Digital Future Institute of the Khalifa University of Science and Technology has launched ‘RF-GPT’, a first-of-its-kind radio-frequency AI language model capable of interpreting wireless signals, overcoming a major limitation in telecommunications AI, where language models typically operate only on text and structured network data.
RF-GPT demonstrated consistent performance improvements in radio-frequency spectrogram tasks, outperforming existing baseline models by up to 75.4 percent, reflecting strong radio-frequency understanding. The model also correctly counted the number of signals in a spectrogram nearly 98 percent of the time, a capability that general-purpose AI models rarely achieve.
The RF-GPT model works by transforming radio signals into visual patterns that artificial intelligence systems can understand. After this conversion, the system analyses the patterns and answers questions about activity in the wireless spectrum using plain language.
The foundation model aligns with the UAE National Artificial Intelligence Strategy, helping pave the way for more autonomous and intelligent wireless networks.
RF-GPT was trained on around 625,000 computer-generated radio signal samples. It is intended for telecommunications operators, network engineering teams, and spectrum authorities to manage increasingly complex wireless environments.
The model has shown strong performance in tasks such as identifying signal types, detecting overlapping transmissions, recognizing wireless standards, estimating device activity in Wi-Fi networks, and extracting information from 5G signals.
RF-GPT research team
The project was developed by researchers at Khalifa University, led by Professor Merouane Debbah, Senior Director of the Digital Future Institute. Key contributors include postdoctoral fellows Hang Zou and Yu Tian, research scientists Dr. Lina Bariah, Dr. Samson Lasaulce of Université de Lorraine, and Dr. Chongwen Huang, along with PhD student Bohao Wang from Zhejiang University.
Professor Ahmed Al Durrah Associate Provost for Research Khalifa University
“The launch of ‘RF-GPT’ reflects Khalifa University’s long-term focus on innovation in digital infrastructure to advance AI integration across strategic sectors and next-generation connectivity research, aligned with national priorities. Initiatives such as this model contribute to the UAE’s rapidly growing human capital and research capabilities necessary to support the country’s evolving digital ecosystem.”
Professor Merouane Debbah stated that, “RF-GPT represents a turning point for spectrum intelligence, moving from isolated, task-specific radio-frequency pipelines towards a unified RF-language interface. We gave a language model its first glimpse of the electromagnetic spectrum, and the view is already remarkable. By making the physical layer queryable in natural language, we open the door to AI-native radio systems, where RF perception can directly support network optimization and policy decisions, a crucial step towards future AI-native 6G networks.”
