scholarly journals Forward Behavioral Modeling of a Three-Way Amplitude Modulator-Based Transmitter Using an Augmented Memory Polynomial

Sensors ◽  
2018 ◽  
Vol 18 (3) ◽  
pp. 770
Author(s):  
◽  
◽  
Keyword(s):  
Behavioral Modeling ◽  
Amplitude Modulator ◽  
Memory Polynomial

Research on Modeling Methods of Power Amplifier with Memory Effect in Broadband Communication

2014 ◽  
Vol 687-691 ◽  
pp. 4060-4063
Author(s):  
Lu Sun ◽  
Long Long Xue ◽  
Jia Li Wang ◽  
Chun Yang Zhou
Keyword(s):  
Memory Effect ◽  
Power Amplifier ◽  
Polynomial Model ◽  
Behavioral Modeling ◽  
Design System ◽  
Behavioral Models ◽  
Electric Characteristic ◽  
Memory Polynomial ◽  
With Memory ◽  
Frequency Power

Memory effect of power amplifier (PA) due to broadband signals which adopt new modulation technique is becoming obvious, and worsening the linearity of PA. Behavioral modeling for RF (Radio Frequency) power amplifier is indispensable to design digital pre-distortion system by which we can promote the efficiency of PA. According to the simulation data in the software of ADS (Advanced Design System), behavioral models of MRF21085 amplifier can be established by MATLAB. Comparison of memory polynomial model and ADS simulation of MRF21085 amplifier demonstrate memory polynomial model can represent the electric characteristic of it exactly.

Efficient Pruning Technique of Memory Polynomial Models Suitable for PA Behavioral Modeling and Digital Predistortion

2014 ◽  
Vol 62 (10) ◽  
pp. 2290-2299 ◽  
Author(s):  
Wenhua Chen ◽  
Silong Zhang ◽  
You-Jiang Liu ◽  
Fadhel M. Ghannouchi ◽  
Zhenghe Feng ◽  
...  
Keyword(s):  
Behavioral Modeling ◽  
Digital Predistortion ◽  
Polynomial Models ◽  
Memory Polynomial ◽  
Pruning Technique

A Novel Weighted Memory Polynomial for Behavioral Modeling and Digital Predistortion of Nonlinear Wireless Transmitters

2016 ◽  
Vol 63 (3) ◽  
pp. 1745-1753 ◽  
Author(s):  
Abdalla E. Abdelrahman ◽  
Oualid Hammi ◽  
Andrew K. Kwan ◽  
Azzedine Zerguine ◽  
Fadhel M. Ghannouchi
Keyword(s):  
Behavioral Modeling ◽  
Digital Predistortion ◽  
Wireless Transmitters ◽  
Memory Polynomial

Behavioral Modeling and Design of Predistortion for Wireless Transmitters with Multi-Branch RF Power Amplifier

2013 ◽  
Vol 284-287 ◽  
pp. 2615-2621 ◽  
Author(s):  
Won Shil Kang ◽  
Jong Gyun Lim ◽  
Kang Yoon Lee ◽  
Hyun Chul Ku
Keyword(s):  
Modeling Method ◽  
Behavioral Modeling ◽  
Rf Power Amplifiers ◽  
Behavioral Models ◽  
Rf Power ◽  
Wireless Transmitters ◽  
Rf Power Amplifier ◽  
Single Output ◽  
Single Input ◽  
Memory Polynomial

In this paper, behavioral modeling approach and predistortion design methods are proposed for wireless transmitters with multi-branch radio frequency (RF) power amplifiers (PAs). Multi -branch RF PA architectures are studied such as balanced RF PA systems and linear amplification with nonlinear component (LINC) systems. Conventional behavioral modeling using single input and single output data cannot extract the behaviors of RF PAs in each branch. The behavioral modeling method using separated input signals and weighted input identification is proposed to extract accurate behavioral models for each branch. A decentralized predistortion structure that consists of multi-branch memory polynomial architecture predistortion components is proposed. The proposed behavioral modeling method is used for the design of decentralized predistortion using indirect learning method. The performances of proposed modeling and predistortion method are evaluated by comparing the normalized mean square error (NMSE) values with conventional single-branch behavioral modeling and predistortion. The input signal is 10MHz long-term evolution (LTE) signal. The results show that the proposed behavioral modeling and decentralized predistortion architecture are suitable for wireless transmitters with multi-branch RF PAs.

Application of embedding dimension estimation to Volterra series-based behavioral modeling and predistortion of wideband RF power amplifier

2013 ◽  
Vol 5 (2) ◽  
pp. 115-122 ◽  
Author(s):  
Bilel Fehri ◽  
Slim Boumaiza
Keyword(s):  
Power Amplifiers ◽  
Volterra Series ◽  
Model Performance ◽  
Behavioral Modeling ◽  
Embedding Dimension ◽  
Rf Power ◽  
Rf Power Amplifier ◽  
Volterra Models ◽  
Wideband Signals ◽  
Memory Polynomial

This paper expounds the systematic modeling of the behavior of radio frequency (RF) power amplifiers (PAs) exhibiting nonlinear, dynamic behavior. The approach begins with an analysis of the PA output signal to deduce the minimum embedding parameters required to accurately model its response, particularly the nonlinearity order and memory effects depth. The knowledge of the RF PA is then exploited in limiting the number of kernels consequently addressing the complexity of the Volterra series which has been the key hindrance to its wider practical adoption. In the proposed Volterra series model, performance is assessed and compared to memory polynomial model and dynamic deviation reduction Volterra models when used to linearize different high-power amplifiers driven with wideband signals of bandwidth up to 40 MHz. Significant linearization performance is achieved using a reduced number of kernels.

Sparsity Adaptive Estimation of Memory Polynomial Based Models for Power Amplifier Behavioral Modeling

2016 ◽  
Vol 26 (5) ◽  
pp. 370-372 ◽  
Author(s):  
Mingyu Li ◽  
Zhenxing Yang ◽  
Zhongming Zhang ◽  
Ruoyu Li ◽  
Qing Dong ◽  
...  
Keyword(s):  
Power Amplifier ◽  
Adaptive Estimation ◽  
Behavioral Modeling ◽  
Memory Polynomial
Sign in / Sign up

Export Citation Format

Share Document