Advertisement

Reduced-Complexity Polynomials with Memory Applied to the Linearization of Power Amplifiers with Real-Time Discrete Gain Control

  • Luis Schuartz
  • Edson L. Santos
  • Bernardo Leite
  • André A. Mariano
  • Eduardo G. LimaEmail author
Article
  • 29 Downloads

Abstract

In reconfigurable power amplifiers (PAs), the efficiency can be improved by dynamically switching the discrete gain mode according to the input envelope amplitude. Nevertheless, discontinuities that occur between gain mode changes critically compromise the linearization capability of traditional digital baseband predistorters (DPDs) based on continuous polynomials with memory. To circumvent such drawback, this work introduces a model based on polynomials bounded at both sides and able to take into account commutation delays. Besides, two novel approaches are presented to the model order reduction without basis change. The effectiveness of the proposed approaches to linearize a 130 nm CMOS class AB PA commutating in real time among three gain modes is certified based on Cadence Virtuoso and Matlab simulations. The proposed memory polynomial-based model was able to accurately model both direct and inverse transfer characteristics of a three gain mode PA, showing normalized mean square error results of about − 41 dB. Besides, a 25.5 dB reduction in adjacent channel power ratio is provided by the inclusion of a 10 parameters DPD that adopts the proposed approaches, in comparison with unlinearized PA of same output mean power.

Keywords

Digital baseband predistorter Linearity Multimode PA Power amplifier efficiency Radio frequency Wireless transmitter 

Notes

Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 and by National Council for Scientific and Technological Development (CNPq).

References

  1. 1.
    A. Abdelhafiz, A. Kwan, O. Hammi, F.M. Ghannouchi, Digital predistortion of LTE-A power amplifiers using compressed-sampling-based unstructured pruning of Volterra series. IEEE Trans. Microw. Theory Tech. (2014).  https://doi.org/10.1109/TMTT.2014.2360845 Google Scholar
  2. 2.
    K.H. An, D.H. Lee, O. Lee, H. Kim, J. Han, J. Kim, C. Lee, H. Kim, J. Laskar, A 2.4 GHz fully integrated linear CMOS power amplifier with discrete power control. IEEE Microw. Wirel. Compon. Lett. (2009).  https://doi.org/10.1109/LMWC.2009.2022141 Google Scholar
  3. 3.
    A.R. Belabad, S.A. Motamedi, S. Sharifian, A novel generalized parallel two-box structure for behavior modeling and digital predistortion of RF power amplifiers at LTE applications. Circuits Syst. Signal Process. (2017).  https://doi.org/10.1007/s00034-017-0700-9 Google Scholar
  4. 4.
    N. Bhushan, J. Li, D. Malladi, R. Gilmore, D. Brenner, A. Damnjanovic, R.T. Sukhavasi, C. Patel, S. Geirhofer, Network densification: the dominant theme for wireless evolution into 5G. IEEE Commun. Mag. (2014).  https://doi.org/10.1109/MCOM.2014.6736747 Google Scholar
  5. 5.
    E.J. Bonfim, E.G. de Lima, A modified two dimensional Volterra-based series for the low-pass equivalent behavioral modeling of RF power amplifiers. Progress Electromagn. Res. M (2016).  https://doi.org/10.2528/PIERM15122806 Google Scholar
  6. 6.
    S. Chen, C.F.N. Cowan, P.M. Grant, Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans. Neural Netw. (1991).  https://doi.org/10.1109/72.80341 Google Scholar
  7. 7.
    S. Chen, X. Hong, C.J. Harris, Fully complex-valued radial basis function networks for orthogonal least squares regression, in 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence) (2008).  https://doi.org/10.1109/IJCNN.2008.4633759
  8. 8.
    S. Cripps, RF Power Amplifiers for Wireless Communications, 2nd edn. (Artech House, Norwood, MA, 2006)Google Scholar
  9. 9.
    C. Eun, E.J. Powers, A new volterra predistorter based on the indirect learning architecture. IEEE Trans. Signal Process. (1997).  https://doi.org/10.1109/78.552219 Google Scholar
  10. 10.
    P.L. Gilabert, G. Montoro, D. López, N. Bartzoudis, E. Bertran, M. Payaró, A. Hourtane, Order reduction of wideband digital predistorters using principal component analysis, in 2013 IEEE MTT-S International Microwave Symposium Digest (MTT) (2013).  https://doi.org/10.1109/MWSYM.2013.6697687
  11. 11.
    R. Giofré, L. Piazzon, P. Colantonio, F. Giannini, A Doherty architecture with high feasibility and defined bandwidth behavior. IEEE Trans. Microw. Theory Tech. (2013).  https://doi.org/10.1109/TMTT.2013.2274432 Google Scholar
  12. 12.
    M.R. Hasin, J. Kitchen, A compact watt-level GaN-on-Si class AB power amplifier for handset applications, in 2017 Texas Symposium on Wireless and Microwave Circuits and Systems (WMCS) (2017).  https://doi.org/10.1109/WMCaS.2017.8070682
  13. 13.
    D. Kang, B. Park, D. Kim, J. Kim, Y. Cho, B. Kim, Envelope-tracking CMOS power amplifier module for LTE applications. IEEE Trans. Microw. Theory Techn. (2013).  https://doi.org/10.1109/TMTT.2013.2280186 Google Scholar
  14. 14.
    P.B. Kenington, High Linearity RF Amplifier Design (Artech House, Norwood, MA, 2000)Google Scholar
  15. 15.
    J. Kim, K. Konstantinou, Digital predistortion of wideband signals based on power amplifier model with memory. Electron. Lett. (2001).  https://doi.org/10.1049/el:20010940 Google Scholar
  16. 16.
    B.M. Lee, R.J.P. de Figueiredo, Adaptive predistorters for linearization of high-power amplifiers in OFDM wireless communications. Circuits Syst. Signal Process. (2006).  https://doi.org/10.1007/s00034-004-0901-x zbMATHGoogle Scholar
  17. 17.
    E.G. Lima, T.R. Cunha, J.C. Pedro, A physically meaningful neural network behavioral model for wireless transmitters exhibiting PM-AM/PM-PM distortions. IEEE Trans. Microw. Theory Techn. (2011).  https://doi.org/10.1109/TMTT.2011.2171709 Google Scholar
  18. 18.
    W.A. Malik, A.F.A. Sheta, I. Elshafiey, A broadband high efficiency class AB GaN HEMT balanced power amplifier, in 2017 8th International Conference on Information Technology (ICIT) (2017).  https://doi.org/10.1109/ICITECH.2017.8079979
  19. 19.
    V. Mathews, G. Sicuranza, Polynomial Signal Processing (Wiley, New York, 2000)Google Scholar
  20. 20.
    J.C. Mayeda, D.Y.C., Lie, J. Lopez, A highly efficient and linear 15 GHz GaN power amplifier design for 5G communications, in 2017 Texas Symposium on Wireless and Microwave Circuits and Systems (WMCS) (2017).  https://doi.org/10.1109/WMCaS.2017.8070699
  21. 21.
    R. Meshkin, A. Saberkari, M. Niaboli-Guilani, A novel 2.4 GHz CMOS class-E power amplifier with efficient power control for wireless communications, in 17th IEEE Int. Conf. Electron. Circuits Syst (2010).  https://doi.org/10.1109/ICECS.2010.5724583
  22. 22.
    L.A.A. Montes, K. Raja, F.U.H.G. Wong, M. Je, An efficient power control scheme for a 2.4 GHz class-E PA in 0.13-\(\mu \)m CMOS, in IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing Singapore (2014).  https://doi.org/10.1109/ISSNIP.2014.6827687
  23. 23.
    D.R. Morgan, Z. Ma, J. Kim, M.G. Zierdt, J. Pastalan, A generalized memory polynomial model for digital predistortion of RF power amplifiers. IEEE Trans. Signal Process. (2006).  https://doi.org/10.1109/TSP.2006.879264 zbMATHGoogle Scholar
  24. 24.
    M.S. Muha, C.J. Clark, A.A. Moulthrop, C.P. Silva, Validation of power amplifier nonlinear block models, in 1999 IEEE MTT-S International Microwave Symposium Digest (Cat. No.99CH36282) (1999).  https://doi.org/10.1109/MWSYM.1999.779870
  25. 25.
    W. Pan, Y. Liu, S. Shao, Y. Tang, A method to reduce sampling rate of the ADC in feedback channel for wideband digital predistortion. Circuits Syst. Signal Process. (2014).  https://doi.org/10.1007/s00034-014-9751-3 Google Scholar
  26. 26.
    J.C. Pedro, S.A. Maas, A comparative overview of microwave and wireless power-amplifier behavioral modeling approaches. IEEE Trans. Microw. Theory Techn. (2005).  https://doi.org/10.1109/TMTT.2005.845723 Google Scholar
  27. 27.
    F.H. Raab, P. Asbeck, S. Cripps, P.B. Kenington, Z.B. Popovic, N. Pothecary, J.F. Sevic, N.O. Sokal, Power amplifiers and transmitters for RF and microwave. IEEE Trans. Microw. Theory Techn. (2002).  https://doi.org/10.1109/22.989965 Google Scholar
  28. 28.
    D. Raychaudhuri, N.B. Mandayam, Frontiers of wireless and mobile communications. Proc. IEEE (2012).  https://doi.org/10.1109/JPROC.2011.2182095 Google Scholar
  29. 29.
    H.D. Rodrigues, T.C. Pimenta, R.A.A. de Souza, L.L. Mendes, Orthogonal scalar feedback digital pre-distortion linearization. IEEE Trans. Broadcast. (2017).  https://doi.org/10.1109/TBC.2017.2755261 Google Scholar
  30. 30.
    E.L. Santos, B. Leite, A. Mariano, Multimode 2.4 GHz CMOS power amplifier with gain control for efficiency enhancement at power backoff, in 2015 IEEE 6th Latin American Symposium on Circuits Systems (LASCAS) (2015).  https://doi.org/10.1109/LASCAS.2015.7250427
  31. 31.
    E.L. Santos, M.A. Rios, L. Schuartz, B. Leite, L. Lolis, E.G. Lima, A.A. Mariano, A fully integrated CMOS power amplifier with discrete gain control for efficiency enhancement. Microelectron. J. (2017).  https://doi.org/10.1016/j.mejo.2017.09.009 Google Scholar
  32. 32.
    F. Santos, A. Mariano, B. Leite, 2.4 GHz CMOS digitally programmable power amplifier for power back-off operation, in 2016 IEEE 7th Latin American Symposium on Circuits Systems (LASCAS) (2016).  https://doi.org/10.1109/LASCAS.2016.7451034
  33. 33.
    M. Schetzen, Nonlinear system modeling based on the Wiener theory. Proc. IEEE (1981).  https://doi.org/10.1109/PROC.1981.12201 Google Scholar
  34. 34.
    A.S. Tehrani, H. Cao, S. Afsardoost, T. Eriksson, M. Isaksson, C. Fager, A comparative analysis of the complexity/accuracy tradeoff in power amplifier behavioral models. IEEE Trans. Microw. Theory Techn. (2010).  https://doi.org/10.1109/TMTT.2010.2047920 Google Scholar
  35. 35.
    A. Tufféry, N. Deltimple, E. Kerhervé, V. Knopik, P. Cathelin, CMOS fully integrated reconfigurable power amplifier with efficiency enhancement for LTE applications. Electron. Lett. (2015).  https://doi.org/10.1049/el.2014.3525 Google Scholar
  36. 36.
    P. Varahram, J. Dooley, K. Finnerty, R. Farrell, A digital pre-distortion based on nonlinear autoregressive with exogenous inputs. IEEE Microw. Wirel. Compon. Lett. (2016).  https://doi.org/10.1109/LMWC.2016.2549178 Google Scholar
  37. 37.
    J. Wood, Digital pre-distortion of RF power amplifiers: progress to date and future challenges, in 2015 IEEE MTT-S International Microwave Symposium (2015).  https://doi.org/10.1109/MWSYM.2015.7166711
  38. 38.
    X. Yu, H. Jiang, Digital predistortion using adaptive basis functions. IEEE Trans. Circuits Syst. I Regul. Pap. (2013).  https://doi.org/10.1109/TCSI.2013.2265958 Google Scholar
  39. 39.
    R. Zhang, M. Acar, M.P. van der Heijden, M. Apostolidou, D.M.W. Leenaerts, Generalized semi-analytical design methodology of class-E outphasing power amplifier. IEEE Trans. Circuits Syst. I Regul. Pap. (2014).  https://doi.org/10.1109/TCSI.2014.2327278 Google Scholar
  40. 40.
    A. Zhu, P.J. Draxler, C. Hsia, T.J. Brazil, D.F. Kimball, P.M. Asbeck, Digital predistortion for envelope-tracking power amplifiers using decomposed piecewise Volterra series. IEEE Trans. Microw. Theory. Techn. (2008).  https://doi.org/10.1109/TMTT.2008.2003529 Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Group of Integrated Circuits and SystemsFederal University of Paraná (UFPR)CuritibaBrazil

Personalised recommendations