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AI-powered Adaptive Spectrum Dynamics (ASD) for Military Radios: Enhancing Spectrum Efficiency and Security

Author

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  • Akanksha Srivastava
  • Ritesh Chandra

Abstract

The increasing demand for wireless communication in military operations necessitates efficient spectrum utilization. This paper proposes an AI-powered Adaptive Spectrum Dynamics (ASD) framework for military radios, leveraging machine learning and cognitive radio techniques. ASD optimizes spectrum allocation, mitigates interference, and enhances security. Simulation results demonstrate improved spectrum efficiency (25%) and reduced interference (40%) compared to traditional methods. The increasing complexity of modern battlefields demands robust and adaptive communication systems. This paper presents a comprehensive study on AI-Powered Adaptive Spectrum Dynamics (ASD) in military radios, emphasizing its role in optimizing spectrum usage, ensuring resilience against interference, and securing communication channels. By leveraging machine learning algorithms, ASD enables real-time spectrum monitoring, dynamic allocation, and mitigation of jamming threats. The paper discusses architecture, key technologies, challenges, and practical implementations of ASD in military communication systems, demonstrating its potential to revolutionize tactical communications.

Suggested Citation

  • Akanksha Srivastava & Ritesh Chandra, 2024. "AI-powered Adaptive Spectrum Dynamics (ASD) for Military Radios: Enhancing Spectrum Efficiency and Security," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 11(6), pages 900-911, December.
    • Handle: RePEc:etm:ijsrst:v11:y2024:i6:id:521
    DOI: 10.32628/IJSRST241161181
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