Keysight Technologies and MediaTek have announced a working prototype designed to advance AI-driven uplink optimization and model life cycle management for next-generation radio access networks (RAN). The prototype is being demonstrated at Mobile World Congress 2026, highlighting how AI-enabled, RAN-assisted intelligence can improve uplink performance in real-time while maintaining effectiveness through model retraining and over-the-air (OTA) updates.
As networks evolve, maintaining consistent uplink performance across urban, rural, indoor, and hard-to-reach locations remains a challenge. Traditional transmitter diversity techniques are typically static, limiting adaptability as coverage conditions change. In addition, AI models trained in one environment may not generalize across diverse deployment scenarios, and updating models in live networks introduces operational complexity.
Keysight and MediaTek address these challenges by combining RAN-assisted AI decision-making, site-specific model retraining, and OTA model updates within a controlled test environment designed to replicate real-world network conditions. The prototype leverages Keysight’s Channel Studio RaySim and its Network and Channel Emulation solutions to create realistic and repeatable validation scenarios. The approach is designed to deliver measurable gains in uplink throughput, spectral efficiency, and reliability while reducing operational effort across varied deployment environments. The initiative aligns with the objectives of the AI-RAN Alliance, supporting scalable deployment and continuous AI optimization in the RAN.
Mingxi Fan, Senior General Manager of Wireless Technology Group, MediaTek, said: “We’re looking forward to highlighting how instrumental uplink performance enhancement will be in scaling future mobile networks so they can support AI-era applications more efficiently. Transmit diversity is a promising technique to be implemented at the device level so it can work across a wide variety of network environments, and our collaboration with Keysight demonstrates that through open infrastructure and device cooperation, our technology will facilitate practical, scalable AI-native RAN deployments.”
Peng Cao, Vice President and General Manager, Wireless Test Group, Keysight, said: “Together with MediaTek, we have demonstrated a novel AI-enabling-AI technique which helps address the increasing demand on mobile networks’ uplink performance, capacity, and consistent end-user experiences driven by AI and AR applications. This involves training and testing the AI-enhanced transmitter model in the UE with high-fidelity real-world training datasets generated from Keysight’s RF digital twin channel emulation solutions with 3D ray tracing capabilities.”
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