Our Research Builds the Next-Generation
AI-Powered Sensing and Communications Systems
Directed by Prof. Ahmed Alkhateeb, the Wireless Intelligence Lab focuses on leveraging signal processing and machine learning to address the key challenges of future wireless communication systems and enable new sensing and positioning capabilities. We develop enabling technologies, mathematically evaluate their theoretical limits, build proof-of-concept hardware prototypes, and demonstrate the developed solutions in real-world environments.
Announcement
We are always looking for highly-motivated Ph.D. students to join our lab. Interested students are encouraged to contact Prof. Alkhateeb with a brief resume.
Research Highlights
News
Oct. 2026
The paper “LWM-TF: A Wireless Foundation Model on 5G NR Time-Frequency Resource Grids” has been accepted to the IEEE Journal of Selected Topics in Signal Processing.
Oct. 2026
Ph.D. student Tawfik Osman presented his paper “RIS-Assisted Near-Field Sensing in 5G O-RAN Systems Using Downlink PRS” at Asilomar.
Ph.D. student Preston Garrett presented his paper “Wireless Digital Twin Calibration: A Small-Scale Real-World Prototype” at Asilomar.
Ph.D. student Hao Luo presented his paper “Wireless Digital Twin Calibration: Refining DFT-Domain Channel Information” at Asilomar.
Sep. 2026
Tawfik Osman successfully defended his Ph.D. dissertation and joined Apple. Congratulations!
Aug. 2026
The paper “Digital Twin-Aided Prescreening for User Scheduling in MU-MIMO Downlink Systems” is available on arXiv.
May. 2026
Ph.D. students Hao Luo and Namhyun Kim are interning at InterDigital in Summer 2026.
Ph.D. student Sadjad Alikhani is interning at TeraSpatial in Summer 2026.
Ph.D. student Kengmin Lin is interning at VIAVI in Summer 2026.
Jan. 2026
Five papers have been accepted to the IEEE ICC 2026.
LWM-Temporal: Sparse Spatio-Temporal Attention for Wireless Channel Representation Learning
LWM-Spectro: A Foundation Model for Wireless Baseband Signal Spectrograms
Digital Twin Aided Millimeter Wave MIMO: Site-Specific Beam Codebook Learning
Low-Complexity Digital Twin for CSI Acquisition in MIMO Communications
Generative Decoding of Compressed CSI for MIMO Precoding Design
Jan. 2026
The paper “Wireless Dataset Similarity: Measuring Distances in Supervised and Unsupervised Machine Learning” is available on arXiv.
Oct. 2025
Dr. João Morais presented his paper “Comparing Stochastic and Ray-tracing Datasets in Machine Learning for Wireless Applications” at Asilomar.
Oct. 2025
The paper “RIS-Aided mmWave O-RAN: Coverage Extension and User Mobility Handling” is available on arXiv.
Oct. 2025
Shuaifeng Jiang successfully defended his Ph.D. dissertation and joined Bosch. Congratulations!
Support
The Wireless Intelligence Lab is grateful for the support it is receiving from the following organizations
