Proceedings ArticleDOI
Digital Predistorter with Real-Valued Feedback Employing Forward Model Estimation
Jan Kral,Tomas Gothans,Roman Marsalek,Michal Harvanek +3 more
- pp 471-475
TLDR
An innovative technique is proposed which allows to use a nonquadrature RF mixer with one ADC in the feedback path to achieve the same results as a DPD with complex feedback samples and the other real-valued feedback architectures.Abstract:
Digital predistorters (DPD) are used in modern communication systems to linearise nonlinear power amplifiers (PA) and maximise power efficiency For their function, a feedback signal from the PA output is required A conventional DPD uses a quadrature mixer and two analogue-to-digital converters (ADC) which consume additional power and increase system complexity In this paper we have proposed an innovative technique which allows to use a nonquadrature RF mixer with one ADC in the feedback path The DPD adaptation is noniterative and based on favoured indirect learning architecture Firstly, the forward PA model is estimated and subsequently it is used to train DPD coefficients We have verified and compared the proposed method with other DPD architectures in simulations The results show that the proposed architecture can achieve the same results as a DPD with complex feedback samples and the other real-valued feedback architecturesread more
Citations
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Journal ArticleDOI
On Feedback Sample Selection Methods Allowing Lightweight Digital Predistorter Adaptation
TL;DR: It is shown that the computational complexity of D PD adaptation can be drastically reduced if a low number of samples is properly selected for DPD adaptation, and methods of sample selection are proposed.
Journal ArticleDOI
Digital predistortion based on sample selection with memory effect
Guichen Yang,Guichen Yang,Hongmin Li,Hongmin Li,Wen Qiao,Wen Qiao,Chengye Jiang,Chengye Jiang,Qiao Liu,Guangjian Wang,Falin Liu,Falin Liu +11 more
Journal ArticleDOI
Digitally-Compensated Wideband 60 GHz Test-Bed for Power Amplifier Predistortion Experiments
TL;DR: 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.
Journal ArticleDOI
Early Stopping Criterion for Recursive Least Squares Training of Behavioural Models
TL;DR: In this paper , the authors proposed a technique to detect the onset of instability during adaptive RLS training and subsequently to inform the decision to cease training of dynamic memory polynomial based behavioral models, to avoid the arrival of instability.
Proceedings ArticleDOI
Real-Valued Sign Algorithm for Digital Predistortion Based on Direct Learning Architecture
Tianbao Wang,Hua Wei +1 more
TL;DR: In this paper , a real-valued sign algorithm (RVS) based on direct learning architecture (DLA) is proposed, which allows only single 1-bit resolution ADC to be used in the feedback path.
References
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Journal ArticleDOI
Digital predistortion of wideband signals based on power amplifier model with memory
Jungsang Kim,K. Konstantinou +1 more
TL;DR: In this paper, memory effects in the power amplifier limit the performance of digital predistortion for wideband signals, and novel algorithms that take into account such effects are proposed to solve the problem.
Journal ArticleDOI
Behavioral modeling and predistortion
TL;DR: A software digital predistortion solution that enables closed-loop wideband linearization was briefly presented with excellent linearization capabilities when amplifying a 12-carrier 60-MHZ wide WCDMA signal.
Journal ArticleDOI
Iterative Learning Control for RF Power Amplifier Linearization
TL;DR: In this paper, an iterative learning algorithm is proposed to identify the optimal power amplifier (PA) input signal that drives the PA to the desired linear output response, and the parameters of the predistorter are estimated using standard modeling approaches, e.g., least squares.
Proceedings ArticleDOI
Comparison of direct learning and indirect learning predistortion architectures
Henna Paaso,Aarne Mammela +1 more
TL;DR: This paper modeled predistorters and analysed nonlinear effects of a power amplifier and their digital compensation by using Matlab and showed that the memory polynomial model has convergence problems at large amplitudes and also problems of accuracy of representation.
Journal ArticleDOI
Filter Lookup Table Method for Power Amplifier Linearization
P. Jardin,Genevieve Baudoin +1 more
TL;DR: The new technique, due to the addition of filters to the LUT, has possibilities to compensate not only for the nonlinearity but also for the memory effects in the PA, and it is one order of magnitude less complex than the memory polynomial system.