Vol. 93

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues
2019-05-31

New Behavior Model and Adaptive Predistortion for Power Amplifiers

By Mingming Gao, Yue Wu, Shao-Jun Fang, Jingchang Nan, and Shuyang Cui
Progress In Electromagnetics Research C, Vol. 93, 39-48, 2019
doi:10.2528/PIERC18112802

Abstract

A three-box model, composed of a triangular memory polynomial, a look-up table, and a cross item among memory times, is proposed for power amplifiers. The model acquired good accuracy and linear effect and reduced the calculation coefficient. Moreover, the paper proposes the GRLS_IVSSLMS adaptive predistortion algorithm. This algorithm is based on the structure of indirect learning. This work uses 16QAM signal to drive a strongly nonlinear Doherty amplifier. Experimental results show that the proposed method is suitable for the adaptive predistortion of power amplifiers.

Citation


Mingming Gao, Yue Wu, Shao-Jun Fang, Jingchang Nan, and Shuyang Cui, "New Behavior Model and Adaptive Predistortion for Power Amplifiers," Progress In Electromagnetics Research C, Vol. 93, 39-48, 2019.
doi:10.2528/PIERC18112802
http://jpier.org/PIERC/pier.php?paper=18112802

References


    1. Zhang, L., "Three-dimensional power segmented tracking for adaptive digital pre-distortion," IEICE Electron. Express, Vol. 13, 1, 2016, doi: 10.1587/elex.13.20160711.

    2. Mkadem, F., et al., "Multi band complexity reduced generalized memory polynomial poweramplifier digital predistortion," IEEE Trans. Microw. Theory Techn., Vol. 64, 1763, 2016, doi: 10.1109/TMTT.2016.2561279.
    doi:10.1109/TMTT.2016.2561279

    3. Hammi, O., et al., "Multi-basis weighted memory polynomial for RF power amplifiers behavioral modeling," IEEE MTT-S International Conf., Vol. 1, 2016, doi: 10.1109/IEEE-IWS.2016.7585475.

    4. Ba, S. N., K. Waheed, and G. T. Zhou, "Efficient lookup table-based adaptive baseband predistortion architecture for memoryless nonlinearity," EURASIP Journal on Advances in Signal Processing, 379249, 2010, doi: 10.1155/2010/379249.
    doi:10.1155/2010/379249

    5. Chen, H. H., et al., "Joint polynomial and look-up-table predistortion power amplifier linearization," IEEE Trans. Circuit System, Vol. 53, 612, 2006, doi: 10.1109/TCSII.2006.877278.
    doi:10.1109/TCSII.2006.877278

    6. Yang, Z., et al., "PA linearization using multi-stage look-up-table predistorter with optimal linear weighted delay," IEEE International Conf. Signal Process., Vol. 47, 2012, doi: 10.1109/ICoSP.2012.6491529.

    7. Kim, J., et al., "Digital predistortion of wideband signals based on power amplifier model with memory," Electronics Letters, Vol. 37, 1417, 2001, doi: 10.1049/el:20010940.
    doi:10.1049/el:20010940

    8. Morgan, D. R., et al., "A generalized memory polynomial model for digital predistortion of RF power amplifiers," IEEE Transactions on Signal Processing, Vol. 54, 3852, 2006, doi: 10.1109/TSP.2006.879264.
    doi:10.1109/TSP.2006.879264

    9. Yao, S., et al., "A recursive least squares algorithm with reduced complexity for digital predistortion linearization," IEEE International Conf. Signal Process., 4736, 2013, doi: 10.1109/ICASSP.2013.6638559.

    10. Mandic, D. P., "A generalized normalized gradient descent algorithm," IEEE Signal Processing Letters, Vol. 11, 115, 2004, doi: 10.1109/LSP.2003.821649.
    doi:10.1109/LSP.2003.821649

    11. Liu, Y. J., et al., "A robust augmented complexity-reduced generalized memory polynomial for wideband RF power amplifiers," IEEE Trans. on Industrial Electronics, Vol. 61, 2389, 2014, doi: 10.1109/TIE.2013.2270217.
    doi:10.1109/TIE.2013.2270217

    12. Dawar, N., T. Sharma, R. Darraji, and F. M. Ghannouchi, "Linearisation of radio frequency power amplifiers exhibiting memory effects using direct learning-based adaptive digital predistoriton," IET Communications, Vol. 10, No. 8, 950-954, May 19, 2016, doi: 10.1049/iet-com.2015.1048.
    doi:10.1049/iet-com.2015.1048

    13. Carusone, A. C., "An equalizer adaptation algorithm to reduce jitter in binary receivers," IEEE Transactions on Circuits and Systems II: Express Briefs, Vol. 53, No. 9, 807-811, Sep. 2006, doi: 10.1109/TCSII.2006.881161.
    doi:10.1109/TCSII.2006.881161

    14. Akhtar, M. T., M. Abe, and M. Kawamata, "A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems," IEEE Transactions on Audio, Speech, and Language Processing, Vol. 14, No. 2, 720-726, Mar. 2006, doi: 10.1109/TSA.2005.855829.
    doi:10.1109/TSA.2005.855829

    15. Mitra, A., M. Chakraborty, and H. Sakai, "A block floating-point treatment to the LMS algorithm: Efficient realization and a roundoff error analysis," IEEE Transactions on Signal Processing, Vol. 53, No. 12, 4536-4544, Dec. 2005, doi: 10.1109/TSP.2005.859342.
    doi:10.1109/TSP.2005.859342