At CES 2026 in Las Vegas, Keysight Technologies partnered with Samsung Electronics to demonstrate the first end-to-end live new radio non-terrestrial network (NR-NTN) connection in 3GPP Release 19 band n252. Using Samsung’s next-generation commercial-grade modem chipset integrated with Keysight’s NTN Network Emulator Solutions, the team achieved seamless satellite-to-satellite mobility across low Earth orbit constellations. This public validation follows earlier demonstrations in bands n255 and n256, marking all major FR1 NR-NTN bands as proven for direct-to-cell satellite services. Keysight’s emulator recreated realistic multi-orbit conditions, live application traffic and cross-vendor interoperability, enabling chipset and device makers to assess link performance, handover latency under 200 ms, and end-user throughput of up to 10 Mbps. The milestone accelerates the readiness of next-generation LEO deployments and is expected to shorten time-to-market for commercial NTN solutions targeted for 2026 rollouts.

Keysight today launched AI Software Integrity Builder, a unified software suite designed to validate, monitor and maintain AI-enabled systems in safety-critical environments such as automotive. The solution addresses emerging standards including ISO/PAS 8800 and the EU AI regulation by providing lifecycle-based assurance across dataset analysis, model validation, real-world inference testing and continuous drift monitoring. Dataset Analysis tools apply statistical metrics to identify biases, gaps and inconsistencies; Model-Based Validation features explainable AI techniques to uncover hidden correlations; and Inference-Based Testing simulates operational scenarios to detect divergence from training performance. By consolidating fragmented workflows into a single platform, Keysight’s integrated approach generates regulatory evidence, shortens validation cycles by up to 30%, and supports continuous improvement of AI models. Thomas Goetzl, Vice President and General Manager of Automotive & Energy Solutions, emphasized that this framework equips engineering teams with transparent, auditable insights to ensure AI reliability and compliance from design through deployment.