{"id":10397,"date":"2025-03-01T17:11:38","date_gmt":"2025-03-01T17:11:38","guid":{"rendered":"https:\/\/www.gsma.com\/get-involved\/gsma-foundry\/?post_type=gsma_theme_resources&p=10397"},"modified":"2025-09-19T11:15:48","modified_gmt":"2025-09-19T11:15:48","slug":"turkcell-autonomous-5g-slicing-for-seamless-communication","status":"publish","type":"gsma_theme_resources","link":"https:\/\/www.gsma.com\/get-involved\/gsma-foundry\/gsma_resources\/turkcell-autonomous-5g-slicing-for-seamless-communication\/","title":{"rendered":"Turkcell: Autonomous 5G slicing for seamless communication"},"content":{"rendered":"\n

By using extended reality (XR) devices, users can collaborate on designs remotely and in real time, eliminating the need to be physically present at the same location. This approach leverages the high speed and low latency of 5G technology to enhance communication and streamline remote collaboration, ultimately driving digital transformation in industrial design processes.<\/p>\n\n\n\n

Solution:<\/strong><\/p>\n\n\n\n

The solution leverages network slicing technology on the private 5G radio access network (RAN) network, combined with artificial intelligence (AI) algorithms, to enable efficient resource management. Turkcell<\/a> trains and deploys an AI model to manage RAN resources through dedicated slices within an autonomous network architecture. In this setup, system key performance indicators (KPIs) are continuously collected to train the AI model, which autonomously generates and applies optimized resource allocation decisions. Moreover, the customer can manage their own slice through application programming interface (API) requests. In particular, the customer can issue intent-based requests, allowing the system to either respond directly or manage resources autonomously. Depending on user requests, the network owner can make decisions via APIs or delegate them to an autonomous system, allowing resource optimization to be managed automatically. This setup enables a flexible interplay between customer-driven inputs and network KPI-based AI analysis, ensuring optimal slice management.<\/p>\n\n\n\n

Impact:<\/strong><\/p>\n\n\n\n

In a fully autonomous, responsive network architecture, XR traffic is isolated from other user traffic, prioritized, and optimized through slicing, ensuring enhanced performance and minimal disruptions. By leveraging AI-driven autonomous slicing, the solution dynamically adjusts resource allocation in real-time to meet service requirements essential for immersive XR or other throughput-sensitive experiences. This intelligent resource management not only enhances user engagement but also optimizes operational efficiency, reducing operational costs. Furthermore, the flexible deployment model enables seamless scalability to accommodate varying demands while maintaining consistent performance and reliability. Additionally, the API integration facilitates self-management, particularly in private networks, empowering network owners to efficiently manage their infrastructure through the developed platform.<\/p>\n\n\n\n

Topic:<\/strong> Network optimisation, and operations and maintenance<\/p>\n\n\n\n

Cost:<\/strong> Low<\/p>\n\n\n\n

Location:<\/strong> Europe<\/p>\n\n\n\n

MNO:<\/strong> Turkcell<\/p>\n\n\n\n

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