Equalization of the Non-Linear Satellite Communication Channel with an Echo State Network

Because of the small energy available aboard a satellite, the power amplifier must achieve a very high power efficiency which suggest to work close to the saturation point. This would be power efficient, but unfortunately would add non-linear distortions to the communication channel. Several equalization algorithms have been proposed to compensate for this non-linear behaviour. The Echo State Network (ESN), an algorithm coming from the field of artificial neural networks, has also been proposed for this task but has never been compared to state-of-the-art equalizers for non-linear channel. The aim of this paper is to adapt the ESN to the satellite communication channel and to compare it to the baseband Volterra equalizer. We show that the ESN is able to reach the same performances as the Volterra equalizer, evaluated in terms of bit error rate, and has similar complexity. In addition, we propose a new training strategy for the ESN and the Volterra equalizer to improve their performance.