4 papers
End-to-End Fast Training of Communication Links Without a Channel Model via Online Meta-Learning
Sangwoo Park, Osvaldo Simeone, Joonhyuk Kang
When a channel model is not available, the end-to-end training of encoder and decoder on a fading noisy channel generally requires the repeated use of the channel and of a feedback…
From Learning to Meta-Learning: Reduced Training Overhead and Complexity for Communication Systems
Osvaldo Simeone, Sangwoo Park, Joonhyuk Kang
Machine learning methods adapt the parameters of a model, constrained to lie in a given model class, by using a fixed learning procedure based on data or active observations. Adapt…
Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels
Sangwoo Park, Osvaldo Simeone, Joonhyuk Kang
When a channel model is available, learning how to communicate on fading noisy channels can be formulated as the (unsupervised) training of an autoencoder consisting of the cascade…
Learning How to Demodulate from Few Pilots via Meta-Learning
Sangwoo Park, Hyeryung Jang, Osvaldo Simeone +1
Consider an Internet-of-Things (IoT) scenario in which devices transmit sporadically using short packets with few pilot symbols. Each device transmits over a fading channel and is…