Title :
Field-of-View Optimization of FSO Receiver Using Real-coded Genetic Algorithm
Author :
Chen, Chunyi ; Yang, Huamin ; Fan, Jingtao ; Ding, Ying ; Han, Cheng
Author_Institution :
Sch. of Comput. Sci. & Technol., Changchun Univ. of Sci. & Technol., Changchun, China
Abstract :
The optimal receiver field-of-view (FOV) of a free-space optical (FSO) link through clouds strongly depends on the multiple-scattering characteristics of the channel. Due to the complexity of the multiple-scattering model of clouds, it is a non-trivial task to obtain the optimal FOV. In this paper, the real-coded genetic algorithm (GA) is applied to determine the optimal FOV, which is defined as: with this FOV, the received optical signal reaches the highest level and the channel bandwidth is not below the specific value. The objective function for the fitness evaluation of individuals is built based on both the received-optical-energy model and the channel-bandwidth model. The penalty-function method is used to obtain an unconstrained optimization. Elitism is also employed to increase the performance of GA. Finally, the optimal FOVs are obtained by using the real-coded GA.
Keywords :
broadband networks; channel coding; genetic algorithms; optical links; optical receivers; FSO receiver; channel bandwidth; field-of-view optimization; fitness evaluation; free-space optical link; multiple-scattering characteristics; nontrivial task; penalty-function method; real-coded genetic algorithm; received-optical-energy model; Bandwidth; Clouds; Gallium; Optical fiber communication; Optical receivers; Optimization; cloud; field of view; free-space optical link; genetic algorithm; optimization;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.216