A useful PoC should answer a decision: does the use case work, under which conditions, and what is needed next? That requires a representative application, a working network, and measurements tied to the customer’s objective.
BubbleRAN combines a configured MX-PDK testbed, reusable deployment workflows, and project-scoped integration services to support application PoCs, customer demonstrations, and field validation. For integrated industrial O-RAN and multi-cell trials, start with MX-PDK O-RAN or MX-PDK AI-RAN. A small 5G or near-RT RIC/xApp PoC can begin with MX-PDK LAB, using its optional OTA Pack when live SDR radio is needed.
Choose the product that fit your PoC
| What you need to prove | Recommended product | Why it fits |
|---|---|---|
| A small end-to-end 5G application PoC, configuration experiment, or near-RT RIC/xApp prototype | MX-PDK LAB | One pre-installed node, emulated RAN/Core/UEs, near-RT RIC, xApp SDK, and CDK; optional OTA Pack for live SDR validation. |
| Industrial O-RAN 7.2 integration, non-RT RIC/rApps, or a larger single-cell trial with a commercial UE fleet | MX-PDK O-RAN | Includes one industrial O-RU, two O-Cloud nodes, five commercial UE modules, both RICs, xApp/rApp SDKs, and agentic observability. |
| Mobility between two live cells, applications on 5G edge nodes, or agent-driven automation | MX-PDK AI-RAN | Includes two O-RUs, three O-Cloud nodes, five Pictel edge nodes, the Automation Blueprint, and BAT Agent DevKit. |
| Coverage across buildings or outdoor areas, with enterprise infrastructure and Digital Twin workflows | MX-PDK CAMPUS | Provides enterprise infrastructure, GPU capacity, and Network Digital Twin capabilities, with optional indoor and/or outdoor radios selected for the site. |
Choose by the capability the trial must validate. MX-PDK LAB with the OTA Pack can cover a small live 5G or xApp PoC; industrial O-RAN fronthaul and non-RT RIC/rApp requirements point toward MX-PDK O-RAN. For a focused mobility trial without the AI suite, O-RAN can also be extended with a second compatible O-RU and the required capacity.
Value for your team
- Make investment decisions with evidence: identify what is feasible and which constraints matter before expanding.
- Reduce repeated engineering: reuse network configurations, applications, dashboards, and test procedures.
- Improve stakeholder confidence: demonstrate the use case with visible measurements and documented conditions.
- Plan the next phase accurately: turn trial findings into radio, compute, integration, and support requirements.
What this solution brings together
- A validated network baseline. Deploy the selected RAN, Core, O-RAN control functions, devices, and observation tools using repeatable blueprints.
- The application in the test loop. Integrate the selected customer application and devices, then evaluate the complete communication path and relevant operating conditions.
- A measurable trial workflow. Define the scenarios, traffic profiles, metrics, and pass criteria before the demonstration. Keep the configuration and datasets needed to reproduce each result.
- A path into the field. Scope the radio hardware, antennas, transport, timing, compute, installation, and support to the actual environment.
More use cases you can unlock
Choose the application first, then the platform and extensions required to demonstrate it. The examples below are trial opportunities, with acceptance criteria agreed for the selected configuration.
| Related trial | What the customer can learn | Starting product and scope |
|---|---|---|
| Connected video and remote inspection | Whether image delivery, uplink demand, and application response meet the intended workflow. | O-RAN for a focused live connectivity trial; AI-RAN for edge inference or agent automation. Cameras, application software, and any required GPU are scoped separately. |
| Mixed-traffic QoS and slice trials | How supported policies affect competing data flows and application performance. | O-RAN for a single-cell baseline; AI-RAN for two-cell evaluation. Define the traffic mix and available stack/device controls. |
| TN/NTN service feasibility | How the application behaves in supported terrestrial or non-terrestrial scenarios before a more costly field campaign. | O-RAN or AI-RAN using supported emulated profiles. A live NTN trial needs additional radio and integration scope. |
| Sensing and positioning demonstrators | Whether supported radio measurements can support a target sensing or localization experiment. | O-RAN with an appropriate stack and LLC/SRS I/Q workflow. Sensing algorithms, calibration, and experimental geometry are project-specific. |
| AI-assisted incident investigation and response | Whether an agent can gather useful evidence, propose an appropriate action, and improve the measured outcome. | O-RAN for observability-led investigation; AI-RAN for the included Automation Blueprint and agent development tools. Define the task and approval process. |
| Energy and capacity trade-off trials | How resource choices affect application performance and measured node power. | O-RAN or AI-RAN with optional energy visibility/PDU control; CAMPUS includes these capabilities and the Digital Twin optimization path. |
From initial question to deployment evidence
| Step | Focus | Result |
|---|---|---|
| Define success | Agree the use case, devices, traffic, environment, and decision the trial must support. | Requirements and an acceptance plan. |
| Build the baseline | Configure the selected MX-PDK platform and integrate the application. | A repeatable end-to-end setup. |
| Run the campaign | Execute agreed scenarios in the lab and, where scoped, in the field. | Measurements, observations, and identified limitations. |
| Decide the next step | Compare outcomes with the acceptance criteria and review scaling requirements. | A go/no-go decision or a targeted improvement and deployment plan. |
Agree acceptance metrics around the application: uplink/downlink throughput, latency, jitter, packet loss, radio conditions, and resource use. Mobility trials also measure handover behavior and application continuity. Numerical targets are established for the chosen hardware, traffic, and environment.
Scope the field deployment
The standard O-RAN and AI-RAN bundles include indoor O-RUs. An outdoor or mobile installation needs a configuration matched to coverage, available spectrum, mounting, power, transport, synchronization, and environmental conditions. Field services and additional hardware are scoped with the trial.
O-RAN, AI-RAN, and CAMPUS configurations are quoted to the trial requirements. The software license includes one year of updates and technical support. Trial integration, training, and on-site support are agreed as part of the project scope. Reusable blueprints, applications, APIs, and workflows support continuity between the lab baseline and the next deployment phase.
FAQs
1️⃣ Do we need AI-RAN for every PoC?
No. Start with MX-PDK LAB for a small 5G or near-RT RIC/xApp PoC, adding the OTA Pack when live SDR validation is needed. Choose O-RAN for industrial O-RAN fronthaul, non-RT RIC/rApps, or its larger integrated setup. AI-RAN is the stronger starting point when the packaged two-cell environment, 5G edge nodes, or agent automation are central to the demonstration.2️⃣ Does a successful PoC establish production readiness?
It provides evidence under the tested conditions. Broader deployment also requires agreement on coverage, capacity, availability, security, operations, and support, followed by validation against those requirements.3️⃣ Can we use our own devices and application?
Yes, subject to compatibility and integration scoping. Share the device models, supported bands, application architecture, interfaces, and traffic requirements so these can be reflected in the configuration and test plan.Ready to define a PoC that answers your deployment question?
Share the use case, devices, indoor or outdoor setting, mobility needs, target metrics, and timeline. BubbleRAN can recommend the starting product and propose the integration and trial scope.