Abstract
How to estimate channel parameters more effectively, intelligently and accurately is the key problem to realize the requirements of intelligent and adaptive short-wave communication system. Based on the detailed analysis of chirp signal and fractional Fourier transform, an intelligent channel parameter estimation system is constructed. By building and training the regression model of multilayer fully connected neural network, the estimation error of Doppler shift is reduced. The simulation results show that the hierarchical channel estimation algorithm improves the precision of channel parameter estimation and the anti-noise performance of the system.
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