Southern University of Science and Technology Uses AI to Drive Innovative Teaching of Advanced Communications
New Approach Boosts Student Engagement and Skill Development
“In the course, AI and cutting-edge communication system experimental projects based on MATLAB and Deep Learning Toolbox are introduced to enhance the course’s advancement and challenge level within the context of new engineering disciplines.”
Key Outcomes
- MATLAB provides detailed AI shipping demos, reducing the time required to prepare course materials
- Comprehensive help documentation and annotations facilitate learning for students while also enhancing their research capabilities
- Stable support for MATLAB makes both software and hardware easily accessible to students
Integrating AI and software-defined radio devices into wireless communication courses is a popular research topic in university engineering departments. At Southern University of Science and Technology (SUSTech), Dr. Guang Wu’s Advanced Communication System Design is a core course for communication engineering and information engineering majors. The course’s experimental projects aim to develop students’ ability to solve complex engineering problems in wireless communication applications.
The Advanced Communication System Design lab course is centered around cutting-edge communication systems, such as Wi-Fi® systems, LTE/5G systems, and integrated communication and sensing systems, and includes a series of practical projects based on MATLAB®. In this course, Dr. Wu introduced AI advanced communication system experimental projects—based on Deep Learning Toolbox™—which integrate research results into experimental teaching and employ experimental scenarios using application cases provided by MATLAB. During the experiments, students use USRP for deep learning–based modulation recognition and localization. Dr. Wu organizes the data collected by USRP into standard data sets, which are then made available along with course materials and videos for other universities without experimental equipment. This project won the second prize in the 2023 National College Electrical and Electronic Experimental Teaching Case Design Competition in the South China region.
Dr. Wu chose MATLAB because of its rich examples, detailed documentation, and annotations. This not only facilitated continuous improvement and optimization of course content by teachers, but also helped students self-learn, understand cutting-edge technological achievements in the field of wireless communication, and publish academic papers. Additionally, the current version of MATLAB offers more stable hardware support than previous versions, making software and hardware development easier.
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