基于记忆遗传算法的车载认知无线电空白空间优化

F. Riaz, Saeed Ahmed, I. Shafi, M. Imran, N. Ratyal, M. Sajid
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引用次数: 9

摘要

近年来,基于认知无线电的通信方法因其固有的优势被引入到车载通信系统中。由于车辆的移动性和不可预测的射频(RF)信道,在IVC中频谱迁移非常频繁。这就需要一种高效的空白空间优化技术来保证频谱管理功能。本文采用改进的遗传算法,引入记忆概念,针对车辆所要求的服务质量(QoS),获得最合适的空白空间。仿真结果表明,该方法在寻找空白区域方面具有较高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
White space optimization using memory enabled genetic algorithm in vehicular cognitive radio
Recently cognitive radio based approaches have been introduced in inter-vehicle communication (IVC) system due to inherent advantages. Spectrum mobility is very frequent in IVC due to the mobility of vehicles and unpredictable radio frequency (RF) channel. This requires an efficient white space optimization technique to ensure spectrum management function. In this paper, a modified genetic algorithm, by introducing memory concept, is employed to obtain the most suitable white space against the quality of service (QoS) requested by vehicles. Simulation results demonstrate that the proposed approach is more efficient in finding white spaces.
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