Developing AI models for wireless applications can be challenging, particularly when it comes to collecting data. How can we obtain real-world data with channel-impaired waveforms without interference from other signals ?.
To address this, we will generate synthetic waveforms with included impairments and then broadcast and receive them using SDRs. The captured signals will be used to train and evaluate a Convolutional Neural Network (CNN) AI model.w
Using the Wireless Waveform Generator to easily generate synthetic waveforms with various modulation schemes
Live demo to showcase ease of integrating SDRs (ADALM-PLUTO) into workflows
Developing Deep Learning AI models for modulation classification
[White Paper ] 5G NR Waveform Generation and Over-the-Air Testing
Mr.Jonathan Tee
Application Engineer
Jonathan Tee, an Application Engineer at TechSource Systems, holds a Master of Engineering degree in Electrical and Electronics from Nottingham Malaysia. With expertise in RF and microwave technology, he has designed Phased Arrays and tackled Signal and Power Integrity challenges.
Jonathan's passion extends to using MATLAB for Communication Systems and RF Propagation. In his spare time, he's a 3D modeling enthusiast and has even built his own 3D printer from scratch. His innovative approach and technical prowess make him a standout professional in the field.
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