Secrecy Capacity Enhancement in Active IRS-Assisted UAV Communication System

Area of Science:

• Wireless communication systems
• Information security
• Robotics and intelligent systems

Background:

• Intelligent Reflecting Surfaces (IRS) offer novel solutions for reconstructing communication environments, particularly in Unmanned Aerial Vehicle (UAV) systems.
• Existing IRS-assisted UAV systems face challenges in physical layer security, hardware limitations, and power consumption.
• Active IRS integration with controllable power amplifiers addresses blocked links and enhances communication reliability.

Purpose of the Study:

• To propose a secrecy capacity optimization scheme for active IRS-assisted UAV communication systems.
• To address multi-user security challenges and hardware limitations in IRS-assisted UAV networks.
• To maximize the average achievable secrecy capacity under power constraints for both the UAV and the active IRS.

Main Methods:

• Joint optimization of user scheduling, UAV trajectory, beamforming vector, and reflection matrix.
• Integration of controllable power amplifiers into IRS reflecting units.
• Application of the block coordinate descent (BCD) algorithm to solve the non-convex optimization problem.

Main Results:

• The active IRS-assisted UAV communication scheme effectively mitigates the 'multiplicative fading' effect.
• Achieved a significant enhancement in system secrecy capacity by 55.4% compared to passive IRS schemes.
• Demonstrated an 11.9% improvement in secrecy capacity over systems without optimal UAV trajectory planning.

Conclusions:

• The proposed active IRS-assisted UAV communication system offers a robust solution for enhancing physical layer security.
• The joint optimization strategy effectively balances secrecy capacity maximization with power constraints.
• This approach represents a significant advancement in secure and efficient UAV communication networks.