Power amplifiers (PAs) are important components of communication
systems and are inherently nonlinear. When a non-constant modulus
signal goes through a nonlinear PA, spectral regrowth (broadening)
appears in the PA output, which in turn causes adjacent channel
interference (ACI). Stringent limits on the ACI are imposed by
regulatory bodies, and thus the extent of the PA nonlinearity must
be controlled. PA linearization is often necessary to suppress
spectral regrowth, contain adjacent channel interference, and
reduce bit error rate (BER). This dissertation addresses the
following aspects of power amplifier research: modeling,
linearization, and spectral regrowth analysis.
We explore the passband and baseband PA input/output relationships
and show that they manifest differently when the PA exhibits
long-term, short-term, or no memory effects. The so-called
quasi-memoryless case is especially clarified. Four particular
nonlinear models with memory are further investigated. We provide
experimental results to support our analysis.
The benefits of using the orthogonal polynomials as opposed to the
conventional polynomials are explored, in the context of digital
baseband PA modeling and predistorter design. A closed-form
expression for the orthogonal polynomial basis is derived. We
demonstrate the improvement in numerical stability associated with
the use of orthogonal polynomials for predistortion.
Spectral analysis can help to evaluate the suitability of a given
PA for amplifying certain signals or to assist in predistortion
linearization algorithm design. With the orthogonal polynomials
that we derived, spectral analysis of the nonlinear PA becomes a
straightforward task. We carry out nonlinear spectral analysis
with digitally modulated signal as input. We demonstrate an
analytical approach for evaluating the power spectra of filtered
QPSK and OQPSK signals after nonlinear amplification.
Many communications devices are nonlinear and have a peak power or
peak amplitude constraint. In addition to possibly amplifying the
useful signal, the nonlinearity also generates distortions. We
focus on signal-to-noise-and-distortion ratio (SNDR) optimization
within the family of amplitude limited memoryless nonlinearities.
We obtain a link between the capacity of amplitude-limited
nonlinear channels with Gaussian noise to the SNDR.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/5152 |
| Date | 07 April 2004 |
| Creators | Raich, Raviv |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 1750050 bytes, application/pdf |
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