To maximize the benefits of making radio-access networks more AI-native while simultaneously minimizing complexity and cost, we propose a stepwise approach based on generalization and scalability of learning.Ī holistic vision of an AI-native radio-access network (RAN) would be a system designed for artificial intelligence (AI) algorithms, in which a single AI algorithm could learn and govern most networking operations, ranging from the physical layer to Radio Resource Management (RRM).Īs appealing as a holistic vision of an AI-native RAN might seem, making it a reality would almost certainly break the logical boundaries of traditional communication protocols. “AI native” is a trending concept that is gaining momentum in many industries, and ours is no exception. SON-AI – Self-Organizing Networks based on Artificial Intelligence PHY-AI – Physical Layer based on Artificial Intelligence MSRBS – Multi-standard Radio Base Station MAC-AI – Medium Access Control based on Artificial Intelligence 3GPP – 3rd Generation Partnership Project
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