CSI Feedback
These examples demonstrate AI techniques to process downlink channel state information (CSI).
Featured Examples
Prepare Data for CSI Processing
Generate channel estimates and prepare a data set to train an autoencoder for channel state information (CSI) feedback compression.
CSI Feedback with Transformer Autoencoder
Design and train a convolutional transformer deep neural network for channel state information feedback by using a downlink clustered delay line (CDL) channel model.
CSI Feedback with Autoencoders
Compress downlink channel state information (CSI) for 5G systems by using an autoencoder neural network.
CSI Feedback with Autoencoders Implemented on an FPGA
Demonstrates how to use an autoencoder neural network to compress downlink channel state information (CSI) over a clustered delay line (CDL) channel. CSI feedback is in the form of a raw channel estimate array. In this example, the autoencoder network is implemented on an FPGA using the Deep Learning HDL Toolbox™.
Optimize CSI Feedback Autoencoder Training Using MATLAB Parallel Server and Experiment Manager
Accelerate determination of the optimal training hyperparameters for a channel state information (CSI) autoencoder by using a Cloud Center cluster and Experiment Manager.
NR PDSCH Throughput Using Channel State Information Feedback
Measure the PDSCH throughput of a 5G NR adaptive link that adjusts the MCS, precoding matrix, and number of layers based on the CSI feedback.
