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A Reinforcement Sensor Embedded Vertical Handoff Controller for Vehicular Heterogeneous Wireless Networks

机译:车载异构无线网络的增强传感器嵌入式垂直切换控制器

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Vehicular communication platforms that provide real-time access to wireless networks have drawn more and more attention in recent years. IEEE 802.11p is the main radio access technology that supports communication for high mobility terminals, however, due to its limited coverage, IEEE 802.11p is usually deployed by coupling with cellular networks to achieve seamless mobility. In a heterogeneous cellular/802.11p network, vehicular communication is characterized by its short time span in association with a wireless local area network (WLAN). Moreover, for the media access control (MAC) scheme used for WLAN, the network throughput dramatically decreases with increasing user quantity. In response to these compelling problems, we propose a reinforcement sensor (RFS) embedded vertical handoff control strategy to support mobility management. The RFS has online learning capability and can provide optimal handoff decisions in an adaptive fashion without prior knowledge. The algorithm integrates considerations including vehicular mobility, traffic load, handoff latency, and network status. Simulation results verify that the proposed algorithm can adaptively adjust the handoff strategy, allowing users to stay connected to the best network. Furthermore, the algorithm can ensure that RSUs are adequate, thereby guaranteeing a high quality user experience.
机译:近年来,提供​​对无线网络的实时访问的车辆通信平台越来越受到关注。 IEEE 802.11p是支持高移动性终端通信的主要无线电接入技术,但是,由于覆盖范围有限,通常通过与蜂窝网络耦合来部署IEEE 802.11p,以实现无缝移动性。在异构蜂窝/802.11p网络中,车辆通信的特点是与无线局域网(WLAN)关联的时间跨度短。此外,对于用于WLAN的媒体访问控制(MAC)方案,网络吞吐量随着用户数量的增加而急剧下降。针对这些迫在眉睫的问题,我们提出了一种增强传感器(RFS)嵌入式垂直切换控制策略,以支持移动性管理。 RFS具有在线学习功能,可以在没有先验知识的情况下以自适应方式提供最佳切换决策。该算法整合了各种考虑因素,包括车辆移动性,流量负载,切换延迟和网络状态。仿真结果验证了该算法可以自适应地调整切换策略,使用户保持与最佳网络的连接。此外,该算法可以确保RSU足够,从而保证了高质量的用户体验。

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