Wide-band dynamic modeling of power amplifiers using radial-basis function neural networks

@article{Isaksson2005WidebandDM,
  title={Wide-band dynamic modeling of power amplifiers using radial-basis function neural networks},
  author={Magnus Isaksson and D. Wisell and Daniel Ronnow},
  journal={IEEE Transactions on Microwave Theory and Techniques},
  year={2005},
  volume={53},
  pages={3422-3428}
}
A radial-basis function neural network (RBFNN) has been used for modeling the dynamic nonlinear behavior of an RF power amplifier for third generation. In the model, the signal's envelope is used. The model requires less training than a model using IQ data. Sampled input and output signals were used for identification and validation. Noise-like signals with bandwidths of 4 and 20 MHz were used. The RBFNN is compared to a parallel Hammerstein (PH) model. The two model types have similar… CONTINUE READING
Highly Cited
This paper has 74 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 54 extracted citations

Study and simulation of RF power amplifier behavioral model based on RBF Neural Network

2010 International Conference on Microwave and Millimeter Wave Technology • 2010
View 13 Excerpts
Highly Influenced

The Dynamic Behavioral Model of RF Power Amplifiers With the Modified ANFIS

IEEE Transactions on Microwave Theory and Techniques • 2009
View 9 Excerpts
Highly Influenced

Modeling the nonlinear power amplifier with memory using complex-valued radial basis function networks

2008 International Conference on Microwave and Millimeter Wave Technology • 2008
View 3 Excerpts
Highly Influenced

Advanced Extrapolation Technique for Neural-Based Microwave Modeling and Design

IEEE Transactions on Microwave Theory and Techniques • 2018
View 1 Excerpt

75 Citations

0510'08'11'14'17
Citations per Year
Semantic Scholar estimates that this publication has 75 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 24 references

Dynamic behavioral modeling of 3G power amplifiers using real-valued time-delay neural networks

IEEE Transactions on Microwave Theory and Techniques • 2004
View 5 Excerpts
Highly Influenced

Measurement, analysis, modeling, and digital predistortion of RF/microwave power amplifiers

D. Rönnow
presented at the Gigahertz 2003, Linköping, Sweden, 2003. • 2003
View 8 Excerpts
Highly Influenced

Neural Networks for RF and Microwave Design

Q.-J. Zang, K. C. Gupta
2000
View 9 Excerpts
Highly Influenced

Neural-network-based adaptive baseband predistortion method for RF power amplifiers

IEEE Transactions on Circuits and Systems II: Express Briefs • 2004
View 14 Excerpts
Highly Influenced

Behavioral modeling of nonlinear RF power amplifiers considering memory effects

H. Ku, J. S. Kenney
IEEE Trans. Microw. Theory Tech., vol. 51, no. 12, pp. 2495–2504, Dec. 2003. • 2003
View 6 Excerpts
Highly Influenced

Neural Networks, 2nd ed

S. Haykin
Upper Saddle River, NJ: Prentice-Hall, • 1999
View 3 Excerpts
Highly Influenced

Reduced-complexity decision-feedback equalizer for nonlinear channels

9th European Signal Processing Conference (EUSIPCO 1998) • 1998
View 14 Excerpts
Highly Influenced

A Baseband Time Domain Measurement System for Dynamic Characterization of Power Amplifiers with High Dynamic Range Over Large Bandwidth

D. Wisell
Uppsala, Sweden: Uppsala Univ., • 2004
View 4 Excerpts

Similar Papers

Loading similar papers…