A new Cloud RAN trial has proven how AI boosts network efficiency, giving operators a path to better resource management.
AT&T completed an evaluation alongside Ericsson and Intel that tested how machine learning models perform over varying radio frequencies. The setup ran on a cloud-based architecture using Intel processors. By relying on commercial off-the-shelf hardware rather than proprietary equipment, telcos can optimise total cost of ownership while avoiding vendor lock-in.
Operators are exploring how to extract more value from radio networks, testing tools like AI-native link adaptation that read channel conditions and interference levels in real time to decide transmission rates.
Rather than relying on static rules, this dynamic approach yielded throughput gains of up to 20 percent during the evaluation. Spectral efficiency also improved, providing a collaborative benchmark for how AI can improve radio access networks.
Overcoming legacy infrastructure barriers
Deploying these capabilities requires a departure from heavily integrated legacy systems. The trial utilised Ericsson software separated from the underlying physical infrastructure, running entirely on an Intel Xeon 6 system-on-a-chip.
The silicon includes advanced vector and matrix extensions built specifically to handle machine learning workloads without requiring separate graphics processing units or other discrete accelerators. Using such a hardware-agnostic design allows network operators to introduce new features quickly from the laboratory environment into commercial service.
Rob Soni, VP of RAN Technology at AT&T, said: “AT&T is leading the charge toward an open, intelligent, and scalable network future by advancing Open RAN and Cloud RAN with AI-native capabilities at their core.
“This demo highlights how AI capabilities, powered by our next-generation Cloud RAN platform, can be deployed seamlessly to drive innovation and deliver superior customer experiences.”
Accelerating AI workloads in Cloud RAN environments
Infrastructure providers are designing software stacks to function across various deployment scenarios.
Mårten Lerner, Head of Networks Strategy and Product Management, Business Area Networks at Ericsson, commented: “Together with AT&T and Intel, Ericsson is demonstrating how our domain expertise combined with AI-native RAN software can drive transformative advancements in both Cloud RAN and purpose-built deployments.
“Our industry-leading AI-native Link Adaptation serves as the first proof point on this journey. With a hardware-agnostic RAN software stack, Ericsson is committed to offering maximum flexibility and enabling all our customers to benefit from future innovations—regardless of their chosen underlying hardware.
“This milestone underscores Ericsson’s commitment to helping operators advance their networks by deploying AI functionality across the RAN stack.”
Cristina Rodriguez, VP and GM, Network and Edge at Intel, added: “This successful collaboration with AT&T and Ericsson showcases the power of Intel Xeon 6 SoC to enable and accelerate AI workloads in Cloud RAN environments.
“Xeon 6 SoC is architected to handle the demanding compute requirements of AI-native network functions, delivering the performance and efficiency operators need to unlock the full potential of intelligent networks.
“By providing a flexible, standards-based platform, Intel Xeon 6 enables service providers like AT&T to deploy innovative AI capabilities while maintaining the openness and choice that drive industry innovation.”
The trial outlines a clear path for open architectures. Adopting decoupled software and hardware models provides the agility needed to deploy machine learning tools exactly where they deliver the highest return on investment.
By prioritising interoperability and processing capabilities, operators can prepare networks to handle AI adjustments to transmission quality, ensuring better overall performance across purpose-built and virtualised Cloud RAN environments.
See also: Qualcomm: Prepping telecom infrastructure for AI-native 6G rollouts
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