Abstract:

Adaptive digital predistortion is the most promising technique to overcome the nonlinearity of High Power Amplifier (HPA). In order to improve the efficiency and effectiveness of the predistortion, the evolutionary computation techniques of the parallel computing platform are introduced, the method of training neural network in advance based on the PSO algorithm is proposed, and the basic process of the algorithm is given. Based on the above, a threelayer forward neural network predistorter with two inputs and two outputs is proposed for HPA with memory. The predistorter is realized using indirect learning architecture associated with the Backpropagation algorithm .This technique allows us to correct for general nonlinearities and memory effects simultaneously. Simulation results show that the new approach is more efficient than the conventional BP algorithm, without training in advance based on PSO.

Key words: power amplifier;memory nonlinear;predistortion;PSO;neural network;parallel computing