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Unleash the potential of generative AI in 5G networks for network slicing

URN C25.0.839

Topics 5G monetization, AI (Artificial Intelligence), Network slicing

Telecom industry revolution and potentially address the customer experience in B2B2X markets

Project companies

Today in our Industrial Market, Spectrum is not correctly shared for the B2B2X(B2C & B2B) customers, and so the network slicing too. For example from the User Equipments (UEs) - Smartphones, Robots, Smart Watch are underutilizing the spectrum bandwidth or the overutilization happens of bandwidth as we don’t have exact KPIs in the performance management domain to say that we should use this slicing in this level of Band (Low, Mid and High level)of mmWave, eMBB, URLLC) based on latency of the UEs coming from Performance Management KPIs. Business Value : Potentially Address the CSPs real-time user experience and telecom industry revolution for B2B2X Customers(B2C & B2B) Approach : 1. Use Large Language Model(LLMs) for Network Slicing in 5G Networks to address Spectrum Management(Dynamic Spectrum Sharing) across all level Band(Low, Mid and High level)of mmWave, eMBB, URLLC using enhanced Fault & Performance Management APIs 2. Address Spectrum Management(DSS -Dynamic Spectrum Sharing), Network slicing in 5G Networks for Service Orchestration by using AI/ML algorithms of Fault & Performance Management to bring Enhanced Customer Experience(B2C), (B2B) and (B2B2X) based on UEs - Smartphones, Robots, Smart Watch