Building the Cognitive Network: Pillars of AI-Native Wireless ecosystem

Supratik Bhattacharjee, Sharad Sambhwani

Keywords: 6G AI Native, Wireless Machine Learning, Life Cycle management, End to End Learning, Multi-Modal fusion, Predictive network, Self optimizing

TL;DR: The future network will be cognitive: aware of its environment, predictive of the future, and capable of learning and evolving to meet demands we can’t even yet imagine. This is the path to a truly intelligent and connected world.

Abstract:

Classical wireless system design, which has underpinned generations up to 5G, depends on simplified or approximately linear mathematical models that are increasingly insufficient for
the unprecedented complexity of future 6G and beyond networks.
%Traditional wireless design, based on simplified linear models, is inadequate for the non-linear complexity of future 6G networks.
This paper proposes a paradigm shift to an AI-Native framework that makes the network inherently intelligent, rather than just managed by AI.
This vision is built on six pillars, including reinforcement learning for self-optimization, predictive forecasting, a learned physical layer,
generative models for digital twins, multi-modal data fusion, and hyper-local model management.
We argue that this AI-Native approach represents not an incremental improvement, but a
necessary evolution, transforming wireless systems into autonomous, adaptive ecosystems capable of
meeting the demands of a hyper-connected future.

Submission Number: 38