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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, t
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2

Ahmed, Serien, Majid Ahmed, Souheil Bensmida, and Oualid Hammi. "Power Amplifier Predistortion Using Reduced Sampling Rates in the Forward and Feedback Paths." Sensors 24, no. 11 (2024): 3439. http://dx.doi.org/10.3390/s24113439.

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The feasibility of implementing digital predistortion for next-generation wireless communication is faced with a dilemma due to the ever-increasing demand for faster data rates. This causes the utilized bandwidth to increase significantly, as seen in the 5G NR standard in which bandwidths as high as 400 MHz are utilized. Hence, the development of new predistortion techniques in which the forward and feedback paths operate at lower sampling rates is of utmost importance to realize efficient and practical predistortion solutions. In this work, a novel predistortion technique is presented by whic
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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 (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 predistort
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4

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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5

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
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6

Song, Wenxian, Guofu Wang, and Jincai Ye. "A Novel Digital Predistortion Identification Algorithm Based on Variable Forgetting Factor Recursive Least Square Method." International Journal of RF and Microwave Computer-Aided Engineering 2023 (May 20, 2023): 1–10. http://dx.doi.org/10.1155/2023/6377941.

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The transmitting signal of wireless communication system is impaired by the nonlinearity of RF power amplifier (PA) which leads to signal distortion and spectrum spillover, by which the signal transmission quality is affected. Digital predistortion (DPD) is an efficient and economical way to correct the nonlinear effects of power amplifiers. The recursive least square (RLS) recognition algorithm is commonly used to extract the correction coefficients of the DPD model, and the accuracy of the extraction directly affects the system performance. In this paper, a new variable forgetting factor ide
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7

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

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8

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

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9

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

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10

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

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11

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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12

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 (2018): 445–54. http://dx.doi.org/10.1109/jstsp.2018.2824981.

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13

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
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14

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 scientifi
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15

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
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16

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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17

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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18

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 (2022): 569. http://dx.doi.org/10.1360/ssi-2021-0421.

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19

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

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20

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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21

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

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22

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

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23

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

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24

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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25

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 (2017): 1495–505. http://dx.doi.org/10.1007/s11265-017-1303-1.

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26

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 (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
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27

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
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28

Abdelnaby, Moustafa, Reem Alnajjar, Souheil Bensmida, and Oualid Hammi. "Reduced Complexity Sequential Digital Predistortion Technique for 5G Applications." Smart Cities 7, no. 2 (2024): 772–85. http://dx.doi.org/10.3390/smartcities7020032.

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Wireless communication infrastructure is a key enabling technology for smart cities. This paper investigates a novel technique to enhance the performance of 5G base stations by addressing the compensation of nonlinear distortions caused by radiofrequency power amplifiers. For this purpose, a sequential digital predistortion approach that uses twin nonlinear two-box structure along with reduced sampling rates in the feedback path is proposed to implement a linearization system. Such a system is shown to have a correction bandwidth that exceeds the bandwidth of the feedback path. This is achieve
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29

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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30

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

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31

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

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32

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 (2016): 2452–66. http://dx.doi.org/10.1109/taes.2016.150142.

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33

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

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34

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

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35

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 (2015): 254–67. http://dx.doi.org/10.1109/tcomm.2014.2364571.

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36

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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37

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 (2018): 93–108. http://dx.doi.org/10.1007/s10470-018-1347-6.

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38

Chen, Boyuan, and Wei Wu. "Principles, applications, and challenges of digital predistortion technology." Applied and Computational Engineering 54, no. 1 (2024): 64–75. http://dx.doi.org/10.54254/2755-2721/54/20241262.

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A power amplifier plays a crucial role in the transmitter end of wireless communication systems. Despite enhancing operational efficiency, it inadvertently introduces nonlinear distortion, leading to signal degradation and spectral regrowth. This occurrence necessitates the incorporation of additional linearization techniques in transmitter terminals to optimize both efficiency and linearity concurrently. Among these, Digital Pre-Distortion (DPD) technology stands out as a well-researched and extensively employed strategy for alleviating the nonlinear distortion induced by power amplifiers. Th
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39

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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40

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 (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 osc
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41

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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42

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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43

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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44

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 (2022): 1490–99. http://dx.doi.org/10.1109/tmtt.2021.3122956.

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45

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

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46

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 (2012): 48–58. http://dx.doi.org/10.6109/jkiice.2012.16.1.048.

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47

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

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48

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

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49

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

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50

Seebacher, David, Peter Singerl, Christian Schuberth, et al. "Predistortion of Digital RF PWM Signals Considering Conditional Memory." IEEE Transactions on Circuits and Systems I: Regular Papers 62, no. 9 (2015): 2342–50. http://dx.doi.org/10.1109/tcsi.2015.2451931.

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