Optimization Method for Secrecy Capacity of UAV Relaying Based on Dynamic Adjustment of Power Allocation Factor

Area of Science:

• Wireless Communication Security
• Information Theory
• Optimization Techniques

Background:

• Wireless channels are vulnerable to eavesdropping, especially when the eavesdropper has a strong signal.
• Traditional power optimization struggles to counter high-quality eavesdropping channels.
• Unmanned Aerial Vehicle (UAV) relaying presents unique security challenges due to its broadcast nature.

Purpose of the Study:

• To propose a novel optimization method for enhancing the secrecy capacity in UAV relaying systems.
• To address the limitations of traditional power optimization in secure wireless transmissions.
• To maximize the secrecy rate by dynamically adjusting the power allocation factor.

Main Methods:

• Formulating a joint optimization problem to maximize the secrecy rate in a four-node model (source, UAV, destination, eavesdropper).
• Employing successive convex approximation (SCA) to convert the non-convex problem into a convex one.
• Utilizing the water-filling (WF) algorithm for analytical solutions and an alternating iterative optimization algorithm with artificial noise (AN) for global optimization.

Main Results:

• The proposed dynamic power allocation method effectively suppresses eavesdropping channel capacity.
• Artificial noise injection combined with real-time channel information precisely jams the eavesdropping link.
• Simulation results show substantial improvements in secrecy performance and communication reliability compared to traditional methods.

Conclusions:

• The developed optimization method significantly enhances the security of UAV-assisted wireless communications.
• Dynamic power allocation and artificial noise are effective strategies for combating eavesdropping.
• The approach improves both secrecy capacity and overall system reliability in challenging wireless environments.