A system that provides low-latency resource allocation at the base station level.
The system addresses latency and privacy issues in 5G networks by using Federated Learning and Edge AI for autonomous resource allocation at base stations, improving communication efficiency and reducing power consumption.
TR202617431A2Pending Publication Date: 2026-10-21TURKCELL TEKNOLOJI ARASTIRMA & GELISTIRME AS
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Patent Information
- Application Number
- TR202617431
- Authority / Receiving Office
- TR · TR
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2026-10-08
- Publication Date
- 2026-10-21
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Abstract
This invention relates to a system (1) that uses a closed-loop distributed control architecture that learns collectively at the base station level without sharing raw user data in the 5G network and translates local traffic prediction directly into radio resource blocks (Resource Block ? RB), thereby enabling autonomous radio resource management within the base station in the millisecond range and enabling the GSM network to become a collectively self-optimizing structure.
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