AI-Based Dynamic Spectrum Allocation for Hybrid Satellite-5G Networks

• Author(s): Asrar Ahmad Ansari ; Prabhdeep Singh
• Paper ID: 1707338
• Page: 472-485
• Published Date: 14-04-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 8 Issue 10 April-2025

Abstract

The integration of satellite communication systems with 5G networks presents an opportunity to extend high-speed internet access to remote and underserved areas. However, efficient spectrum management remains a critical challenge in this hybrid satellite-5G environment due to the vast and dynamic nature of the radio frequency spectrum. This paper proposes an AI-based Dynamic Spectrum Allocation (DSA) framework to optimize spectrum utilization in hybrid satellite-5G networks. The proposed system leverages machine learning algorithms, particularly reinforcement learning (RL), to predict and allocate spectrum resources dynamically based on real-time demand, interference levels, and network conditions. In this framework, a hybrid network management system uses AI to continually monitor spectrum usage across both satellite and terrestrial 5G networks, adjusting allocations in response to fluctuating user traffic and environmental conditions. The reinforcement learning model is trained to make intelligent decisions on spectrum sharing, balancing the trade-off between high-throughput communication and the avoidance of interference. This paper also explores the implementation of deep learning techniques to predict spectrum demand and optimize the handover between satellite and 5G base stations. The proposed AI-based DSA approach not only ensures efficient spectrum utilization but also minimizes latency, reduces interference, and enhances the overall quality of service in hybrid networks. Simulation results demonstrate the potential of the AI-driven framework to outperform traditional static allocation methods, offering significant improvements in throughput, user experience, and network efficiency.

Keywords

AI-driven Spectrum Management, Dynamic Spectrum Allocation, Hybrid Satellite-5G Networks, Machine Learning for Spectrum Optimization and 5G-Satellite Integration.

Citations

IRE Journals:
Asrar Ahmad Ansari , Prabhdeep Singh "AI-Based Dynamic Spectrum Allocation for Hybrid Satellite-5G Networks" Iconic Research And Engineering Journals Volume 8 Issue 10 2025 Page 472-485

IEEE:
Asrar Ahmad Ansari , Prabhdeep Singh "AI-Based Dynamic Spectrum Allocation for Hybrid Satellite-5G Networks" Iconic Research And Engineering Journals, 8(10)