Test bed for characterization and predistortion of power amplifiers

Ma, Yuelin; Akaiwa, Yoshihiko; Yamao, Yasushi; He, Songbai

doi:10.1002/mmce.20653

Cited by 12 publications

(4 citation statements)

References 12 publications

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“…Directly calculating the cross-correlation between the signs of the input and output in the time domain will cause large errors. In this paper, instead, we suggest to use the frequency domain based algorithm to estimate the time delay [29], [30].…”

Section: B Time-alignment Algorithmmentioning

confidence: 99%

1-bit Observation for Direct-Learning-Based Digital Predistortion of RF Power Amplifiers

Wang

Zhou

et al. 2017

IEEE Trans. Microwave Theory Techn.

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In this paper, we propose a low-cost data acquisition approach for model extraction of digital predistortion (DPD) of RF power amplifiers. The proposed approach utilizes only 1-bit resolution analog-to-digital converters (ADCs) in the observation path to digitize the error signal between the input and output signals. The DPD coefficients are then estimated based on the direct learning architecture using the measured signs of the error signal. The proposed solution is proved to be feasible in theory and the experimental results show that the proposed algorithm achieves equivalent performance as that using the conventional method. Replacing high resolution ADCs with 1bit comparators in the feedback path can dramatically reduce the power consumption and cost of the DPD system. The 1-bit solution also makes DPD become practically implementable in future broadband systems since it is relatively straightforward to achieve an ultra-high sampling speed in data conversion by using only simple comparators.

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Section: B Time-alignment Algorithmmentioning

confidence: 99%

1-bit Observation for Direct-Learning-Based Digital Predistortion of RF Power Amplifiers

Wang

Zhou

et al. 2017

IEEE Trans. Microwave Theory Techn.

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“…Behavioral modeling of radio‐frequency (RF) and microwave power amplifiers (PAs) for communications has been the focus of considerable research efforts over the last years 1,2,3,4,5,6,7 . Multiple physical and circuital causes concur in determining the complex nonlinear dynamic behavior displayed by RF PAs under typical operating conditions, for example, input/output/interstage matching networks, parasitic supply modulation, charge trapping phenomena, and self‐heating effects, leading to a variety of interlinked memory effects with characteristic time constants distributed across many orders of magnitude.…”

Section: Introductionmentioning

confidence: 99%

“…Multiple physical and circuital causes concur in determining the complex nonlinear dynamic behavior displayed by RF PAs under typical operating conditions, for example, input/output/interstage matching networks, parasitic supply modulation, charge trapping phenomena, and self‐heating effects, leading to a variety of interlinked memory effects with characteristic time constants distributed across many orders of magnitude. Nevertheless, accurate behavioral models of RF PAs are required for system‐level simulation and optimization of RF transmitters, 8 as well as to improve the design of digital predistortion (DPD) linearizers 4,5 . Such models, apart from the good fitting properties, should display favorable characteristics in terms of generality, ease of extraction, and efficiency of the implementation.…”

Section: Introductionmentioning

confidence: 99%

Efficient implementation of a modified‐Volterra radio‐frequency power amplifier nonlinear dynamic model by global rational functions approximation

Angelotti

Gibiino

Santarelli

2020

Int J RF Microw Comput Aided Eng

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Power amplifiers (PAs) used in modern radio frequency transmitters for communications display significant nonlinear dynamic effects under typical operating regimes. Accurate and efficient implementations of behavioral models describing these effects are required in order to enable system-level simulation, or for guiding the design of effective linearization predistorters. This work proposes an efficient implementation of the widely adopted modified-Volterra model, resulting from a global rational functions approximation of the model nonlinear convolution kernels. The proposed implementation, tested by gallium nitride PA simulations, reproduces the model behavior with highaccuracy and features an extremely compact structure, comparing favorably with alternative descriptions.

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“…Fractional time delay estimation (referred to as FDE), also known as subsample time delay estimation, is widely utilized in high precision location (such as the radar [1,2], the medical auxiliary diagnostic [3], the satellite navigation [4] and the fault location [5]) and the time delay compensation (such as the digital pre-distortion [6,7], sensors calibration [8] and the beam forming [9]). …”

Section: Introductionmentioning

confidence: 99%

Fractional time delay estimation algorithm based on the maximum correntropy criterion and the Lagrange FDF

Qiu

Luan

2015

Signal Processing

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Test bed for characterization and predistortion of power amplifiers

Cited by 12 publications

References 12 publications

1-bit Observation for Direct-Learning-Based Digital Predistortion of RF Power Amplifiers

1-bit Observation for Direct-Learning-Based Digital Predistortion of RF Power Amplifiers

Efficient implementation of a modified‐Volterra radio‐frequency power amplifier nonlinear dynamic model by global rational functions approximation

Fractional time delay estimation algorithm based on the maximum correntropy criterion and the Lagrange FDF

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