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Pattern Prediction and Passive Bandwidth Management for Hand-over Optimization in QoS Cellular Networks with Vehicular Mobility

机译:具有车辆移动性的QoS蜂窝网络中用于切换优化的模式预测和无源带宽管理

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In wireless networking, the main desire of end-users is to take advantage of satisfactory services, in terms of QoS, especially when they pay for a required need. Many efforts have been made to investigate how the continuity of services can be guaranteed in QoS networks, where users can move from one cell to another one. The introduction of a prediction scheme with passive reservations is the only way to face this issue; however, the deployment of in-advance bandwidth leads the system to waste resources. This work consists of two main integrated contributions: a new pattern prediction scheme based on a distributed set of Markov chains, in order to handle passive reservations, and a statistical bandwidth management algorithm for the reduction of bandwidth wastage. The result of the integration is the Distributed Prediction with Bandwidth Management Algorithm (DPBMA) that is independent from the considered technology and the vehicular environment. Several simulation campaigns were conducted in order to evaluate the effectiveness of the proposed idea. It was also compared with other prediction schemes, in terms of system utilization, accuracy, call dropping, and call blocking probabilities.
机译:在无线网络中,最终用户的主要愿望是利用令人满意的服务(就QoS而言),尤其是当他们为所需的需求付费时。已经进行了许多努力来研究如何在QoS网络中保证服务的连续性,在QoS网络中,用户可以从一个小区移动到另一个小区。引入带有被动保留的预测方案是解决此问题的唯一方法。但是,超前带宽的部署导致系统浪费资源。这项工作由两个主要的综合贡献组成:一种基于马尔可夫链的分布式集合的新模式预测方案(用于处理被动预留),以及一种统计带宽管理算法,用于减少带宽浪费。集成的结果是具有带宽管理算法的分布式预测(DPBMA),该算法独立于所考虑的技术和车辆环境。为了评估所提出的想法的有效性,进行了几次模拟运动。在系统利用率,准确性,呼叫丢失和呼叫阻塞概率方面,还与其他预测方案进行了比较。

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