Artificial neural network approach for LNA design of GPS receiver

Abstract

Paper presents an ANN modeling of microwave LNA for the global positioning front end receiver, operating at 1.57542 GHz. To design LNA, multilayer perceptron architecture is used. The scattering parameters of LNA are calculated using Levenberg Marquardt Backpropagation Algorithm for the frequency range 100 MHz to 8 GHz. The inputs given to this architecture are drain to source current, drain to source voltage, temperature and frequency and the outputs are maximum available gain, noise figure and scattering parameters (magnitude as well as angle). ANN model is trained using Agilent MGA 72543 GaAs pHEMT Low Noise Amplifier datasheet and this model shows high regression. The smith and polar charts are plotted for frequency range 100 MHz to 8 GHz.

DOI: 10.3103/S1060992X16040111

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Cite this paper

@article{Singh2016ArtificialNN, title={Artificial neural network approach for LNA design of GPS receiver}, author={Shruti Singh and Pradeep Kumar Chopra}, journal={Optical Memory and Neural Networks}, year={2016}, volume={25}, pages={236-242} }