CNS is designing the Radio Access Neural Network (RA-NN)—a new kind of wireless intelligence system that learns to optimize your network using neural network principles.
A RA-NN reimagines the traditional radio access network as a neural network—merging wireless infrastructure with the learning principles of deep AI. It transforms how networks adapt, replacing static heuristics with learning-based control guided by performance gradients.
This paradigm shift turns configuration into computation—enabling every cell to learn, adapt, and optimize its role within the larger system.
For decades, radio networks have been tuned to perform.
What if they could learn to perform?
The RA-NN reframes optimization as learning — not just about data, but about structure, behavior, and cause.
The result isn’t smarter tuning...
It’s a system that understands how to get better.
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