AI-Led Real-Device Wi-Fi Testing
This whitepaper explains how AI-led, real-device Wi-Fi testing enables more reliable validation of modern Wi-Fi 5, 6, 6E, and 7 networks by eliminating the gap between lab results and real-world performance. It outlines why traditional simulation-based testing fails to capture real device behaviour, RF interference, mobility, and application-level experience, leading to field failures, customer complaints, and delayed releases.
It introduces real-device + AI validation as the new standard, showing how testing with actual smartphones, routers, mesh systems, and real traffic, combined with AI-driven automation, anomaly detection, and root-cause analysis delivers accurate QoE, predictable deployments, and production-ready Wi-Fi networks.
Key Takeaways from This Whitepaper:
- Why simulation-led Wi-Fi testing fails in Wi-Fi 6E and Wi-Fi 7 networks
- How real-device testing reveals failures that labs miss
- The role of AI in automating test creation, anomaly detection, and root-cause analysis
- A new validation model that mirrors real-world Wi-Fi behaviour
- How AutoWiFi delivers predictable, repeatable, field-accurate validation