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首页> 外文期刊>Intelligent Transportation Systems, IEEE Transactions on >Measurement-Based Burst-Error Performance Modeling for Cooperative Intelligent Transport Systems
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Measurement-Based Burst-Error Performance Modeling for Cooperative Intelligent Transport Systems

机译:协作智能运输系统中基于测量的突发错误性能建模

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摘要

Safety applications for cooperative intelligent transport systems are limited in their performance by the latency of the communication more than by the achieved throughput. However, there exist few models at packet level that are able to capture the burstiness of the communication. We therefore introduce a packet error model that considers burst lengths through second-order statistics and mean packet errors. The foundation of our approach is the Gilbert–Elliot model, which is able to model not only the packet error rate, but also the burst durations of the packet errors, which we interpret in a nonstationary fashion. Based on this, we formulate maximum likelihood expressions for the time variant model fits, and then proceed to fit the parameters to extensive recorded measurements. We consider the fading statistics of the measured channel and the signal-to-noise ratio and present how they influence the channel burstiness. Our analysis demonstrates that the communication shows strong bursts at packet level, proving the demand for such models. The approach we demonstrate here remains of low computational complexity, allowing future employment in large-scale simulations.
机译:协作智能运输系统的安全应用程序的性能受到通信延迟的限制,而不是获得的吞吐量所限制。但是,在数据包级别上很少有能够捕获通信突发性的模型。因此,我们引入了一种包错误模型,该模型通过二阶统计量和平均包错误来考虑突发长度。我们方法的基础是吉尔伯特-埃利奥特(Gilbert-Elliot)模型,该模型不仅可以对数据包错误率进行建模,而且还可以对数据包错误的突发持续时间进行建模,我们以一种非平稳的方式对其进行解释。基于此,我们为时变模型拟合制定了最大似然表达式,然后继续将参数拟合为大量记录的测量值。我们考虑测量信道的衰落统计和信噪比,并介绍它们如何影响信道突发性。我们的分析表明,通信在数据包级别显示出很强的突发性,证明了对此类模型的需求。我们在这里演示的方法仍然具有较低的计算复杂度,从而允许将来在大规模仿真中使用。

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