Title :
Neural network based power amplifier dynamic modeling for wireless communications
Author :
Doufana, Mohamed ; Park, Chan Wang
Author_Institution :
Univ. du Quebec a Rimouski, Quebec, QC
Abstract :
In this paper we present the Neural Network (NN) based dynamic power amplifier (PA) modeling with memory effect. We developed this model with system generator for DSP by Xilinx that could be implemented on DSP chip. The advantage of our system generator based model is to develop highly parallel systems with the most advanced FPGAs, providing system modeling and automatic code generation from Simulink and MATLAB. Our real time modeling method can be adapted for any kind of latest signal type such as cdma-2000 and W-CDMA without any modification of the model and can be adapted to any environmental change such as temperature variation in PA without modify the model. That means our real time model is self adaptable. By using this method we can do a modeling dynamically the non linearity of the PA including memory effects for realistic modulation signals inputs. In this paper, by using our modeling architecture we demonstrate to have an almost same dynamic AM-AM and AM-PM curves of PA.
Keywords :
code division multiple access; digital signal processing chips; field programmable gate arrays; mathematics computing; neural nets; power amplifiers; DSP chip; FPGA; MATLAB; Simulink; W-CDMA; automatic code generation; cdma-2000; neural network; power amplifier dynamic modeling; system generator; wireless communications; Digital signal processing chips; Field programmable gate arrays; MATLAB; Mathematical model; Multiaccess communication; Neural networks; Power amplifiers; Power system modeling; Temperature; Wireless communication; Neural networks; Power amplifier; memory effects;
Conference_Titel :
Microwave and Millimeter Wave Technology, 2008. ICMMT 2008. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-1879-4
Electronic_ISBN :
978-1-4244-1880-0
DOI :
10.1109/ICMMT.2008.4540326