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Digital Twin for network operations

URN C23.5.457

Winner

Enabling a highly autonomous network beyond L4 using an efficient collaboration mechanism to integrate industry’s best digital twin capabilities.

Project companies

This Catalyst is showcasing at Digital Transformation World Asia, March 14-16, 2023 in Bangkok, Thailand. Visit us at Innovation Zone kiosk C6 Attend our presentation on Wednesday 15 March, 14:45 - 15:00 To date, AI is introduced into network OAM mostly as an assistant information provider for manual decision-making. However, the requirement of L4 and L5 autonomous networks needs to improve network AI performance and engineer's trust in AN. The introduction of a digital twin network has been considered a promising approach to enable L4+ autonomy, providing low-cost testing to speed up application and solution innovation and reduce deployment risk on CSP’s real network. As a whole, the industry in general is in the initial stages of target-applying scenario exploration and PoC. Industry players investing in Digital Twin have varying areas of focus and levels of progress. Collaboration is needed to strengthen and solve the challenges in data, modeling, and computing force. A collective approach to addressing difficulties in specific scenarios and domains will avoid repeated R&D and promote quick deployment and testing on CSP’s network, ultimately enabling E2E network autonomy. This Catalyst aims to build an open digital twin platform with industry partners, and for industry partners by providing an open ecology for CSPs, research institutes, vendors and integrators, etc. This will advance opportunities for pooling the joint forces, best solutions, and capabilities in user interaction, data collection, network simulation, visualization, and optimal decision-making. Through openness in data (e-map, physical environment info, network coverage, delay, load, topology, etc.), environment (computing force, storage resource, user journey, antenna coverage, etc.), and configuration (scheduling algorithm, real network parameters, user behavior, etc.), this platform will realize closed-loop development and verification. This serves academic research in bottom communication technology, 5G+AI algorithms, simulation for academic purposes, model performance verification, and comparison. It also serves operation and maintenance in the core autonomous capabilities development, optimization, and deployment effect visualization.