Intelligent Optimization of LTE and 5G Networks Using AI and Machine Learning
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V6I3P104Keywords:
Artificial Intelligence, Machine Learning, Network Optimization, LTE, 5G NR, Self-Organizing Networks, Edge Intelligence, Deep Learning, Reinforcement Learning, Anomaly DetectionAbstract
The evolution of wireless networks from LTE to 5G NR and beyond has led to unprecedented complexity in architecture and operations. Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of this transformation, offering tools that can learn, adapt, and automate network optimization tasks. These techniques help solve real-time performance, load balancing, and fault detection challenges, leading to efficient resource utilization, reduced operational expenditure (OPEX), and improved user experience.[1] This paper reviews the integration of AI/ML across different layers of network architecture, including radio access, core, and edge, and outlines the current challenges and future directions for intelligent networking
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