Impact at a Glance
- 2 times faster innovation cycles
- Demos using MX-PDK: 1 showcased, 1 running, 1 planned
- Number of team members in research teams actively using the platform: 7
- Advanced artifacts under evaluation: 6
As Europe accelerates investment in next-generation connectivity, research institutions are under growing pressure to validate 5G and 6G concepts faster, and in more flexible and interoperable environments. For the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), experimentation platforms are no longer simply technical infrastructure, they are strategic enablers of innovation.
Based in Castelldefels, Spain, CTTC is a leading European telecommunications research institution focused on advanced communication systems, network architectures, and applied digital technologies. Within its research ecosystem, the ADAPT (Adaptive Processing Technologies) unit is leveraging BubbleRAN MX-PDK to accelerate experimentation in cloud-native and AI-driven network environments.
One Multivendor Platform
One of the key objectives of CTTC’s ADAPT research unit was to reduce the operational and maintenance complexity associated with deploying and validating advanced 5G and O-RAN environments. As research initiatives become increasingly multi-vendor, AI-driven, and cloud-native, significant effort is often spent on infrastructure integration and maintenance rather than on innovation and experimentation itself.
For ambitious R&D organizations targeting higher Technology Readiness Levels (TRLs), shortening the path between concept development and real-world validation is critical. CTTC therefore required an environment that would enable researchers to rapidly prototype, test, and iterate without repeatedly rebuilding complex underlying network infrastructures.
What began between CTTC and BubbleRAN in 2024 as a technology collaboration quickly evolved into a strategic partnership focused on accelerating advanced telecom research and innovation. Leveraging the BubbleRAN MX-PDK platform, CTTC benefits from rapid prototyping methodologies, O-RAN and AI-RAN DevKits, a catalogue of reusable artifacts and comprehensive technical resources.
According to Nikolaos Bartzoudis Senior Researcher and Head of the ADAPT Research Unit, the immediate value came from reducing deployment complexity while maintaining the flexibility to experiment across the full telecom stack: from RAN and core networks to cloud-native orchestration and AI-driven applications.
“What stood out immediately was how much complexity BubbleRAN had already solved for us; deploying a full 5G O-RAN network with a single command felt almost too good to be true, but it works. Their team brings deep, hands-on expertise across the full stack: RAN, core, O-RAN interfaces, and cloud-native orchestration. It’s rare to find that breadth in one place.“ says Nikolaos Bartzoudis.
CTTC selected BubbleRAN MX-PDK not only for its technical capabilities, but also for the depth of engineering collaboration behind the platform. For research teams operating at the frontier of AI-native and O-RAN experimentation, access to responsive expertise and adaptable tooling was essential.
Beyond the platform itself, CTTC highlighted the value of BubbleRAN’s documentation ecosystem and direct developer engagement. This allows research teams to focus on experimentation and innovation rather than platform integration overhead.
The collaboration gained momentum through the EU-funded VERGE project under the Smart Networks and Services Joint Undertaking (SNS JU), where CTTC used the BubbleRAN MX-PDK platform to support experimentation around open and secure edge architectures.
Faster from Idea to Proof of Concept
Using BubbleRAN MX-PDK, CTTC’s ADAPT teams have been able to perform numerous experimentations around AI-driven network automation, particularly in the development of rApps and xApps for traffic prediction and network decision-making. The research teams integrated internally fine-tuned machine learning models directly into the BubbleRAN environment, enabling rapid validation and iterative optimization within realistic network scenarios. MX-PDK doubled the pace of their research agenda.
For CTTC researchers, one of the most significant advantages has been the platform’s flexibility and multi-vendor adaptability. By reducing the operational burden associated with deploying and orchestrating complex 5G and O-RAN environments, the teams have been able to focus more directly on innovation.
The collaboration has also expanded CTTC’s access to end-to-end networking expertise spanning RAN, core, orchestration, and AI-native network operations.
Co-creating AI-native networks
Looking ahead, CTTC plans to extend its research activities toward more advanced AI-native network operations and autonomous optimization scenarios, leveraging the BubbleRAN MX-AI platform. A key focus will be evaluating and comparing machine learning models for network traffic prediction and decision-making, helping researchers better understand how AI can support future network operations.
In parallel with ongoing experimentation, CTTC is advancing a research publication on machine learning for network prediction, further strengthening the scientific rigor and external validation of its R&D efforts. CTTC and BubbleRAN are also exploring future collaboration opportunities within upcoming European research initiatives.
The collaboration between CTTC and BubbleRAN reflects a shared commitment to advancing telecom research. Working closely together, both organizations are accelerating experimentation and validating next-generation network concepts. Together, they are pushing the boundaries of 5G and 6G innovation in a more open, flexible, and scalable way.