A.A. Korobkov1, A.K. Gaysin2, I.A. Safiullin3, I.P. Ashaev4, A.F. Nadeev5

1–5 Kazan National Research Technical University named after A.N. Tupolev – KAI (Kazan, Russia)

1 aakorobkov@kai.ru, 2 akgaysin@kai.ru, 3 iasafiullin@kai.ru, 4 ipashaev@kai.ru, 5 afnadeev@kai.ru

The open architecture of O-RAN networks enables the integration of third-party applications based on machine learning (ML) and artificial intelligence (AI) to enhance the efficiency of the radio access network (RAN). One of the major challenges in mobile networks is efficient handover management for users with diverse mobility patterns. This paper presents a model of interaction between O-RAN elements for mobility management. The proposed model includes data collection and pre-processing, user classification based on mobility type, and handover decision-making using reinforcement learning (RL) techniques. The model is designed to improve key performance indicators (KPIs) of mobile networks. The development considers the O-RAN architecture and interfaces, ensuring compatibility with existing mobile network infrastructures.

Korobkov A.A., Gaysin A.K., Safiullin I.A., Ashaev I.P., Nadeev A.F. Interaction model of O-RAN radio access network elements for mobility management. Electromagnetic waves and electronic systems. 2025. V. 30. № 5. P. 79−92. DOI: https://doi.org/10.18127/ j15604128-202505-06 (in Russian)

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