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Dynamic Behavioral Modeling of Power Amplifiers Using ANFIS-Based Hammerstein

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5 Author(s)
Jianfeng Zhai ; Dept. of Radio Eng., Southeast Univ., Nanjing ; Jianyi Zhou ; Lei Zhang ; Jianing Zhao
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This letter presents a novel structure for the dynamic behavioral modeling of radio frequency power amplifiers (RF PAs) with ANFIS-based Hammerstein model for memory effects. The model is an adaptive neuro-fuzzy inference system (ANFIS) followed by a finite impulse response (FIR) filter. A hybrid learning algorithm is adopted to identify the parameters of the ANFIS. The parameters of the FIR filter are estimated by a straightforward least-squares method. The input and output signals of the PA excited with a three-carrier WCDMA signal were sampled for the model identification and validation in a test bench. Experimental results in the frequency and the time domains show that the proposed model was able to give an accurate approximation to characterize the wideband RF PAs.

Published in:

Microwave and Wireless Components Letters, IEEE  (Volume:18 ,  Issue: 10 )