APPLICATION OF ARTIFICIAL INTELLIGENCE ALGORITHMS IN DYNAMIC TRAFFIC ALLOCATION FOR 5G/6G MOBILE COMMUNICATION NETWORKS
DOI:
https://doi.org/10.66345/stj.6681Keywords:
5G, 6G, artificial intelligence, machine learning, deep learning, dynamic traffic allocation, telecommunications, network optimizationAbstract
This article analyzes the theoretical and practical aspects of applying artificial intelligence algorithms for dynamic traffic allocation in 5G and 6G mobile communication networks. The study examines the rapid growth of network traffic, the need for efficient utilization of network resources, and the importance of improving Quality of Service in modern telecommunication systems. Particular attention is given to the application of machine learning, deep learning, and reinforcement learning algorithms for traffic prediction, resource optimization, and load balancing. The advantages of AI-based traffic management systems in enhancing network performance, reducing latency, and improving energy efficiency are also discussed. The findings indicate that artificial intelligence technologies will become a fundamental component of network management in future 6G communication systems and intelligent wireless infrastructures.
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