RCRTech report tracks RAN's shift toward software-defined, AI-driven models
A new RCRTech report examines how radio access networks are moving from hardware-focused designs to software-defined, open and AI-enabled systems. It focuses on the convergence of AI RAN, Cloud RAN and Open RAN as operators prepare for 5G-Advanced and 6G. The report covers deployment approaches, standards and efficiency goals for future wireless networks.
The RCRTech report focuses on radio access networks as they move away from designs centered on dedicated hardware. It examines three related approaches—AI RAN, Cloud RAN and Open RAN—and how they are converging as operators prepare for 5G-Advanced and 6G.
The report also looks at deployment methods, evolving standards and efficiency objectives for future wireless networks. Its scope is the transition toward more software-defined, open and AI-enabled RAN systems.
The shift could affect mobile users through potentially more adaptable and efficient networks, while equipment vendors, software developers and operators may face changing design and skills requirements. Communities relying on wireless connectivity might see gradual changes in service flexibility and sustainability, though outcomes depend on deployment choices and standards. The report’s framing may shape industry priorities, but its practical effects on society would likely emerge over years rather than immediately.