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use machine learning, deep learning, and reinforcement learning in wireless communications systems

you can use deep learning toolbox™ features in wireless communications systems to help train reception algorithms.

functions

dlarray support

	modulate using ofdm method
	demodulate using ofdm method

datastores and data import

datastore for collection of signals

related information

featured examples

ofdm autoencoder for wireless communications

model an end-to-end orthogonal frequency division modulation (ofdm) communications system with an autoencoder to reliably transmit information bits over a wireless channel.

modulation classification with deep learning

use a convolutional neural network (cnn) for modulation classification. you generate synthetic, channel-impaired waveforms. using the generated waveforms as training data, you train a cnn for modulation classification. you then test the cnn with software-defined radio (sdr) hardware and over-the-air signals.

deep learning data synthesis for 5g channel estimation

generate deep learning training data for channel estimation using 5g toolbox™.