Mobile Jamming Mitigation in 5G Networks: A MUSIC-Based Adaptive Beamforming Approach

• URL: http://arxiv.org/abs/2505.08046v1
• Date: Mon, 12 May 2025 20:31:31 GMT
• Title: Mobile Jamming Mitigation in 5G Networks: A MUSIC-Based Adaptive Beamforming Approach
• Abstract summary: Mobile jammers pose a critical threat to 5G networks, particularly in military communications.<n>We propose an intelligent anti-jamming framework that integrates Multiple Signal Classification (MUSIC) for high-resolution Direction-of-Arrival estimation.<n>Our hybrid approach achieves an average Signal-to-Noise Ratio (SNR) improvement of 9.58 dB and up to 99.8% DoA estimation accuracy.
• Score: 3.8683028650079625
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Mobile jammers pose a critical threat to 5G networks, particularly in military communications. We propose an intelligent anti-jamming framework that integrates Multiple Signal Classification (MUSIC) for high-resolution Direction-of-Arrival (DoA) estimation, Minimum Variance Distortionless Response (MVDR) beamforming for adaptive interference suppression, and machine learning (ML) to enhance DoA prediction for mobile jammers. Extensive simulations in a realistic highway scenario demonstrate that our hybrid approach achieves an average Signal-to-Noise Ratio (SNR) improvement of 9.58 dB (maximum 11.08 dB) and up to 99.8% DoA estimation accuracy. The framework's computational efficiency and adaptability to dynamic jammer mobility patterns outperform conventional anti-jamming techniques, making it a robust solution for securing 5G communications in contested environments.

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