For starters, automation and cloud-native tooling are making Open RAN more scalable, not less
Despite the very real progress made around Open RAN, a few myths still linger. Many still believe the technology remains experimental, while others assume it is only suitable for limited, rural deployments — not dense, urban, or complex RAN environments. Wind River CTO Paul Miller told RCR Wireless News that these assumptions are outdated. In his view, Open RAN has moved well beyond early trials and is now a mature, carrier-grade technology being deployed at scale.
Here are a few of the most persistent myths still circulating:
Myth #1: Open RAN performance and optimization are lacking
One common misconception is that Open RAN networks cannot match the reliability or performance of traditional RAN systems. Miller pushed back strongly against that idea, pointing to years of ecosystem progress.
“Collaboration on standards, well-defined interfaces, successful Plug fests, vendor interoperability certifications have all helped expand the ecosystem, reduce interworking complexity, and productize open components for a telco network,” he said.
He added that executives from global CSPs have confirmed Open RAN deployments are comparable — and in some cases superior — to traditional RAN networks in terms of reliability and performance.
Still, Miller noted that optimization in a disaggregated network looks different from that in a monolithic one. Traditionally, tuning focused largely on RF performance, since the RAN stack itself was assumed to be validated and optimized. “The most common misunderstanding is that tuning a disaggregated RAN is simply a virtualized version of tuning a traditional ‘monolithic’ RAN,” he explained.
Instead, complexity shifts into the cloud platform layer, including hardware accelerators, real-time operating systems, and the software needed to deliver the consistent latency and jitter performance required by the 5G distributed unit.
In addition to cloud platform optimization, Miller said operators must also address tuning across multiple parts of the stack, including:
- Power consumption optimization
- Fronthaul and midhaul interface latency
- Resource pooling across compute, storage, and memory under varying loads
Myth #2: Open RAN is harder to operate at scale
Another lingering belief is that Open RAN introduces operational complexity that makes large-scale deployment unrealistic. Miller argued the opposite: that automation and cloud-native tooling are making Open RAN more scalable, not less. “Operational efficiency is the lifeline of a telecom network deployed at scale,” he said. “Efficiency can only be achieved via automating Day 0 to Day n operations of the network.”
He pointed to centralized monitoring and automation platforms as key enablers, replacing vendor-specific processes with repeatable, software-driven workflows.
Together, he said, these capabilities have helped transform Open RAN into a carrier-grade operational model that matches — and in some cases improves upon — the efficiency of traditional RAN, while accelerating innovation and service deployment.
Myth #3: Open RAN introduces new security risks
Security has also been a major concern since Open RAN’s early days, particularly around responsibility in a disaggregated architecture with more interfaces.
But Miller emphasized that Open RAN does not inherently increase risk. “When properly implemented, it can strengthen security posture through greater transparency, automation, and control,” he said. While Open RAN does expand the number of interfaces in a telecom network, he argued it also enables a zero-trust, cloud-native security model that is difficult to achieve in closed, proprietary RAN systems.
Myth #4: TCO is the only metric that matters
Finally, Miller said Open RAN’s success should not be judged solely on cost savings.
“While TCO is a compelling metric to measure the success of Open RAN, it is important to understand the value a disaggregated network brings to the operator,” he said. The real value, he continued, lies in operational agility — faster feature deployment, autoscaling, and continuous optimization.
He pointed to one U.S. operator that replaced its cloud platform across 25,000 commercial sites in just three months, a shift he said would have been nearly impossible in a traditional RAN environment.
