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Journal articles on the topic 'Digital predistortion'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 March 2023

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1

Zhang, Rui, and Zhi Bin Zeng. "Undersampling Digital Predistortion Compensation Technology Based on Broadband Signals." Applied Mechanics and Materials 543-547 (March 2014): 2381–84. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2381.

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Nonlinearity of power amplifier always results in spectrum spreading on input signal. When using digital predistortion technology to compensate power amplifier's nonlinearity, the required sampling frenquence for the output signal of amplifier is times of the original signal. The undersampling predistortion method can reduce the sampling frequency requirements. However, for the broadband signal, due to the significant memory effect of the power amplifier, the performance of undersampling digital predistortion is not satisfactory. In order to improve the undesirable predistortion performamce, this paper presents two kinds of undersampling digital predistortion compensation methods. For different sampling frequencies, the predistortion performances of these two kinds of compensation methods are different.

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2

Kim, W. J., K. J. Cho, S. P. Stapleton, and J. H. Kim. "Baseband derived RF digital predistortion." Electronics Letters 42, no. 8 (2006): 468. http://dx.doi.org/10.1049/el:20060606.

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3

Melczarsky, Ilan, Pere L. Gilabert, Valeria Di Giacomo, Eduard Bertran, and Fabio Filicori. "Behavioral modeling and linearization of a millimeter-wave power amplifier." International Journal of Microwave and Wireless Technologies 1, no. 2 (April 2009): 127–36. http://dx.doi.org/10.1017/s1759078709000075.

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The use of digital predistortion for linearizing a millimeter-wave power amplifier (PA) is investigated. A PA operating at 38 GHz is designed using an accurate non-quasi-static transistor model, taking into account both short- and long-term memory effects. A realistic test signal is then used for the identification of a nonlinear auto-regressive moving average (NARMA) behavioral model of the PA. The NARMA-based digital predistorter is then derived and formulated in terms of basic predistortion cells, especially suitable for efficient implementation in an FPGA. The performance of the predistortion solution is preliminarily assessed by means of computer simulations.

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4

Petushkov, S. V. "ADAPTIVE PREDISTORTION DEVICE OF THE SATELLITE TRANSMITTERS." H&ES Research 12, no. 6 (2020): 11–17. http://dx.doi.org/10.36724/2409-5419-2020-12-6-11-17.

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The improvement of energetic and spectral characteristics of the satellite transmitters which act in the harsh space environment with the help of the predistortion linearization becomes more and more actual task. The proposed adaptive predistortion device is based on the correlation evaluation of the nonlinear distortion level at the output of the power amplifier. The device allows to provide more effective linearization in the conditions with changing characteristics of the satellite transmitter within the lifetime of the satellite at the orbit in difference to the systems with advance tuning. The proposed technical solution has a higher reliability and simplified technical implementation in comparison with the analogs due to lack of the preliminary analog and digital processing of the RF signal. The simplified algorithm which requires lesser logical capacity in the digital microcircuits than conventional adaptive algorithms was developed for the modeling of the adaptive predistortion device. The proposed algorithm of changing the parameters of the predistortion linearizer requires less mathematical calculations within one iteration cycle, which is based on the determination of the cross-correlation function gradient rise direction. The obtained results of proposed predistortion linearizer modeling show that the process of two-dimension adaptation based on the developed algorithm is monosemantic and leads to the recovery of the linearizer’s non-linear characteristics optimal tune. The adaptation process leads to the lowering of the intermodulation distortion at the output of the power amplifier in a few adaptation cycles. It is worth noting that the process of the optimization and selection of the two parameters of the predistortion linearizer in the amplifier flows the same way whatever if the analog of digital implementation of the linearizer is used.

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5

Brihuega, Alberto, Lauri Anttila, and Mikko Valkama. "Frequency-Domain Digital Predistortion for OFDM." IEEE Microwave and Wireless Components Letters 31, no. 6 (June 2021): 816–18. http://dx.doi.org/10.1109/lmwc.2021.3062982.

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6

Jeong, Eui-Rim. "Digital Predistortion Technique for MIMO Transmitters." Journal of Korea Information and Communications Society 37C, no. 12 (December 28, 2012): 1289–95. http://dx.doi.org/10.7840/kics.2012.37c.12.1289.

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7

Yu, Xin, and Hong Jiang. "Digital Predistortion Using Adaptive Basis Functions." IEEE Transactions on Circuits and Systems I: Regular Papers 60, no. 12 (December 2013): 3317–27. http://dx.doi.org/10.1109/tcsi.2013.2265958.

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8

Wan-Jong Kim, S. P. Stapleton, Jong Heon Kim, and C. Edelman. "Digital predistortion linearizes wireless power amplifiers." IEEE Microwave Magazine 6, no. 3 (September 2005): 54–61. http://dx.doi.org/10.1109/mmw.2005.1511914.

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9

Gonzalez-Serrano, F. J., J. J. Murillo-Fuentes, and A. Artes-Rodriguez. "GCMAC-based predistortion for digital modulations." IEEE Transactions on Communications 49, no. 9 (2001): 1679–89. http://dx.doi.org/10.1109/26.950354.

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10

Abdelaziz, Mahmoud, Lauri Anttila, Alberto Brihuega, Fredrik Tufvesson, and Mikko Valkama. "Digital Predistortion for Hybrid MIMO Transmitters." IEEE Journal of Selected Topics in Signal Processing 12, no. 3 (June 2018): 445–54. http://dx.doi.org/10.1109/jstsp.2018.2824981.

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11

Sevcik, Bretislav. "Time-Domain Predistortion Method Based on Raised Cosine Signaling in Real Transmission Channels." Active and Passive Electronic Components 2012 (2012): 1–5. http://dx.doi.org/10.1155/2012/596481.

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The concept of time-domain predistortion method based on raised cosine signaling is applied in real transmission channels. The proposed PWM-RC method uses raised-cosine pulse shaping instead of conventional rectangular digital signals and pulse-width modulation (PWM) scheme to achieve better output channel data response in harsh channel environment. The conventional predistortion methods based on pulse amplitude adjusting are not compatible with modern low-power CMOS design. Currently existing time-domain predistortion methods which are only based on a PWM scheme show many highfrequency signal harmonic components for both fast and slow signal transitions. It can cause more system crosstalk susceptibility if the crosstalk is dominant factor in transmission channel. In this case, the additional preemphasis boosted undesirable high-frequency components. Finally, the real channel transfer functions in connection with ADS Agilent development studio are used to compare the performance of proposed method with other predistortion methods.

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12

Kong, Xiao Wei, Jin Zheng Li, Wei Xia, and Zi Shu He. "Kalman Filter Algorithm for Adaptive Digital Predistortion." Applied Mechanics and Materials 347-350 (August 2013): 2385–89. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2385.

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This paper introduces a recursive algorithm of Kalman filter for digital predistorter parameters extraction based on memory polynomials predistorter model. The predistorter model is firstly formulated as linear regression expression. Then we derive the state-space equation of the model and attain the steps of the algorithm. Finally, the accuracy and stability of the algorithm is proved by simulation.

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13

Qiao, Wen, Hongmin Li, Chengye Jiang, Guichen Yang, Lei Su, and Falin Liu. "Heuristic Model Structure Optimization for Digital Predistortion." IEEE Access 9 (2021): 158831–41. http://dx.doi.org/10.1109/access.2021.3131212.

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14

刘, 昕., 文华陈, 汇波吴, and 正和冯. "Digital predistortion: development trends and key techniques." SCIENTIA SINICA Informationis 52, no. 4 (April 1, 2022): 569. http://dx.doi.org/10.1360/ssi-2021-0421.

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15

Youngcheol Park and J. S. Kenney. "Adaptive digital predistortion linearization of frequency multipliers." IEEE Transactions on Microwave Theory and Techniques 51, no. 12 (December 2003): 2516–22. http://dx.doi.org/10.1109/tmtt.2003.819771.

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16

Lee, K. C., and P. Gardner. "Neuro-fuzzy approach to adaptive digital predistortion." Electronics Letters 40, no. 3 (2004): 185. http://dx.doi.org/10.1049/el:20040154.

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17

Afsardoost, Sepideh, Thomas Eriksson, and Christian Fager. "Digital Predistortion Using a Vector-Switched Model." IEEE Transactions on Microwave Theory and Techniques 60, no. 4 (April 2012): 1166–74. http://dx.doi.org/10.1109/tmtt.2012.2184295.

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18

Jiang, Hong, Xin Yu, and Paul A. Wilford. "Digital Predistortion Using Stochastic Conjugate Gradient Method." IEEE Transactions on Broadcasting 58, no. 1 (March 2012): 114–24. http://dx.doi.org/10.1109/tbc.2011.2174281.

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19

Wu, Xiaofang, Xinshuo Cai, Jinfu Huang, and Jianghong Shi. "Frequency selective digital predistortion for harmonic rejection." International Journal of Electronics 105, no. 10 (May 28, 2018): 1728–38. http://dx.doi.org/10.1080/00207217.2018.1477201.

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20

Tanio, Masaaki, Naoto Ishii, and Norifumi Kamiya. "Efficient Digital Predistortion Using Sparse Neural Network." IEEE Access 8 (2020): 117841–52. http://dx.doi.org/10.1109/access.2020.3005146.

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21

Tarver, Chance, Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama, and Joseph R. Cavallaro. "Low-complexity, Multi Sub-band Digital Predistortion." Journal of Signal Processing Systems 90, no. 10 (November 15, 2017): 1495–505. http://dx.doi.org/10.1007/s11265-017-1303-1.

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22

Sun, Liying, Peng Chu, and Rui Zhu. "Navigation Signal Radio Frequency Channel Modeling and Predistortion Technology Based on Artificial Intelligence Technology and Neural Network." Mobile Information Systems 2022 (August 18, 2022): 1–11. http://dx.doi.org/10.1155/2022/5745907.

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Digital predistortion technology is widely used in wireless communication. As a vital part of wireless communication system, the predistortion technology of radio frequency power amplifier has always been a hot and difficult topic. This paper will research and explore the key technologies of radio frequency channel construction and predistortion of navigation information through artificial intelligence technology and neural network. The article first conducts a simple research on a new generation of artificial intelligence systems--artificial intelligence is an engineering technology scientific research that develops theories, methods, skills, and application systems for modeling, scaling, and amplifying collective human knowledge. Then, the article combines neural network algorithms. BP network is not only a part of synthetic neural network but also a multiple layer fed-forward network. Finally, a neural network method is proposed to model and predistort the load channel model. Then, the RF channel distortion model can be constructed, and the RF channel modeling simulation experiment and the RF channel predistortion simulation experiment are carried out. The experimental results of this paper showed that compared with the situation without predistortion, the two indicators of the zero-crossing slope distortion and the zero-crossing offset of the discriminant function of the output signal of the channel with predistortion had been greatly improved. Overall, the neural network-based model outperformed the RVTDNN model by 30% on these two metrics. It also indicated that the neural network model could model and predistort the cascade model well, and the new model had better modeling accuracy and predistortion effect than the RVTDNN model.

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23

Pascual Campo, Pablo, Vesa Lampu, Alexandre Meirhaeghe, Jani Boutellier, Lauri Anttila, and Mikko Valkama. "Digital Predistortion for 5G Small Cell: GPU Implementation and RF Measurements." Journal of Signal Processing Systems 92, no. 5 (December 21, 2019): 475–86. http://dx.doi.org/10.1007/s11265-019-01502-4.

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AbstractIn this paper, we present a high data rate implementation of a digital predistortion (DPD) algorithm on a modern mobile multicore CPU containing an on-chip GPU. The proposed implementation is capable of running in real-time, thanks to the execution of the predistortion stage inside the GPU, and the execution of the learning stage on a separate CPU core. This configuration, combined with the low complexity DPD design, allows for more than 400 Msamples/s sample rates. This is sufficient for satisfying 5G new radio (NR) base station radio transmission specifications in the sub-6 GHz bands, where signal bandwidths up to 100 MHz are specified. The linearization performance is validated with RF measurements on two base station power amplifiers at 3.7 GHz, showing that the 5G NR downlink emission requirements are satisfied.

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24

Wang, Yong Fei, Dong Fang Zhou, Yi Zhang, Yu Sun, and Jing Yuan Xu. "Predistortion Technology Used for TWTA." Advanced Materials Research 756-759 (September 2013): 760–63. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.760.

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According to the predistortion technique of travelling wave tube amplifiers (TWTAs), by analyzing TWTA model proposed by Saleh, the gain transmission function curve and phase expansion function curve of the predistortion circuit are deduced. The linear range of TWTA could be enlarged by using predistortion technique, and invariable gain together with zero phase excursions are reached at the working region of the linearized TWTA. As a kind of microwave and millimeter wave amplifiers, TWTAs find a wide utilization in communication, radar and electronic countermeasure applications. To obtain high output power, TWTAs are usually working at their saturation region where severe nonlinear distortion appears. The nonlinearity manifests gain compression and phase excursion. For digital communications application, the nonlinear distortion increase bit error rate, and this limits system efficiency. For electronic countermeasure applications, the nonlinear distortion limits the output power obtainable at the carrier frequency, and this limits the obtainable efficiency of the system. So insights into measures to improve nonlinearity of TWTAs will benefit wireless communications systems and electronic countermeasure systems. Predistortion technique is one of the best choices [1,2,.

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25

Li, Huan, Cheng Sheng Pan, Yu Zhang, and Bo Ren. "On Adaptive Identification Algorithm for PA Linearization." Applied Mechanics and Materials 29-32 (August 2010): 1268–73. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.1268.

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According to the nonlinear amplification characteristic with memory effection of power amplifier(PA) in WCDMA systems, we have analyzed the structure of Wiener digital predistortion system in which Hammerstein power amplifier model with memory is adopted. LR algorithm and LMS algorithm were used respectively to identify and update parameters of Wiener predistortion system. An LR / LMS identification algorithm is proposed for syetem adaptive Identification. The method has a very good suppression of signal spectral regrowth. Theoretical analysis and computer simulation verified the effectiveness and practicability of the algorithm.

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26

Bu, Yun, Tian-Qian Li, and Yong-Qiang Chen. "A robust digital predistortion algorithm for power amplifiers." IEICE Electronics Express 11, no. 5 (2014): 20130759. http://dx.doi.org/10.1587/elex.10.20130759.

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27

Huang, Hai, Patrick Mitran, and Slim Boumaiza. "Digital Predistortion Function Synthesis using Undersampled Feedback Signal." IEEE Microwave and Wireless Components Letters 26, no. 10 (October 2016): 855–57. http://dx.doi.org/10.1109/lmwc.2016.2605500.

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28

Liu, Ying, Xin Quan, Shihai Shao, and Youxi Tang. "Digital predistortion architecture with reduced ADC dynamic range." Electronics Letters 52, no. 6 (March 2016): 435–37. http://dx.doi.org/10.1049/el.2015.4174.

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29

Dunn, Zachary, Mark Yeary, Caleb Fulton, and Nathan Goodman. "Wideband digital predistortion of solid-state radar amplifiers." IEEE Transactions on Aerospace and Electronic Systems 52, no. 5 (October 2016): 2452–66. http://dx.doi.org/10.1109/taes.2016.150142.

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30

Song, Bin, Songbai He, Jun Peng, and Yatao Zhao. "Dynamic deviation memory polynomial model for digital predistortion." Electronics Letters 53, no. 9 (April 2017): 606–7. http://dx.doi.org/10.1049/el.2017.0226.

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31

Jiang, Hong, and Paul A. Wilford. "Digital Predistortion for Power Amplifiers Using Separable Functions." IEEE Transactions on Signal Processing 58, no. 8 (August 2010): 4121–30. http://dx.doi.org/10.1109/tsp.2010.2049742.

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32

Fu, Zhu, Lauri Anttila, Mahmoud Abdelaziz, Mikko Valkama, and Alexander M. Wyglinski. "Frequency-Selective Digital Predistortion for Unwanted Emission Reduction." IEEE Transactions on Communications 63, no. 1 (January 2015): 254–67. http://dx.doi.org/10.1109/tcomm.2014.2364571.

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33

Brihuega, Alberto, Lauri Anttila, Mahmoud Abdelaziz, Thomas Eriksson, Fredrik Tufvesson, and Mikko Valkama. "Digital Predistortion for Multiuser Hybrid MIMO at mmWaves." IEEE Transactions on Signal Processing 68 (2020): 3603–18. http://dx.doi.org/10.1109/tsp.2020.2995972.

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34

Shokair, Ahmad, Ali Beydoun, Dang-Kièn Germain Pham, Chadi Jabbour, and Patricia Desgreys. "Wide band digital predistortion using iterative feedback decomposition." Analog Integrated Circuits and Signal Processing 100, no. 1 (October 19, 2018): 93–108. http://dx.doi.org/10.1007/s10470-018-1347-6.

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35

Wang, Jian, and Zhi Bin Zeng. "A High-Performance Hardware Design for Digital Predistortion System." Applied Mechanics and Materials 380-384 (August 2013): 3346–49. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3346.

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Digital predistortion (DPD) is a method widely used to compensate the nonlinearity of power amplifier to improve the transmitting signals. The DPD performance, however, depend heavily on the hardware design on signal integrity, EMI and low additional distortion of downconversion circuit. In this paper, a new high-performance hardware solution for DPD is introduced. Engineering tests show that this hardware design characterizes by high reliability and excellent performance to satisfy the requirements of DPD.

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36

Pospíšil, Martin, Roman Maršálek, Tomáš Götthans, and Tomáš Urbanec. "Digitally-Compensated Wideband 60 GHz Test-Bed for Power Amplifier Predistortion Experiments." Sensors 21, no. 4 (February 20, 2021): 1473. http://dx.doi.org/10.3390/s21041473.

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Millimeter waves will play an important role in communication systems in the near future. On the one hand, the bandwidths available at millimeter-wave frequencies allow for elevated data rates, but on the other hand, the wide bandwidth accentuates the effects of wireless front-end impairments on transmitted waveforms and makes their compensation more difficult. Research into front-end impairment compensation in millimeter-wave frequency bands is currently being carried out, mainly using expensive laboratory setups consisting of universal signal generators, spectral analyzers and high-speed oscilloscopes. This paper presents a detailed description of an in-house built MATLAB-controlled 60 GHz measurement test-bed developed using relatively inexpensive hardware components that are available on the market and equipped with digital compensation for the most critical front-end impairments, including the digital predistortion of the power amplifier. It also demonstrates the potential of digital predistortion linearization on two distinct 60 GHz power amplifiers: one integrated in a direct-conversion transceiver and an external one with 24 dBm output power.

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37

Usman, Ovais Bin, and Andreas Knopp. "Digital Predistortion in High Throughput Satellites: Architectures and Performance." IEEE Access 9 (2021): 42291–304. http://dx.doi.org/10.1109/access.2021.3065745.

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38

Zhao, Jianing, Jianyi Zhou, Ningde Xie, Jianfeng Zhai, and Lei Zhang. "Error Analysis and Compensation Algorithm for Digital Predistortion Systems." PIERS Online 2, no. 6 (2006): 702–5. http://dx.doi.org/10.2529/piers060901232412.

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39

Park, Chan-Won, Eui-Rim Jeong, and Ji-Hoon Kim. "A new digital predistortion technique for analog beamforming systems." IEICE Electronics Express 13, no. 2 (2016): 20150998. http://dx.doi.org/10.1587/elex.13.20150998.

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40

Cao, Wenhui, Siqi Wang, Per N. Landin, Christian Fager, and Thomas Eriksson. "Complexity Optimized Digital Predistortion Model of RF Power Amplifiers." IEEE Transactions on Microwave Theory and Techniques 70, no. 3 (March 2022): 1490–99. http://dx.doi.org/10.1109/tmtt.2021.3122956.

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41

Woo, Young Yun, Jangheon Kim, Jaehyok Yi, Sungchul Hong, Ildu Kim, Junghwan Moon, and Bumman Kim. "Adaptive Digital Feedback Predistortion Technique for Linearizing Power Amplifiers." IEEE Transactions on Microwave Theory and Techniques 55, no. 5 (May 2007): 932–40. http://dx.doi.org/10.1109/tmtt.2007.895145.

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42

Choi, Sung-Ho, Byung-Hwan Lee, Chul-Soo Lee, and Eui-Rim Jeong. "Digital Predistortion for Multi-band/Multi-mode Transmission Systems." Journal of the Korean Institute of Information and Communication Engineering 16, no. 1 (January 31, 2012): 48–58. http://dx.doi.org/10.6109/jkiice.2012.16.1.048.

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43

Traverso, Sylvain, and Jean-Yves Bernier. "Low Complexity Time Synchronization Based on Digital Predistortion Coefficients." IEEE Microwave and Wireless Components Letters 29, no. 3 (March 2019): 240–42. http://dx.doi.org/10.1109/lmwc.2019.2895544.

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44

Jing, Jianxin, and Chao Yu. "Multibeam Digital Predistortion for Millimeter-Wave Analog Beamforming Transmitters." IEEE Microwave and Wireless Components Letters 30, no. 2 (February 2020): 209–12. http://dx.doi.org/10.1109/lmwc.2019.2959431.

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45

Choi, Sungho, and Eui-Rim Jeong. "Digital Predistortion Based on Combined Feedback in MIMO Transmitters." IEEE Communications Letters 16, no. 10 (October 2012): 1572–75. http://dx.doi.org/10.1109/lcomm.2012.080312.120224.

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46

Seebacher, David, Peter Singerl, Christian Schuberth, Franz Dielacher, Yannis Papananos, Nikolaos Alexiou, Kostas Galanopoulos, Michael E. Gadringer, and Wolfgang Bosch. "Predistortion of Digital RF PWM Signals Considering Conditional Memory." IEEE Transactions on Circuits and Systems I: Regular Papers 62, no. 9 (September 2015): 2342–50. http://dx.doi.org/10.1109/tcsi.2015.2451931.

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47

Guan, Lei, and Anding Zhu. "Green Communications: Digital Predistortion for Wideband RF Power Amplifiers." IEEE Microwave Magazine 15, no. 7 (November 2014): 84–99. http://dx.doi.org/10.1109/mmm.2014.2356037.

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48

Chauhan, Hari, Marvin Onabajo, Vladimir Kvartenko, Robin Coxe, and Theophane Weber. "An Optimization Platform for Digital Predistortion of Power Amplifiers." IEEE Design & Test 33, no. 2 (April 2016): 49–58. http://dx.doi.org/10.1109/mdat.2015.2480702.

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49

Hong, Soon-il, Kwang-Pyo Lee, and Eui-Rim Jeong. "Robust Digital Predistortion in Saturation Region of Power Amplifiers." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (February 1, 2016): 99. http://dx.doi.org/10.11591/ijece.v6i1.9337.

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This paper proposes a digital predistortion (DPD) technique to improve linearization performance when the power amplifier (PA) is driven near the saturation region. The PA is a non-linear device in general, and the nonlinear distortion becomes severer as the output power increases. However, the PA’s power efficiency increases as the PA output power increases. The nonlinearity results in spectral regrowth, which leads to adjacent channel interference, and degrades the transmit signal quality. According to our simulation, the linearization performance of DPD is degraded abruptly when the PA operates in its saturation region. To relieve this problem, we propose an improved DPD technique. The proposed technique performs on/off control of the adaptive algorithm based on the magnitude of the transmitted signal. Specifically, the adaptation normally works for small and medium signals while it stops for large signals. Therefore, harmful coefficient updates by saturated signals can be avoided. A computer simulation shows that the proposed method can improve the linearization performance compared with the conventional DPD method in highly driven PAs.

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50

Hong, Soon-il, Kwang-Pyo Lee, and Eui-Rim Jeong. "Robust Digital Predistortion in Saturation Region of Power Amplifiers." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (February 1, 2016): 99. http://dx.doi.org/10.11591/ijece.v6i1.pp99-105.

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This paper proposes a digital predistortion (DPD) technique to improve linearization performance when the power amplifier (PA) is driven near the saturation region. The PA is a non-linear device in general, and the nonlinear distortion becomes severer as the output power increases. However, the PA’s power efficiency increases as the PA output power increases. The nonlinearity results in spectral regrowth, which leads to adjacent channel interference, and degrades the transmit signal quality. According to our simulation, the linearization performance of DPD is degraded abruptly when the PA operates in its saturation region. To relieve this problem, we propose an improved DPD technique. The proposed technique performs on/off control of the adaptive algorithm based on the magnitude of the transmitted signal. Specifically, the adaptation normally works for small and medium signals while it stops for large signals. Therefore, harmful coefficient updates by saturated signals can be avoided. A computer simulation shows that the proposed method can improve the linearization performance compared with the conventional DPD method in highly driven PAs.

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