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Testing and validation are how the telecommunications industry explores new technologies, frameworks, and features, as well as how technological evolution and maturity are reflected. The test and measurement space has to be at the very cutting edge of current and future technologies, in order for them to come to fruition. These days, that means a lot of energy and effort going into figuring out how networks will implement, absorb and evolve features and technologies as widely varied as space-based, Non-Terrestrial Network communications; simple, steady RedCap; the puzzle pieces of Open RAN; the looming challenges of quantum computing and security; and of course, the shifting sands of artificial intelligence.
Perhaps most interestingly for the process-driven test and measurement space, AI-driven testing capabilities are likely to shift some aspects of testing from repeatable, highly specific and defined assessment to something that is more flexible, more automated, more continuous and potentially, more opaque—better comprehended by computing machines who can work on the order of dozens or hundreds of changes, than people.
If the industry can’t test something, it can’t understand that thing, and can’t guarantee it—and no network operator is going to hand over its network to AI without being able to test, understand and guarantee that AI’s trustworthiness. Exactly how to do that is still being worked out—but if AI is to win the trust of human telecom experts, it will only happen with consistent, proven testing.
This report draws on insights shared during RCRTech's Test and Measurement Forum to highlight the latest challenges and trends across the telecom testing landscape, and how the industry is addressing them.
