Thesis Structure

The thesis mainly consists of three parts: Introduction to optical wireless communication and its fundamentals, the use of several intelligent systems to tackle the problem in the outdoors LOS optical wireless channels, and the last part manipulates results, evaluates the achievements, and sheds light on future research areas.

The first chapter is the introduction, mainly providing the background about optical wireless communications. It states the motivation around the project, and suggests the main problem to be solved throughout the thesis.

The second chapter concentrates on indoor and outdoor infrared communications, the design technology, service disruption on the physical layer, and optical security. The problem is stated, and the research is narrowed with a set of contributions discussed.

Chapter three consists of a literature review and discusses the recent contributions related to the optical wireless communication. It stresses the achievements of intelligent systems for power and SNR optimizations using genetic algorithms, artificial neural network, fuzzy logic, and hybrid algorithms.

The fourth chapter discusses the methodology that will be used for the subsequent chapters. This chapter includes the first attempt of using a genetic algorithm for a transmission wavelength selection in NIR systems. The selection targets several weather conditions based on the international code of visibility.

Chapter five shows the model of the optical wireless channel considering atmospheric attenuations (deterministic) and turbulence (scintillation) conditions. It discusses the parameters and selection functions that a genetic algorithm makes use of, and then simulates an original coded program that utilizes the concept of

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evolutionary algorithms. It shows the fitness function, and various simulation results covering overall link characteristics. An application-specific genetic algorithm is presented, but, prior to this process, the generated code is compared against the complexity of the MATLAB GA tool box to assure its reliability in solving the designated problem.

Chapter six shows a multivariate data analysis of the application-specific generated data sets studied using principal component analysis (PCA) to find correlations among parameters and map them to the real channel.

The seventh chapter discusses a fuzzy-neuro approach. An Artificial Neural Network (ANN) is firstly used for BER prediction to validate the results obtained by the previous methods and could also be applied to estimate the BER of optical wireless channel model deploying different cross-sections of transceivers; and then a hybrid model using adaptive neuro-fuzzy inference system (ANFIS) is modelled and used for channel adaptation by monitoring the link range and total attenuations in the channel.

Chapter eight concludes the research, and sheds light on possible future work. Important results and methodology obtained from previous chapters are summarized and the possibilities for future directions are discussed.

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References

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[1.25] Hakki H. Refai, J.J.SlussJr, and Hazem H. Refai, “The use of free-space optical links for CATV applications,” accepted to SPIE Opto Ireland, Dublin, Ireland, April 4-5, 2005.

[1.26] Hakki H. Refai, J. J. SlussJr, and Hazem H. Refai, “Interconnection of IS-95 CDMA microcells using free-space optical links,” in proc. of the 1st IEEE and IFIP International Conference on Wireless and Optical Communications Networks (WOCN 2004), Muscat, Oman, June 7-10, pp. 78-81, 2004.

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