Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.595750
Title: Performance prediction, parameter selection, and channel adaptation in the line-of-sight outdoors optical wireless channels using intelligent systems
Author: El Yakzan, Adnan
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2013
Availability of Full Text:
Access from EThOS:
Access from Institution:
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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.595750  DOI: Not available
Keywords: QA Mathematics ; TK Electrical engineering. Electronics Nuclear engineering
Share: