Energy efficiency maximization for IRS-assisted UAV short packet communication

Area of Science:

• Wireless Communication Networks
• Signal Processing
• Robotics and Control Systems

Background:

• Sixth-generation (6G) wireless networks demand ultra-low latency for advanced applications.
• Short packet communication is crucial for meeting these low-latency requirements.
• Unmanned aerial vehicles (UAVs) are increasingly integrated into communication networks for sensing and data relay.

Purpose of the Study:

• To maximize the energy efficiency of intelligent reflecting surface (IRS)-assisted UAV short packet communication.
• To optimize UAV speed, trajectory, transmit power, and IRS passive beamforming.
• To address the non-convex optimization problem inherent in system parameter maximization.

Main Methods:

• Successive convex approximation (SCA) method employed to handle the non-convex problem.
• A joint iterative optimization algorithm developed for system parameter optimization.
• Simulation analysis to validate algorithm convergence and performance.

Main Results:

• The proposed joint iterative algorithm demonstrates good convergence performance.
• An optimal UAV flight speed exists that minimizes overall energy consumption.
• Intelligent reflecting surfaces (IRS) are shown to effectively enhance system energy efficiency.

Conclusions:

• The developed optimization framework successfully improves energy efficiency in IRS-assisted UAV short packet communication systems.
• The findings provide valuable insights for designing energy-efficient 6G communication systems.
• IRS technology presents a promising solution for enhancing wireless communication performance and sustainability.