- Anritsu plans to showcase AI-driven, cloud-based, and virtual testing tools centered on 6G at MWC 2026.
- The company is enhancing its MT8000A platform to support a wider spectrum range, reaching up to 16 GHz, while also introducing new testing capabilities for non-terrestrial networks (NTN).
- Demos include digital-twin style lab replays, cloud-based automotive validation, and real-world IoT power consumption measurement.
Anritsu plans to showcase a fresh lineup of 6G test-and-measurement demos at Mobile World Congress 2026, focusing strongly on AI, cloud integration, and virtualized testing. Their goal is to speed up early 6G standardization and validation during the technology’s formative stage. 1
This is crucial now since “6G” remains largely theoretical, yet engineering teams are busy crafting the tools and workflows that will define its feasibility. Without the ability to measure and replicate, shipment is impossible.
With 5G, the industry quickly discovered the challenge: more spectrum, more devices, more edge cases. Validation efforts grew rapidly, and the brunt of the struggle showed up early on in the labs.
Anritsu is signaling a shift in 6G development: moving away from one-off lab setups toward software-driven, repeatable test environments that can seamlessly transition between physical racks and virtual infrastructure without breaking down.
At MWC 2026 in Barcelona (Hall 5, Stand D41), Anritsu plans to unveil a 6G Test Platform alongside a Virtual Signalling Tester designed for early-stage research. This includes physical layer testing—focusing on the raw radio signal—and MAC testing, plus DIQ/RF interface validation through software-defined radio. The platform features an arbitrary waveform output function to support pre-standard experimentation. Updates to the MT8000A Radio Communication Test Station are also on display, extending support for upper mid-band frequencies up to 16 GHz. Software upgrades enable non-terrestrial network testing, covering Direct-to-Cell and NR-NTN, with real-time satellite and aerial link emulation. Additional demos include Field Simulation Test for lab-based propagation and “digital twin” development, a cloud-based virtual automotive testing setup with Valeo, an IoT power-consumption evaluation platform developed with Qoitech and SmartViser, and an AI-driven Service Assurance platform aimed at boosting autonomous network operations. 2
The underlying message is clear: 6G testing is evolving into a software engineering challenge, moving beyond just RF engineering.
Here’s a quick decoding of the jargon. FR1, FR2, and FR3 refer to distinct “neighborhoods” within the spectrum. Validating across all of them on a single platform cuts down on the tool-switching that drags teams down. NTN, or non-terrestrial networks, covers satellites and aerial links, putting them in the same testing framework as regular cellular networks.
The AI story is sharpening its focus. It’s no longer just “AI will help someday.” Now, AI is integrated directly into workflows—handling test data, untangling complex scenarios, and generating test sequences informed by previous runs.
Field-style simulation marks a subtle yet significant change. By capturing real-world signal propagation and recreating it in the lab, engineers can tackle complex, hard-to-reproduce network issues more effectively. This approach becomes especially valuable as concepts like integrated sensing and communications push networks past mere data transmission.
Automotive plays a role here as well, with cars evolving into mobile software hubs. Relying solely on physical vehicles and test tracks for validation can delay schedules; virtual testing offers a path forward when the hardware isn’t yet available.
Testing IoT power isn’t glamorous, but it matters. Battery life is a key selling point, and devices often fall short when it comes to “real-world power consumption.”
There’s a lot that could still go off track. The 6G standards haven’t been finalized, so what vendors prioritize now might change as the industry settles, which means test methods that seem solid today might require adjustments down the line. On top of that, AI-driven testing only delivers results if the underlying data and models are accurate; otherwise, flawed assumptions just speed up the production of incorrect outcomes.
Anritsu’s message ahead of MWC is clear: it plans to showcase advanced test solutions targeting the next phase of wireless tech. The real question is whether these will translate into usable pilot workflows that engineers can implement right away, or if they’ll remain just another set of “future 6G” demos confined to the booth. 3
