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Genetic algorithm optimisation methods applied to the indoor optical wireless communications channel

机译:遗传算法优化方法应用于室内光无线通信信道

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摘要

This thesis details an investigation into the application of genetic algorithms to indoor optical wireless communication systems. The principle aims are to show how it is possible for a genetic algorithm to control the received power distribution within multiple dynamic environments, such that a single receiver design can be employed lowering system costs. This kind of approach is not typical within the research currently being undertaken, where normally, the emphasis on system performance has always been linked with improvements to the receiver design. Within this thesis, a custom built simulator has been developed with the ability to determine the channel characteristics at all locations with the system deployment environment, for multiple configurations including user movement and user alignment variability. Based on these results an investigation began into the structure of the genetic algorithm, testing 192 different ones in total. After evaluation of each one of the algorithms and their performance merits, 2 genetic algorithms remained and are proposed for use. These 2 algorithms were shown capable of reducing the receiver power deviation by up to 26%, and forming, whilst the user perturbs the channel, through movement and variable alignment, a consistent power distribution to within 12% of the optimised case. The final part of the work, extends the use of the genetic algorithm to not only try to optimise the received power deviation, but also the received signal to noise ratio deviation. It was shown that the genetic algorithm is capable of reducing the deviation by around 12% in an empty environment and maintain this optimised case to within 10% when the user perturbs the channel.
机译:本文详细研究了遗传算法在室内光无线通信系统中的应用。该原理的目的是显示遗传算法如何控制多个动态环境中的接收功率分布,从而可以采用单个接收器设计来降低系统成本。这种方法在当前正在进行的研究中并不常见,在正常情况下,通常将对系统性能的重视与对接收机设计的改进联系在一起。在本论文中,已经开发了定制的模拟器,该模拟器具有在系统部署环境下针对所有配置(包括用户移动和用户对齐可变性)确定所有位置的信道特性的能力。根据这些结果,开始研究遗传算法的结构,总共测试了192种不同的算法。在评估了每种算法及其性能优劣之后,剩下了2种遗传算法,并建议使用。显示的这两种算法能够将接收器的功率偏差降低多达26%,并在用户通过移动和变量对准扰动信道的同时,将功率分布保持在优化情况的12%以内。工作的最后一部分扩展了遗传算法的使用范围,不仅尝试优化接收功率偏差,而且还尝试优化接收信噪比偏差。结果表明,遗传算法能够在空旷的环境中将偏差减少约12%,并在用户干扰信道时将这种优化情况保持在10%以内。

著录项

  • 作者

    Higgins Matthew D;

  • 作者单位
  • 年度 2009
  • 总页数
  • 原文格式 PDF
  • 正文语种 English
  • 中图分类

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