AI for Wireless Communication
Overview
In this presentation, we show how easy it is to apply artificial intelligence (AI) capabilities to solve wireless communications problems in MATLAB. You learn how to be more efficient by using ready-to-use algorithms and data generated with MATLAB and wireless communications products. We will overview AI-driven workflows including data generation, AI networks training, validation and testing and deployment on embedded devices, enterprise systems. Finally, we showcase how to leverage existing deep learning networks outside MATLAB.
Highlights
- Generate training data in the form of synthetic and over-the-air signals using the Wireless Waveform Generator app
- Design and train your AI models using interactive tools such as Deep Network Designer app
- Perform large-scale simulation to test and validate your trained networks using Experiment Manager app
- Deploy your validated models to enterprise or embedded systems
- Explore how easily to interoperate with 3rd party environments such as python models
About the Presenters
Houman Zarrinkoub:
Dr. Houman Zarrinkoub is a senior product manager at MathWorks responsible for wireless communications products. During his 20-year tenure at MathWorks, he has also served as a development manager and has been responsible for multiple signal processing and communications software tools. Prior to MathWorks, he was a research scientist working on mobile and voice coding technologies in the Wireless Group at Nortel Networks. He has been awarded multiple patents on topics related to computer simulations of signal processing applications. Houman is the author of the book Understanding LTE with MATLAB: From Mathematical Modeling to Simulation and Prototyping. He holds a B.Sc. degree in electrical engineering from McGill University and M.Sc. and Ph.D. degrees in telecommunications from the University of Quebec, in Canada.
Uvaraj Natarajan:
Uvaraj is a Senior Application Engineer in MathWorks, focusing on the 5G/ LTE/ WLAN/ Wireless and Satellite communications. Prior to MathWorks he has worked with Cisco Systems where he worked on Self-Optimizing Networks (SON) for the 5G/ LTE market and developed expertise on end-to-end LTE networks working closely with mobile operators across globe. He has industry expertise on LTE ENB protocol stack development, LTE PHY development. He has also worked at Centre for Communication Systems Research, UK on cognitive radios, relay systems, LTE-A, CoMP systems. Uvaraj holds a master's degree in Mobile and Satellite Communications from University of Surrey, UK and BE in Electronics and Communications from Anna University, India.
Recorded: 9 Sep 2022
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AI for Wireless Communications with MATLAB
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