El. Yakzan, Adnan (2013) Performance prediction, parameter selection, and channel adaptation in the line-of-sight outdoors optical wireless channels using intelligent systems. PhD thesis, University of Warwick.

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Abstract

With the increased usage of optical wireless communication, finding appropriate
parameters for reliable transmission and providing efficient channel performance
have become of challenging interest in research and industry. This has been a strong
motivation to examine and develop methods and techniques to find suitable link
parameters to increase the channel availability. This thesis is mainly concerned with
designing, implementing and adapting intelligent algorithms to solve for parameter
selection, channel prediction, and channel adaptation in dynamic optical wireless
channels. The problem could be solved with other methods such as binary and
sequential search; however, intelligent systems have the ability to find optimal
results with more reliability, time efficiency and increased flexibility. The research
focuses on single and multi-objective selection techniques using application-specific
genetic algorithm (ASGA) in the outdoors line-of-sight (LOS) optical wireless
channel where parameters have different effects on the channel performance and may
affect the behaviour of other channel parameters. The technique is well-established at
pre-installation stages of the channel, and could be also applied at run-time if a
reconfigurable hardware is installed.
An intelligent system, which uses a genetic algorithm predicted and optimized
optical wireless channel in the (LOS) field, is presented. The prediction technique is
proposed to estimate the bit error rate (BER) at the receiver, and suggests appropriate
selection of link parameters. In this research, the work is developed based on on-off
keying (OOK) modulation, and makes use of different weather conditions for
channel modeling. A first attempt is made with a GA-based selection for
transmission wavelengths (700nm to 1600nm), the overall deterministic attenuations being estimated by a visibility model, where the changes in visibility decide about
the wavelength control margin. The research is then extended to consider various
external link parameters scaled by look-up tables that meet the optical wireless
industry. It shows that the transmission power should not always be the only costin
the channel, and there are other parameters worthy of control. Principal Component
Analysis is applied targeting the ASGA selected datasets to extract the contribution
of each parameter to the output, and the implicit relations that exist among data sets
to achieve a certain bit-error-rate. An Artificial Neural Network (ANN) is then
applied to the channel for BER prediction; this may also validate the pre-installation
advice done by PCA. Finally, a two-stage modelling using a neuro-fuzzy hybrid
algorithm used for adapting the channel by monitoring the link range and total
attenuations in the channel.
Through analysing the simulation results using these intelligent systems
algorithms, the thesis aims at providing maximum utilization of channel parameters
for achieving optimum channel performance and increased availability under the
application of various intelligent systems, which demonstrate their efficiency and
effectiveness as compared with other techniques.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QA Mathematics T Technology > TK Electrical engineering. Electronics Nuclear engineering
Library of Congress Subject Headings (LCSH):	Wireless communication systems, Optical communications, Intelligent control systems, Genetic algorithms
Official Date:	August 2013
Institution:	University of Warwick
Theses Department:	School of Engineering
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Green, Roger J.; Hines, Evor, 1957-
Extent:	xxi, 197 leaves : illustrations, charts.
Language:	eng

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