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Predistortion for Nonlinear Power Amplifiers with MemoryNizamuddin, Muhammad Ali 30 December 2002 (has links)
The fusion of voice and data applications, along with the demand for high data-rate applications such as video-on-demand, is making radio frequency (RF) spectrum an increasingly expensive commodity for current and future communications. Although bandwidth-efficient digital modulation alleviates part of the problem by requiring a minimal use of spectral resources, they put an extra design burden on RF engineers. RF transmitters and power amplifiers account for more than half the total maintenance cost of a base-station, while occupying nearly the same portion of space. Therefore, power amplifiers become a bottleneck for digital systems in terms of space and power consumption. However, power-efficient use of the amplifiers, although desirable, is extremely detrimental to end-to-end performance due to the very high peak-to-average power ratios of modulations that are used today. In order to reduce distortion while maintaining high power conversion efficiency in a power amplifier, linearization schemes are needed. In addition, significant frequency-dependent Memory Effects result in high power amplifiers operating on wideband signals. Therefore, these effects need to be considered during any attempt to minimize amplifier distortion.
In this thesis, we present two schemes to cancel nonlinear distortion of a power amplifier, along with its memory effects and results for one of the schemes. The results highlight the fact that in the presence of significant memory effects, cancellation of these effects is necessary to achieve reasonable improvement in performance through linearization. We focus on predistortive schemes due to their digital- friendly structure and simple implementation. The operating environment consists of a multi-carrier W-CDMA signal. All of the studies are performed using numerical simulation on MATLAB and Agilent's Advanced Design System (ADS). / Master of Science
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Identifica??o em tempo real de modelo din?mico de rob? m?vel com acionamento diferencial e zona mortaMendes, Ellon Paiva 27 January 2012 (has links)
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Previous issue date: 2012-01-27 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / Several mobile robots show non-linear behavior, mainly due friction phenomena between
the mechanical parts of the robot or between the robot and the ground. Linear
models are efficient in some cases, but it is necessary take the robot non-linearity in consideration
when precise displacement and positioning are desired. In this work a parametric
model identification procedure for a mobile robot with differential drive that considers the
dead-zone in the robot actuators is proposed. The method consists in dividing the system
into Hammerstein systems and then uses the key-term separation principle to present the
input-output relations which shows the parameters from both linear and non-linear blocks.
The parameters are then simultaneously estimated through a recursive least squares algorithm.
The results shows that is possible to identify the dead-zone thresholds together
with the linear parameters / V?rios rob?s m?veis apresentam comportamentos n?o-lineares, principalmente ocasionados
por fen?menos de atrito entre as partes mec?nicas do rob? ou entre o rob? e o
solo. Modelagens puramente lineares apresentam-se eficientes em alguns casos, mas ?
preciso levar em considera??o as n?o-linearidades do rob? quando se deseja movimentos
ou posicionamentos precisos. Este trabalho prop?e um procedimento de identifica??o
param?trica do modelo de um rob? m?vel com acionamento diferencial, no qual s?o consideradas
as n?o-linearidades do tipo zona-morta presentes nos atuadores do rob?. A
proposta baseia-se no modelo de Hammerstein para dividir o sistema em blocos lineares
e n?o-lineares. O princ?pio da separa??o do termo chave ? utilizado para demonstrar a
rela??o entre as entradas e sa?das do sistema com os par?metros tanto da parcela linear
quanto da n?o-linear. Os par?metros de ambas as parcelas s?o identificados simultaneamente,
atrav?s de um algoritmo de m?nimos quadrados recursivo. Os resultados mostram
que ? poss?vel identificar o valor os limites da zona-morta assim como os par?metros da
parcela linear do modelo do sistema
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