Wavelet Network for Nonlinearities Reduction in Multicarrier Systems

In this paper, we propose a wavelet neural network suitable for reducing nonlinear distortion introduced by a traveling wave tube amplifier (TWTA) over multicarrier systems. Parameters of the proposed network are identified using an hybrid training algorithm, which adapts the linear output parameters using the least square algorithm and the nonlinear parameters of the hidden nodes are trained using the gradient descent algorithm. Computer simulation results confirm that the proposed wavelet network achieves a bit error rate performance very close to the ideal case of linear amplification.

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