AI for Wireless
Implement AI workflows for wireless communications systems. Use Deep Learning Toolbox™, Statistics and Machine Learning Toolbox™, and Reinforcement Learning Toolbox™ to incorporate AI in wireless applications.
Related Information
Categories
- Functionality for AI
Functionality that supports deep learning workflow for wireless applications
- Applications
Incorporate AI techniques into wireless applications
- Using MATLAB with Python
AI for wireless when using MATLAB® with Python®
Featured Examples
AI for Positioning Accuracy Enhancement
Use AI to estimate the position of user equipment and compare performance with traditional TDoA techniques.
Structurally Compress Neural Network DPD Using Projection
Structurally compress a neural network DPD to reduce computational complexity and memory requirements using projection and principal component analysis.
Power Amplifier Modeling Using Neural Networks
Model a power amplifier (PA) using several different neural network (NN) architectures.
CSI Feedback with Autoencoders
Compress downlink channel state information (CSI) for 5G systems by using an autoencoder neural network.
