Nonlinear System Identification and Analysis with Applications toPower Amplifier Modeling and Power Amplifier Predistortion

Linearization;Spectral analysis;Predistortion;Nonlinear system identification;Power amplifiers

Raich, Raviv ; Electrical and Computer Engineering

University:Georgia Institute of Technology

Department:Electrical and Computer Engineering

关键词: Linearization;    Spectral analysis;    Predistortion;    Nonlinear system identification;    Power amplifiers;   

Others  :  https://smartech.gatech.edu/bitstream/1853/5152/1/raich_raviv_200405_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Power amplifiers (PAs) are important components of communicationsystems and are inherently nonlinear. When a non-constant modulussignal goes through a nonlinear PA, spectral regrowth (broadening)appears in the PA output, which in turn causes adjacent channelinterference (ACI). Stringent limits on the ACI are imposed byregulatory bodies, and thus the extent of the PA nonlinearity mustbe controlled. PA linearization is often necessary to suppressspectral regrowth, contain adjacent channel interference, andreduce bit error rate (BER). This dissertation addresses thefollowing aspects of power amplifier research: modeling,linearization, and spectral regrowth analysis.We explore the passband and baseband PA input/output relationshipsand show that they manifest differently when the PA exhibitslong-term, short-term, or no memory effects. The so-calledquasi-memoryless case is especially clarified. Four particularnonlinear models with memory are further investigated. We provideexperimental results to support our analysis.The benefits of using the orthogonal polynomials as opposed to theconventional polynomials are explored, in the context of digitalbaseband PA modeling and predistorter design. A closed-formexpression for the orthogonal polynomial basis is derived. Wedemonstrate the improvement in numerical stability associated withthe use of orthogonal polynomials for predistortion.Spectral analysis can help to evaluate the suitability of a givenPA for amplifying certain signals or to assist in predistortionlinearization algorithm design. With the orthogonal polynomialsthat we derived, spectral analysis of the nonlinear PA becomes astraightforward task. We carry out nonlinear spectral analysiswith digitally modulated signal as input. We demonstrate ananalytical approach for evaluating the power spectra of filteredQPSK and OQPSK signals after nonlinear amplification.Many communications devices are nonlinear and have a peak power orpeak amplitude constraint. In addition to possibly amplifying theuseful signal, the nonlinearity also generates distortions. Wefocus on signal-to-noise-and-distortion ratio (SNDR) optimizationwithin the family of amplitude limited memoryless nonlinearities.We obtain a link between the capacity of amplitude-limitednonlinear channels with Gaussian noise to the SNDR.