Signal parameters estimation and its applications in communication systems
- Publication Type:
- Thesis
- Issue Date:
- 2007
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 01Front.pdf | contents and abstract | 1.54 MB | |||
| 02Whole.pdf | thesis | 47.16 MB |
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NO FULL TEXT AVAILABLE. Access is restricted indefinitely. ----- Parameter estimation of frequency tones is one of the oldest problems
in signal processing. It involves estimating the frequency, phase
and amplitude of a single or multiple complex exponential signal(s).
Embedded in the frequencies, phases and amplitudes is information
which can be extracted for tracking movement of a moving object or
alternatively be translated by digital decoders into meaningful data
for the intended recipient. In fact, signal parameter estimation can be
applied in many different fields ranging from biomedical technology
such as ultrasound [29] [37] [8], sophisticated military applications like
radar and sonar [27] [38] [105], to carrier synchronisation for communication
systems.
Over the years, researchers have proposed numerous solutions to the
problem of estimating the parameters of frequency tones. They all
in general, however, suffer from either one or the other of the following
impairments: high computational complexity or very poor error
performance in noisy environments. The former may prohibit the
algorithm being applied in real time applications such as carrier synchronisation
and the latter compromises on accuracy of the estimates
when operating in noisy environments.
This thesis is aimed at developing state of the art carrier acquisition
and tracking algorithms for the next generation of software radio
modems. The work is divided into two parts. The first part of the
thesis is devoted to the investigation into and development of parameter
estimation algorithms for complex frequency tones and general
bandpass signals, that are computationally efficient and yet effective
in very noisy environments. It begins by identifying an existing highly
accurate DFT based single tone frequency estimation algorithm that
holds the key to the answer. It will be shown by combining this DFT
based frequency estimator with ML phase and amplitude estimators
yields a highly accurate parameter estimation algorithm for a single
complex tone. By exploiting a key property of the aforementioned
DFT based frequency estimation algorithm, it is possible to derive a
computationally efficient parameter estimation algorithm for complex
bandpass signals. The performance of these estimation algorithms are
comparable and, in some circumstances, exceed existing state of the
art techniques.
The second part of the thesis begins by revisiting the theory of digital
phase locked loop (DPLL), in particular the four quadrant arctangent
phase detector based DPLL, which is suited for digital signal processor
(DSP) implementation [49]. A by product of digitally implementing
a feedback loop is the inherent delay between the input and output of
the loop. If the ratio between speed of the digital signal processor and
sampling rate of the analog to digital converter (ADC) is relatively
low, this delay can be significant, up to several sample periods.
This inherent delay affects the characteristics of the DPLL such as
loop stability [128] [10] [11] and frequency pull-in and hold in range
[21] [76]. This thesis revisits the analysis of the effective noise bandwidth
of the DPLL, taking into account of the aforementioned loop
delay at low sampling rate relative to the continuous time noise bandwidth
of the PLL. This study of the effective noise bandwidth leads
to a better understanding of how loop delay affects the steady noise
variance performance of the DPLL.
Traditionally, the acquisition process of the DPLL is described with
the aid of a phase plane which provides a graphical illustration of the
frequency vs phase trajectory over time [34] [17] [50]. In this thesis,
a new way of describing the noiseless acquisition behaviour of the
DPLL is presented, based on time series analysis of the individual
loop components. It will be shown that the number of expected cycle
slips and acquisition time for a given frequency and phase can be
precisely calculated from the time series equations using numerical
methods.
Finally, a new discriminator aided DPLL (DA-DPLL) is presented.
This discriminator aided DPLL is formed by integrating the proposed
DFT based parameter estimation algorithm with the DPLL. Feeding
the frequency and phase estimates into the DPLL helps accelerate the
acquisition process. Using the error distribution analysis of the DFT
based parameter estimator, it is possible predict the worst case error
transient of the DA-DPLL in noisy conditions.
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