Using neural network for reduction distrotion introduced by power amplifier in digital communication systems

We proposed and improved an adaptive neural predistorter, which can automatically compensate for amplifier nonlinearity and thus makes it possible to transmit OFDM signals without incurring intolerable distortions. The neural predistorter utilizes gradient algorithms for its adaptation. Our results indicate clear improvements in performance for neural networks networks incorporating memory into their structure