NOMA-Based Secure Physical Layer Communication in UAV Networks with Artificial Noise Injection

This study proposes a secure communication framework for Unmanned Aerial Vehicle (UAV) networks that integrates Non-Orthogonal Multiple Access (NOMA) with Artificial Noise Injection (ANI) to enhance physical layer security. The proposed system employs a UAV as a relay node to communicate with multiple ground users (GUs) while mitigating interference from malicious eavesdroppers (Eves). NOMA dynamically allocates power to users based on their channel conditions, ensuring fairness and efficient spectrum utilization, while ANI degrades eavesdroppers’ channel quality by introducing controlled interference. The system operates over quasi-static Rayleigh fading channels, with channel gains modeled as independent and identically distributed complex Gaussian variables. Key performance metrics, including secrecy rate, throughput, energy efficiency, and bit error rate (BER), are evaluated through extensive Python-based simulations. Results demonstrate that ANI significantly enhances secrecy rate by degrading the eavesdroppers’ signal quality, especially at higher SINR levels, while slightly reducing throughput and energy efficiency due to power allocation for artificial noise. The proposed system achieves a balance between security and performance, offering a robust solution for secure UAV communication in dynamic and adversarial environments. This work provides a foundation for future exploration of optimization strategies and real-world applications in secure UAV networks.