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

Rong-Rong Lu1, Yang Ma2, Sheng-Hong Lin1,3

  • 1Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.

Entropy (Basel, Switzerland)
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Summary
This summary is machine-generated.

This study optimizes unmanned aerial vehicle (UAV) trajectories for hybrid free-space optical (FSO) and radio frequency (RF) communication systems. The goal is to maximize energy efficiency by balancing data rates and buffer capacity.

Keywords:
FSO/RF communicationsUAVenergy efficiencytrajectory optimization

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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.