Vol. 93
Latest Volume
All Volumes
PIERC 150 [2024] PIERC 149 [2024] PIERC 148 [2024] PIERC 147 [2024] PIERC 146 [2024] PIERC 145 [2024] PIERC 144 [2024] PIERC 143 [2024] PIERC 142 [2024] PIERC 141 [2024] PIERC 140 [2024] PIERC 139 [2024] PIERC 138 [2023] PIERC 137 [2023] PIERC 136 [2023] PIERC 135 [2023] PIERC 134 [2023] PIERC 133 [2023] PIERC 132 [2023] PIERC 131 [2023] PIERC 130 [2023] PIERC 129 [2023] PIERC 128 [2023] PIERC 127 [2022] PIERC 126 [2022] PIERC 125 [2022] PIERC 124 [2022] PIERC 123 [2022] PIERC 122 [2022] PIERC 121 [2022] PIERC 120 [2022] PIERC 119 [2022] PIERC 118 [2022] PIERC 117 [2021] PIERC 116 [2021] PIERC 115 [2021] PIERC 114 [2021] PIERC 113 [2021] PIERC 112 [2021] PIERC 111 [2021] PIERC 110 [2021] PIERC 109 [2021] PIERC 108 [2021] PIERC 107 [2021] PIERC 106 [2020] PIERC 105 [2020] PIERC 104 [2020] PIERC 103 [2020] PIERC 102 [2020] PIERC 101 [2020] PIERC 100 [2020] PIERC 99 [2020] PIERC 98 [2020] PIERC 97 [2019] PIERC 96 [2019] PIERC 95 [2019] PIERC 94 [2019] PIERC 93 [2019] PIERC 92 [2019] PIERC 91 [2019] PIERC 90 [2019] PIERC 89 [2019] PIERC 88 [2018] PIERC 87 [2018] PIERC 86 [2018] PIERC 85 [2018] PIERC 84 [2018] PIERC 83 [2018] PIERC 82 [2018] PIERC 81 [2018] PIERC 80 [2018] PIERC 79 [2017] PIERC 78 [2017] PIERC 77 [2017] PIERC 76 [2017] PIERC 75 [2017] PIERC 74 [2017] PIERC 73 [2017] PIERC 72 [2017] PIERC 71 [2017] PIERC 70 [2016] PIERC 69 [2016] PIERC 68 [2016] PIERC 67 [2016] PIERC 66 [2016] PIERC 65 [2016] PIERC 64 [2016] PIERC 63 [2016] PIERC 62 [2016] PIERC 61 [2016] PIERC 60 [2015] PIERC 59 [2015] PIERC 58 [2015] PIERC 57 [2015] PIERC 56 [2015] PIERC 55 [2014] PIERC 54 [2014] PIERC 53 [2014] PIERC 52 [2014] PIERC 51 [2014] PIERC 50 [2014] PIERC 49 [2014] PIERC 48 [2014] PIERC 47 [2014] PIERC 46 [2014] PIERC 45 [2013] PIERC 44 [2013] PIERC 43 [2013] PIERC 42 [2013] PIERC 41 [2013] PIERC 40 [2013] PIERC 39 [2013] PIERC 38 [2013] PIERC 37 [2013] PIERC 36 [2013] PIERC 35 [2013] PIERC 34 [2013] PIERC 33 [2012] PIERC 32 [2012] PIERC 31 [2012] PIERC 30 [2012] PIERC 29 [2012] PIERC 28 [2012] PIERC 27 [2012] PIERC 26 [2012] PIERC 25 [2012] PIERC 24 [2011] PIERC 23 [2011] PIERC 22 [2011] PIERC 21 [2011] PIERC 20 [2011] PIERC 19 [2011] PIERC 18 [2011] PIERC 17 [2010] PIERC 16 [2010] PIERC 15 [2010] PIERC 14 [2010] PIERC 13 [2010] PIERC 12 [2010] PIERC 11 [2009] PIERC 10 [2009] PIERC 9 [2009] PIERC 8 [2009] PIERC 7 [2009] PIERC 6 [2009] PIERC 5 [2008] PIERC 4 [2008] PIERC 3 [2008] PIERC 2 [2008] PIERC 1 [2008]
2019-05-31
New Behavior Model and Adaptive Predistortion for Power Amplifiers
By
Progress In Electromagnetics Research C, Vol. 93, 39-48, 2019
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
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