Meta-learning to communicate: Fast end-to-end training for fading channels

Authors: Sangwoo Park, Osvaldo Simeone, Joonhyuk Kang

Conference: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2020

Abstract: We propose coherent AI-based end-to-end communication system via meta-learning under available channel model. With few trainings on new channel, proposed meta-learning based autoencoder finds coherent solution with reduced training complexity.

Fig. 2: Block error rate over iteration number for training on the new channel (4bits, 4complex channel uses, Rayleigh block fading channel model with 3taps, 16messages per iteration).