Improving compensation of nonlinear distortions in OFDM system using recurrent neural network with conjugate gradient algorithm

The paper presents a neural network predistortion technique compensating for nonlinear distortions caused by an HPA (high power amplifier) cascaded with a filter in an OFDM (orthogonal frequency division multiplexing) system. It is confirmed by computer simulation that the proposed approach produces a faster convergence speed than the conventional backpropagation algorithm. The predistortion technique based on a neural network is very attractive from the implementation point of view, because of the low amount of RAM required and rapid convergence from a blind start.