A comparative analysis of behavioral models for RF power amplifiers

A comparative study of nonlinear behavioral models with memory for radio-frequency power amplifier (PAs) is presented. The models are static polynomial, parallel Hammerstein (PH), Volterra, and radial basis-function neural network (RBFNN). Two PAs were investigated: one was designed for the third-generation (3G) mobile telecommunication systems and one was designed for the second-generation (2G). The RBFNN reduced the total model error slightly more than the PH, but the error out of band was significantly lower for the PH. The Volterra was found to give a lower model error than did a PH of the same nonlinear order and memory depth. The PH could give a lower model error than the best Volterra, since the former could be identified with a higher nonlinear order and memory depth. The qualitative conclusions are the same for the 2G and 3G PAs, but the model errors are smaller for the latter. For the 3G PA, a static polynomial gave a low model error as low as the best PH and lower than the RBFNN for the hardest cross validation. The models with memory, PH, and RBFNN, showed better cross-validation performance, in terms of lower model errors, than a static polynomial for the hardest cross validation of the 2G PA

[1]  H. B. Poza,et al.  A wideband data link computer simulation model , 1978 .

[2]  M. Schetzen.  The Volterra and Wiener Theories of Nonlinear Systems , 1980 .

[3]  Adel A. M. Saleh,et al.  Frequency-Independent and Frequency-Dependent Nonlinear Models of TWT Amplifiers , 1981, IEEE Trans. Commun..

[4]  R. de Figueiredo.  The Volterra and Wiener theories of nonlinear systems , 1982, Proceedings of the IEEE.

[5]  X. T. Vuong,et al.  Modelling of nonlinear elements exhibiting frequency-dependent AM/AM and AM/PM transfer characteristics , 1984, Canadian Electrical Engineering Journal.

[6]  Muhammad Taher Abuelma'atti,et al.  Frequency-Dependent Nonlinear Quadrature Model for TWT Amplifiers , 1984, IEEE Trans. Commun..

[7]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[8]  W. Bosch,et al.  Measurement and simulation of memory effects in predistortion linearizers , 1989 .

[9]  Julius S. Bendat,et al.  Nonlinear System Techniques And Applications , 1990 .

[10]  D. Signorini,et al.  Neural networks , 1995, The Lancet.

[11]  C. J. Clark,et al.  Time-domain envelope measurement technique with application to wideband power amplifier modeling , 1998 .

[12]  Jacques Sombrin,et al.  Neural network modeling and identification of nonlinear channels with memory: algorithms, applications, and analytic models , 1998, IEEE Trans. Signal Process..

[13]  Truong Q. Nguyen,et al.  Design of hybrid filter banks for analog/digital conversion , 1998, IEEE Trans. Signal Process..

[14]  C.P. Silva,et al.  Validation of power amplifier nonlinear block models , 1999, 1999 IEEE MTT-S International Microwave Symposium Digest (Cat. No.99CH36282).

[15]  Mohamed Ibnkahla,et al.  Applications of neural networks to digital communications - a survey , 2000, Signal Process..

[16]  Fang Wang,et al.  A new macromodeling approach for nonlinear microwave circuits based on recurrent neural networks , 2000, IMS 2000.

[17]  A. A. Moulthrop,et al.  Optimal-filter approach for nonlinear power amplifier modeling and equalization , 2000, 2000 IEEE MTT-S International Microwave Symposium Digest (Cat. No.00CH37017).

[18]  David Wisell,et al.  Nonlinear Characterization of Multiple Carrier Power Amplifiers , 2000, 56th ARFTG Conference Digest.

[19]  Peter B. Kenington,et al.  High-Linearity RF Amplifier Design , 2000 .

[20]  Jungsang Kim,et al.  Digital predistortion of wideband signals based on power amplifier model with memory , 2001 .

[21]  C.P. Silva,et al.  Application of polyspectral techniques to nonlinear modeling and compensation , 2001, 2001 IEEE MTT-S International Microwave Sympsoium Digest (Cat. No.01CH37157).

[22]  Ignacio Santamaría,et al.  Nonlinearity estimation in power amplifiers based on subsampled temporal data , 2001, IEEE Trans. Instrum. Meas..

[23]  M.C.E. Yagoub,et al.  Neural based dynamic modeling of nonlinear microwave circuits , 2002, 2002 IEEE MTT-S International Microwave Symposium Digest (Cat. No.02CH37278).

[24]  T. Rahkonen,et al.  Extraction of a nonlinear AC FET model using small-signal S-parameters , 2002 .

[25]  Steve C. Cripps,et al.  Advanced Techniques in RF Power Amplifier Design , 2002 .

[26]  Y. Rolain,et al.  Broadband measurement and identification of a Wiener-Hammerstein model for an RF amplifier , 2002, 60th ARFTG Conference Digest, Fall 2002..

[27]  Jose C. Pedro,et al.  A comprehensive explanation of distortion sideband asymmetries , 2002 .

[28]  A. A. Moulthrop,et al.  Power-amplifier characterization using a two-tone measurement technique , 2002 .

[29]  J. S. Kenney,et al.  Quantifying memory effects in RF power amplifiers , 2002 .

[30]  David Wisell,et al.  A baseband time domain measurement system for dynamic characterization of power amplifiers with high dynamic range over large bandwidths , 2003, Proceedings of the 20th IEEE Instrumentation Technology Conference (Cat. No.03CH37412).

[31]  Ignacio Santamaría,et al.  Modeling Nonlinear Power Amplifiers in OFDM Systems from Subsampled Data: A Comparative Study Using Real Measurements , 2003, EURASIP J. Adv. Signal Process..

[32]  Timo Rahkonen,et al.  Distortion in RF power amplifiers , 2003 .

[33]  J. S. Kenney,et al.  Behavioral modeling of nonlinear RF power amplifiers considering memory effects , 2003 .

[34]  D. Rönnow,et al.  Measurement; analysis; modelling; and digital predistortion of RF/microwave power amplifiers , 2003 .

[35]  Mingyu Li,et al.  Radial basis function neural network models for power-amplifier design , 2004, 2004 International Conference on Communications, Circuits and Systems (IEEE Cat. No.04EX914).

[36]  D.E. Root,et al.  A behavioral modeling approach to nonlinear model-order reduction for RF/microwave ICs and systems , 2004, IEEE Transactions on Microwave Theory and Techniques.

[37]  T.J. Brazil,et al.  Behavioral modeling of RF power amplifiers based on pruned volterra series , 2004, IEEE Microwave and Wireless Components Letters.

[38]  L. Franca-Neto,et al.  RF System and Circuit Challenges for WiMAX , 2004 .

[39]  D. Wisell,et al.  Extension of the hammerstein model for power amplifier applications , 2004, ARFTG 63rd Conference, Spring 2004.

[40]  F.M. Ghannouchi,et al.  Dynamic behavioral modeling of 3G power amplifiers using real-valued time-delay neural networks , 2004, IEEE Transactions on Microwave Theory and Techniques.

[41]  J.C. Pedro,et al.  A comparative overview of microwave and wireless power-amplifier behavioral modeling approaches , 2005, IEEE Transactions on Microwave Theory and Techniques.

[42]  D. Wisell,et al.  Wide-band dynamic modeling of power amplifiers using radial-basis function neural networks , 2005, IEEE Transactions on Microwave Theory and Techniques.

[43]  D. Wisell,et al.  Nonlinear behavioral modeling of power amplifiers using radial-basis function neural networks , 2005, IEEE MTT-S International Microwave Symposium Digest, 2005..