Learning How to Demodulate from Few Pilots via Meta-Learning

Understand

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 characterized by an amplifier with a unique non-linear transfer function.
• The number of pilots is generally insufficient to obtain an accurate estimate of the end-to-end channel, which includes the effects of fading and of the amplifier's distortion.
• This paper proposes to tackle this problem using meta-learning.