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.
News
Jan. 2025
Namhyun Kim and Kengmin Lin started their Ph.D. in Electrical Engineering at Arizona State University and joined the Wireless Intelligence Lab.
Jan. 2025
Dec. 2024
The paper “Environment Semantic Communication: Enabling Distributed Sensing Aided Networks” has been accepted to the IEEE Open Journal of the Communications Society.
Dec. 2024
The paper “Camera Based mmWave Beam Prediction: Towards Multi-Candidate Real-World Scenarios” has been accepted to the IEEE Transactions on Vehicular Technology.
Dec. 2024
Nov. 2024
The paper “Large Wireless Model (LWM): A Foundation Model for Wireless Channels” is available on arXiv. Find more details on the LWM website.
Nov. 2024
Nov. 2024
Two papers have been accepted to the IEEE Transactions on Communications.
Oct. 2024
Ph.D. student Shuaifeng Jiang presented his paper “Digital Twin Assisted Beamforming Design for Integrated Sensing and Communication Systems” at Asilomar.
Ph.D. student João Morais presented his paper “A Dataset Similarity Evaluation Framework for Wireless Communications and Sensing” at Asilomar.
Ph.D. student Hao Luo presented his paper “Digital Twin Aided Compressive Sensing: Enabling Site-Specific MIMO Hybrid Precoding” at Asilomar.
Sep. 2024
The paper “Zone-Specific CSI Feedback for Massive MIMO: A Situation-Aware Deep Learning Approach” has been accepted to the IEEE Wireless Communications Letters.
Support
The Wireless Intelligence Lab is grateful for the support it is receiving from the following organizations




