Real-Time AI-Enabled CSI Feedback Experimentation with Open RAN



Real-Time AI-Enabled CSI Feedback Experimentation with Open RAN

Real-Time AI-Enabled CSI Feedback Experimentation with Open RAN
Research Paper / WONS 2024 / Jan 2024 / ["Machine learning/ Deep learning /Artificial Intelligence", "5G", "Wireless communication"]

"Abstract—3rd Generation Partnership Project (3GPP) Release 18 has initiated a comprehensive study of Artificial Intelligence (AI)/Machine Learning (ML) use cases for Air Interface, e.g., Channel State Information (CSI) feedback enhancement, beam management, and positioning accuracy enhancement. In order to advance the adoption of AI/ML in 5G and towards 6G, it is important to showcase the feasibility of real-time applications and data collection on platforms that closely simulate real-world deployment scenarios. In this paper, we develop the first-ofits-kind AI-enabled 5G CSI feedback enhancement platform in real-time. In our experimentation, we integrate a CSI autoencoder into the OpenAirInterface (OAI) 5G protocol stack. We demonstrate the real-time functionality and evaluate the performance of the CSI compression with the encoder running at the User Equipment (UE) and CSI reconstruction with the decoder running at the Next Generation Node Base (gNB), on an Over-the-Air (OTA) indoor experimental platform, ARENA, as well as, on an emulated environment using Colosseum, the worlds largest wireless network emulator."

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