Intelligent Reflecting Surface Assisted Secure Transmission in UAV-MIMO Communication Systems

Area of Science:

• Wireless Communication
• Information Security
• Signal Processing

Background:

• Unmanned Aerial Vehicle (UAV) communication systems face security challenges from malicious eavesdroppers.
• Intelligent Reflecting Surfaces (IRS) offer a promising solution to enhance signal propagation and security.
• Multiple-Input Multiple-Output (MIMO) systems in UAV communications require advanced techniques for secure data transmission.

Purpose of the Study:

• To maximize the secrecy rate (SR) in an IRS-assisted UAV communication system.
• To jointly optimize transmit precoding (TPC) matrix, artificial noise (AN) matrix, IRS phase shift matrix, and UAV position.
• To address the non-convex optimization problem inherent in secure transmission parameter tuning.

Main Methods:

• An alternating optimization (AO) algorithm is developed to solve the non-convex problem.
• Lagrange dual method is used to derive TPC and AN covariance matrices.
• Alternating Direction Method of Multipliers (ADMM), Majorization-Minimization (MM), and Riemannian Manifold Gradient (RCG) algorithms are employed for IRS phase shift optimization.
• A Secrecy Rate Gradient (SRG) algorithm, based on proportional integral (PI) control theory, is proposed for UAV positioning.

Main Results:

• The proposed AO algorithm demonstrates good convergence performance.
• The joint optimization strategy significantly increases the SR.
• Simulation results show a 40.5% increase in SR compared to systems without IRS assistance.

Conclusions:

• The IRS-assisted secure transmission framework effectively enhances communication security in UAV systems.
• The developed AO algorithm provides an efficient solution for optimizing multiple system parameters.
• This research offers a practical approach to improving the security and performance of UAV communication networks.