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Communications and Network Providers

 

Mobile data traffic is projected to grow nearly fivefold by 2030, and the pressure on today’s Radio Access Networks (RAN) is already immense. Traditional RAN architectures are hitting their limits, unable to cope with the demands. 

By factoring in the increasing complexities of 5G, the forthcoming 6G deployments, the rapid expansion of edge computing and AI markets, and the emergence of new Telco business models, the need for a fundamental shift is undeniable. 

For forward-looking operators, that shift is AI-powered RAN automation. 

From interference mitigation to predictive traffic control and multi-vendor orchestration, AI is reshaping the RAN landscape — and laying the groundwork for AI-native 6G. 

23%
CAGR growth Mobile data traffic projection for 2023 – 2030

Redefining the Network with AI-RAN

AI-RAN is an approach that embeds artificial intelligence into the very fabric of the RAN infrastructure, enabling spectrum efficiency, reducing energy consumption, and adapting performance in real-time. 

A strategic partner for carriers, AI-RAN will help them enhance reliability, reduce costs, and unlock new monetization opportunities.

We’re not just enabling AI-RAN, we’re redefining the very possibilities of what networks can become.

Proving the concept: AI-RAN engineering in action

Through two groundbreaking proofs of concept (PoCs), we explored the transformative power of AI-RAN, moving beyond theory to test GPU-based acceleration in 5G Open RAN environments:

Proof of Concept 01: 5G Open RAN stack porting from CPU-based COTS to CPU + NVIDIA GPU-based COTS to evaluate performance and scalability. 

Proof of Concept 02: Reducing ghost preamble incidents via integrated deep learning.

As AI-RAN evolves from concept to reality, GlobalLogic stands at the forefront—bridging deep telecom engineering with cutting-edge AI to unlock its full potential.

The window of opportunity is now. Early adopters of AI-RAN won’t just participate in the next wave of network evolution – they’ll lead it.


If you want to learn more, discover the technical white paper Accelerating 5G SA L1 processing with the GPU