The Advanced Digital Communication System Modeler (AdvDCSM) technology is currently implemented in the Digital Communication System Simulator AdvDCSMT1DCSS or T1, an Intel® PC Computer-based software tool.
The AdvDCSMT1DCSS application is the result of intense study, analysis and design of Digital Communications Systems in Systems Simulators and of PC Visual C++®.Net and Microsoft Foundation Class Library software development work running under Microsoft® Windows®. This work was performed by Darrell A. Nolta.
He studied at the Henry Samueli School of Engineering of the University of California, Irvine (UCI) for the Degree of Master of Science (M.S.) in Electrical and Computer Engineering. His dissertation, Titled: Computer-Based Simulation and Performance Evaluation of Communication Systems using Trellis-Coded Modulation, Published: 1998 can be found in the University of California Library Collection (UCI Science Library). One can find a copy of the Abstract of his dissertation below.
He earned a degree of Bachelor of Science (B.S.) in Electrical Engineering at the USC Viterbi School of Engineering of the University of Southern California (USC).
Also, he obtained Training in Systems Engineering at TRW where he was a Senior Member of Technical Staff and a Principal Investigator of an IR&D (Independent Research & Development) project.
Currently, his research interests/work pertains to the following key areas of today's technological advancements:
i) Application of the Convolutional Coding Theory, Viterbi Decoding Algorithm and Complex System Modeling and Simulation to the development of unique Realizable Optimal Channel Decoders or State Estimators where these structures and associated algorithms can be practically implemented and operated in real devices;
ii) Application of Expert Systems Technology and Intelligent Agents: "Smart" Human Machine Interface and Reliability of Machine Generated Processes to the development of "Smart Adaptive System Simulators and Performance Evaluators" that can be used for studying or creating novel Digital Communication Systems and BioTechnology Systems including Computational Biological and BioChemical Systems (System Biology); and
iii) Study and Development of accurate, analytical, and numerical formulations of the Physics of Diffraction, Scattering, and Propagation of Waves as applied to Complex 4-D (Space and Time) physical structures/systems. This endeavor belongs to the field of Computational Mathematical Physics and Engineering.
One of the fundamental and key problems of wave theory is the analytical description of the diffraction by edged obstacles. Exact formulations for interesting complex 4-D physical structures do not exist today. The joint application of the solved "canonical problems", the high-frequency theory of diffraction, and the principle of locality has been and is used today. Key to this approach is that the resulting diffracted/scattered fields/waves can be added together at any given location. Depending on the structure of the 4-D object, this approach is not valid. And these asymptotic methods and their corresponding results can not be accurately verified since the true results can not be obtained analytically.
As a result, this problem is one of the most important problems in science and mathematics for obvious reasons.
As an example, in Communication Systems, this physics is used to describe the phenomenon of Fading in Mobile Digital Communications. Fading is a serious impairment of Reliable Communications.
Other extremely important applications involve devices of Invisibility (stealth) or Detection involving Radar Systems; SuperLens that can operate below the diffraction limit; and Energy (low and high) detectors, converters, and resonators.
ABSTRACT OF THE THESIS:
Performance Evaluation of Communication Systems
using Trellis-Coded Modulation
Darrell Arthur Nolta
Master of Science in Electrical and Computer Engineering
University of California, Irvine, 1998
Professor Harry H. Tan, Chair
This thesis presents the bit error rate (BER) simulation
results of a computer-based study of two problems pertaining
to the application of the Viterbi algorithm (VA) to decoding
convolutional channel encoded source sequences sent over AWGN
memoryless channels. Path memory truncation (PMT) and metric
quantization (MQ) for a maximum likelihood (ML) VA decoder
were studied individually and jointly for an equiprobable
independent and identically distributed (i.i.d.) source for
code, signaling scheme, and Eb/N0 dependencies. Optimal VA
decoding of encoded Markov source sequences was studied using
a maximum a posteriori (MAP) VA joint states (source-code)
trellis decoder. Numerical upper bound on BER for VA
decoding of convolutional encoded i.i.d. or Markov source
sequences sent over AWGN channels are also presented.
The ML VA decoder results suggest that PMT and branch MQ
are dependent individually on the code, signaling scheme, and
Eb/N0. Seven bits of branch MQ is sufficient to achieve an
acceptable BER although one case required ten bits. For the
joint PMT and branch MQ results, VA decoder design cost
measures are used to demonstrate that BER may improve along
with the reduction in overall decoder memory cost using a
trade-off between a reduction of PMT bits versus an increase
of branch MQ bits. The PMT and MQ trade-off should be
evaluated for each application. The results for the MAP VA
source-code trellis decoder demonstrate that it's a feasible
decoder for hidden parameter estimation and that the
performance of this study's codes are robust to changes in
Markov source probability distributions.