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Dynamic Resource Allocation Algorithm Based on Queue Management in High-Speed Railway Communication Networks

机译:高速铁路通信网络中队列管理的动态资源分配算法

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With the rapid development of railway transportation, railway communication is particularly important. In addition to meeting the communication needs of train control, it also guarantees the communication quality of passengers on board. In order to solve the problem of low utilization of spectrum resources in the special railway communication network, a spectrum sharing special railway network communication scheme based on the special railway communication network architecture and cognitive radio technology was put forward this paper. Furthermore, in order to improve the fairness of cognitive base station services, we proposed a secondary user queue management strategy based on Kalman Filter Prediction model to realize dynamic resource allocation. On the premise of satisfying the demand of real-time service for queuing delay, the cognitive base station adjusts the service rate of real-time service according to the predicted changes in the queue length, so as to minimize the queuing delay of NRT service. Finally, the simulation results show that the proposed method can reduce the queuing delay of NRT services, effectively improve the fairness of the cognitive base station services, and ensure the efficient utilization of the limited spectrum resources.
机译:随着铁路运输的快速发展,铁路通信尤为重要。除了满足火车控制的沟通需求外,还保证了船上乘客的通信质量。为了解决特殊铁路通信网络中频谱资源利用率低的问题,本文提出了一种基于特殊铁路通信网络架构和认知无线电技术的特殊铁路网络通信方案。此外,为了提高认知基站服务的公平性,我们提出了一种基于卡尔曼滤波预测模型的二次用户队列管理策略,以实现动态资源分配。在满足排队延迟的实时服务需求的前提下,认知基站根据队列长度的预测变化来调整实时服务的服务速率,从而最小化NRT服务的排队延迟。最后,仿真结果表明,该方法可以减少NRT服务的排队延迟,有效地改善认知基站服务的公平性,并确保有限的频谱资源的有效利用率。

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