KEYSIGHT demonstrates AI-powered wireless channel compression technology

Keysight Technologies Inc. (NYSE: KEYS) collaborated with Qualcomm Technologies Inc. to demonstrate machine learning-based Channel State Information compression technology for advanced wireless networks. The companies presented their findings at Mobile World Congress Barcelona 2026.

The joint lab validation showed the ML-based CSI feedback method achieved more than 40% downlink throughput improvement compared to 3GPP eType II CSI reporting in four-layer operation. The demonstration used a mobile test platform powered by a Qualcomm 5G Modem-RF together with Keysight's network emulation solutions in a controlled lab environment.

Channel State Information becomes increasingly important as 5G-Advanced networks use more antennas and wider channels for beam steering and transmission settings. However, sending detailed CSI can increase uplink reporting overhead, particularly for higher-layer MIMO systems, creating a tradeoff between performance and signaling efficiency.

The ML-based compression method provided more efficient channel representation than the standardized eType II method while maintaining information needed for beamforming and link decisions under fixed CSI feedback constraints.

"Efficient CSI feedback is fundamental as antenna dimensions and spatial layers increase," said Tingfang Ji, Vice President of Engineering and Head of 6G Research at Qualcomm Technologies. "This demonstration shows how Qualcomm's advanced machine learning algorithms can significantly improve downlink performance over conventional eType II CSI reporting."

Lucas Hansen, Vice President and General Manager of Keysight's Wireless Test Group, said the demonstration enables evaluation of ML-based CSI compression and its impact on advanced MIMO performance and 6G research directions.

The companies stated the results support scalable advanced MIMO configurations and contribute to industry exploration of AI-native physical-layer enhancements for future 6G wireless systems.

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