Receiver Algorithms
AI-native receivers, channel estimation, and other receiver components
These examples demonstrate AI techniques you can use for various receiver algorithms.
Featured Examples
Verify Performance of 6G AI-Native Receiver Using MATLAB and PyTorch Coexecution
Integrate a trained PyTorch® network with MATLAB®-based data generation to simulate an AI-native air interface.
AI-Native Fully Convolutional Receiver
Use a convolutional neural network to replace conventional channel estimation, equalization, and symbol demodulation.
Training and Testing a Neural Network for LLR Estimation
Generate signals and channel impairments to train a neural network, called LLRNet, to estimate exact log likelihood ratios (LLR).
Deep Learning Data Synthesis for 5G Channel Estimation
Generate deep learning training data for channel estimation using 5G Toolbox™.
