) are increasingly utilized for mobile communication relays.
• Rate imbalances between FSO and RF links necessitate efficient data handling mechanisms, such as buffering.

Purpose of the Study:

• To develop a theoretical framework for energy consumption and throughput in UAV-assisted hybrid FSO/RF systems.
• To derive an expression for the energy efficiency of such hybrid communication systems.
• To formulate and solve a trajectory optimization problem for maximizing energy efficiency under various constraints.

Main Methods:

• Theoretical modeling of energy consumption and throughput for the hybrid FSO/RF system.
• Derivation of the energy efficiency expression.
• Formulation of a nonconvex trajectory optimization problem incorporating buffer, velocity, acceleration, and position constraints.
• Application of sequential convex optimization and first-order Taylor approximation to transform the problem into a convex one.
• Development of an iterative algorithm to find the optimal UAV trajectory.

Main Results:

• Theoretical models for energy consumption and throughput were established.
• An expression for energy efficiency was derived.
• A method to transform a nonconvex optimization problem into a convex one was successfully applied.
• An iterative algorithm was proposed and validated through numerical simulations.
• The impact of buffer size on the UAV's trajectory was analyzed.

Conclusions:

• The proposed iterative algorithm efficiently solves the trajectory optimization problem for UAV-assisted hybrid FSO/RF systems.
• The study demonstrates the trade-offs between buffer size, UAV trajectory, and overall system energy efficiency.
• The findings provide valuable insights for designing and deploying energy-efficient UAV-based communication networks.