计算机科学 ›› 2020, Vol. 47 ›› Issue (12): 273-278.doi: 10.11896/jsjkx.190900199
樊英, 张达敏, 陈忠云, 王依柔, 徐航, 王栎桥
FAN Ying, ZHANG Da-min, CHEN Zhong-yun, WANG Yi-rou, XU Hang, WANG Li-qiao
摘要: 车载网络(Vehicle Ad Hoc Networks)是一种新型的智能网络它通过智能地接入网络实现人与车、车与车、车与路边基础设施之间的互联通信增强车辆行驶过程中的安全预测报警功能满足用户对车辆多媒体接入的需求提升车辆用户体验.针对认知车载网络(Cognitive Vehicular AdHoc NetworksCR-VANET)频谱分配效率低的问题文中提出一种基于改进乌鸦算法的频谱分配方案.首先对乌鸦算法的两个位置更新参数引用曲线自适应参数进行改进以更好地平衡集约化与多元化;其次采用收敛因子策略解决乌鸦算法收敛速度慢和不稳定的问题;然后对随机数混沌化以提高搜索的遍历性和收敛速度;最后以车载网络吞吐量和认知车载用户之间的接入公平性作为参考评价指标将改进后的乌鸦算法应用于认知车载网络的频谱分配中.实验采用改进的方案、遗传算法(Genetic AlgorithmGA)、粒子群算法(Particle Swarm Optimization AlgorithmPSO)分配方案进行比较.仿真结果表明改进的分配方案具有较好的性能.
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