对于5g v2x通信的Q学习和模糊逻辑多层多访问边缘聚类,5g v2x通信的多层边缘聚类
Sangeetha Alagumani1, Uma Maheswari Natarajan2
1Department of Information Technology, PSNA college of Engineering and Technology, Dindigul, Tamil Nadu, India.
概括
这项研究引入了5G蜂网络的新多层集群协议,以改善密集的车辆通信中的数据分布. 它使用模糊逻辑和Q学习来增强车辆到一切服务并减少网络拥堵.
科学领域:
- 电信工程 电信工程 电信工程
- 计算机网络 计算机网络
- 人工智能的人工智能
背景情况:
- 第五代 (5G) 网络对于增加数据需求和客户增长至关重要,支持诸如物联网等多种应用.
- 现有的IEEE 802.11p标准在密集的车辆环境中面临限制,包括有限的覆盖范围,拥堵和连接问题,阻碍了有效的数据分配.
- 蜂车到一切 (C-V2X) 通信对于克服现代,密集网络中的带宽限制至关重要.
研究的目的:
- 解决5G中的密集车辆网络中高效数据分布的挑战.
- 为增强C-V2X通信提出一种新的多层多访问边缘集群协议.
- 通过减少车辆拥堵和适应动态网络条件来提高网络性能.
主要方法:
- 实施车辆对车辆 (V2V),车辆对基础设施 (V2I) 和车辆对行人 (V2P) 服务.
- 应用多层多通道边缘聚类来减少车辆缩.
- 利用模糊逻辑和Q学习来实现智能多跳路线选择系统.
主要成果:
- 拟议的集群协议有效地减少了在密集网络场景中的车辆拥堵.
- 整合Q学习允许集群头节点的动态调整,增强适应性.
- 在不同的带宽和车辆密度条件下,可以实现更好的数据分布和网络效率.
结论:
- 开发的协议为5G车载网络中高效的数据分配提供了强大的解决方案.
- 智能路由和自适应集群显著提高网络性能和可靠性.
- 这种方法提高了C-V2X服务的功能,为未来的智能运输系统铺平了道路.
相关概念视频
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