Telus tapped long-time equipment vendor Samsung for the first Canadian deployment of an AI-powered radio access network (RAN) intelligent controller (RIC), marking AI’s continued progress in driving RAN opportunities.

The deployment involves Telus using Samsung’s RIC platform and accompanying applications from Samsung’s CognitiV Network Operations Suite (NOS). The initial list of applications includes the KPI Anomaly Detector and RAN Anomaly Inisight to proactively identify and analyze network issues; the Energy Saving Manager for dynamic traffic prediction and automated orchestration of energy saving features; and the Load Balancing Manager to optimize resource utilization and improve network performance.

The RIC operates in the middle of an open RAN deployment as a kind of linkage to the wider network. It allows operators to deploy xApps and rApps that then allow operators to design and control RAN functions, providing administrative RAN sovereignty over functions that are typically implemented as proprietary features on base stations.

These “apps” are microservices-based applications operating in near-real time (xApps) and non-real time (rApps) that provide an operator with more control over their open RAN environments.

Bernard Bureau, VP of wireless strategy and 5G services at Telus, explained that this initial application list is focused on energy and network efficiency, but that it plans to add more than a dozen of new applications each year over the next couple of years.

That initial focus on efficiency is important as power savings is significant for operators that are operating tens-of-thousands of individual 5G cell sites. An early report from MTN Consulting found carrier’s spent 5.2% of their capex in 2020 on electricity, fuel, and water.

The evidence that 5G is driving costs higher is “modest,” but the increases “serve as a good reminder that telcos will need to seek out energy efficient equipment, software, and network architectures as 5G penetration grows,” Matt Walker, chief analyst at MTN Consulting, wrote in the report.

Verizon earlier this year reported a successful multivendor deployment with Samsung and Qualcomm using an AI-infused RAN management application running on a RIC that was also focused on efficiency.

That deployment used Qualcomm’s Dragonwing RAN automation suite RIC running Samsung’s AI-powered Energy Saving Manager (AI-ESM) application to help Verizon manage power consumption of its open RAN deployment. Verizon claims it has been able to produce 15% energy savings on average, “with a maximum of 35% per sector during low traffic periods in a variety of field trials.”

Long-standing Samsung support

Telus’ Bureau explained that Samsung’s RIC platform is able to support both legacy hardware-based and more modern virtualized network architectures. This provides support for Telus’ multi-year move toward modernizing its entire network architecture.

Bureau added that this was one of many reasons why Telus selected Samsung for this project.

“All RAN equipment suppliers have their own version of RIC with varying levels of maturity,” Bureau said. “Not all of them are open to manage stuff that goes beyond managing their own equipment, so that's the first differentiator, and Samsung did exceptionally well on that.”

Bureau also noted that a number of “third-party RIC suppliers … unfortunately have disappeared due to mergers and acquisitions, the buying company deciding that it wasn’t a strategy anymore.”

The deployment also builds on long-standing work between Telus and Samsung.

Samsung initially provided RAN equipment to Telus in 2019, which evolved into a virtualized RAN (vRAN) deployment beginning in late 2023. That relationship deepened in early 2024, when Telus tapped Samsung to provide the open RAN equipment.

Bureau noted that this long-standing collaboration contributed to Telus selecting Samsung to provide the latest pieces of equipment and software.

“The trust was there, the collaboration was there, the commitment was there to work together,” Bureau said. “This is new stuff, obviously, so a lot of rApps are in there right now, but a lot of them are going to be deployed over the coming years. And Samsung had a totally open mind about this total openness in terms of flexibility for Telus to build their own rApps or use third-party rApps.”

AI running the RAN

The deployment also deepens AI’s thrust into the RAN market.

“Formal” efforts toward unifying AI-RAN began just ahead of last year’s MWC Barcelona event, when a handful of big-name vendors and operators threw their support behind the aptly named AI-RAN Alliance organization. Those names included Amazon Web Services (AWS), Arm, Ericsson, Microsoft, Nokia, Samsung Electronics, SoftBank, Nvidia, DeepSig, T-Mobile US, and Northeastern University.

The framing goal of the group was to steer the use of AI into RANs for better performance, lower operating costs, greater efficiencies, and to support new business models. That work was to include using AI to improve RAN spectral efficiency, combine the two for more efficient network utilization, and deploy AI at the network edge to support new services.

AI-RAN Alliance membership growth also surged over the past year, with the organization touting 75 total members. That organization’s growth was also highlighted by it naming former head of the O-RAN Alliance to head the AI-RAN Alliance work.

One of the more notable moves came late last year when T-Mobile US partnered with Nvidia, Ericsson, and Nokia on an AI-RAN Innovation Center that will house a focused effort on tying together cloud-based RAN and AI development. The carrier noted in a presentation that the goal is to integrate cloud-based RAN and AI using unified infrastructure that can scale to serve millions of mobile users at once.

“AI-RAN will enable new AI algorithms to unlock the full potential of wireless networks,” T-Mobile US’ presentation noted. “These AI algorithms would be rapidly developed with software-defined RAN, trained on AI data centers, and fine-tuned with physically accurate digital twins. This will lead to dramatic improvements in spectral and energy efficiencies.”

Analysts have pointed to the benefits AI can bring to the deployment and management of cloud-based open RAN networks, which are more complex orchestration challenges due to the disaggregated multivendor ecosystem. The use of AI could help close performance gaps for open RAN architectures compared with legacy RAN models.

However, there does remain some hesitancy.

Ian Hood, CTO for telecommunications at Red Hat, noted in a press briefing earlier this year that there remains some trepidation toward fully embracing any new technology.

“There's always hesitancy in the market to take on new things,” Hood said, referencing the continued challenges around open RAN technology. “We have to make sure that it’s easy enough to automate and scale and deliver those business benefits to that portion of the network. … So we're going to make this so that it’s easy to add this and add that value to this business. So there is some hesitancy, but we're working through this, and it's an ongoing effort for our industry.”

Chivas Nambiar, GM of telco at Amazon Web Services (AWS), expressed similar concerns, which could delay the influence of the AI-RAN Alliance and broader adoption of AI-RAN until the next big investment cycle.

“There's a fair bit of work in that alliance to try and figure out what the next phase of running RAN functions on top of GPU accelerated infrastructure looks like. I think that's still pretty early in the conversation,” Nambiar said. “So far, a lot of people are playing around with it, but my expectation, personally, is that as we get closer to that 6G evolution that's where it's really going to start to become a decision point of whether we see the cost and performance benefits of the GPU infrastructure running these functions, and that supersedes what we see in custom built accelerator costs.”

Despite the hurdles, analysts see an AI-RAN opportunity.

Dell’Oro Group recently forecast that AI-RAN sales will make up one-third of overall RAN spending by 2029, hitting roughly $10 billion in revenues. The firm suggested that existing RAN radio and baseband suppliers are “well positioned” to take advantage of the initial wave of AI-RAN – a finding boosted by the fact that the top five RAN suppliers (Huawei, Ericsson, Nokia, ZTE, and Samsung) were responsible for around 95% of the 2024 RAN revenue.

“There is strong consensus that AI-RAN can improve the user experience, enhance performance, reduce power consumption, and play a critical role in the broader automation journey," Dell'Oro Group VP Stefan Pongratz explained. “Unsurprisingly, however, there is greater skepticism about AI’s ability to reverse the flat revenue trajectory that has defined operators throughout the 4G and 5G cycles.”