IEEE Digital Reality: Power of AI: AI/ML in the Era of 5G and Beyond

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IEEE Digital Reality: Power of AI: AI/ML in the Era of 5G and Beyond


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IEEE Digital Reality: Power of AI: AI/ML in the Era of 5G and Beyond

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AI/ML and 5G are a perfect match sharing a mutually beneficial relationship. While 5G offers very high speeds for enhanced mobile broadband (eMBB), support for a massive number of devices (mMTC), and ultra-reliable low latency communications (URLLC). AI/ML complements the technology by learning from complex patterns to provide scope for autonomous network operations, transforming 5G into a scalable real-time network that is data-driven. To optimize performance, AI/ML is used across all layers -- from disaggregated radio access networks (RAN), to integrated access backhauls (IAB), to the distributed cloud layer (Edge/Core). Just as AI/ML is useful for 5G network operations, 5G is useful for AI/ML by providing multiple points of presence for data collection & computing, control loops that can operate in multiple time scales to support distributed intelligence, deployment automation, and orchestration for the life cycle management of models. 

In this webinar, we will cover the role of AI/ML to support data-driven 5G operations to include slice management, fault prediction, security, the interplay of AI/ML with edge computing, how AI/ML is being leveraged for O-RAN, and opportunities for autonomous network operations. We will also share progress being made in the IEEE Future Networks Initiative's AI/ML working group, and the roadmap items being considered for 5G and beyond networks.

This webinar is a collaboration between IEEE Digital Reality and IEEE Future Networks. Future Networks dedicates an entire chapter to AI/ML in their roadmap project, the INGR (International Network Generations Roadmap). To access that and the other chapters of the INGR roadmap, visit futurenetworks.ieee.org/roadmap

AI/ML and 5G are a perfect match sharing a mutually beneficial relationship. While 5G offers very high speeds for enhanced mobile broadband (eMBB), support for a massive number of devices (mMTC), and ultra-reliable low latency communications (URLLC). AI/ML complements the technology by learning from complex patterns to provide scope for autonomous network operations, transforming 5G into a scalable real-time network that is data-driven. To optimize performance, AI/ML is used across all layers -- from disaggregated radio access networks (RAN), to integrated access backhauls (IAB), to the distributed cloud layer (Edge/Core). Just as AI/ML is useful for 5G network operations, 5G is useful for AI/ML by providing multiple points of presence for data collection & computing, control loops that can operate in multiple time scales to support distributed intelligence, deployment automation, and orchestration for the life cycle management of models. 

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