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Performance analysis of the contention access period in the slotted IEEE 802.15.4 for wireless body sensor networks

机译：用于无线人体传感器网络的时隙IEEE 802.15.4中争用接入时段的性能分析

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Wireless body sensor networks (WBSN) are a particular type of wireless sensor networks (WSN) that are becoming an important topic in the technological research community. Advances in the reduction of the power consumption and cost of these networks have led to solutions mature enough for their use in a broad range of applications such as sportsman or health monitoring. The development of those applications has been stimulated by the nalization of the IEEE 802.15.4 standard, which de nes the medium access control (MAC) and physical layer (PHY) for low-rate wireless personal area networks (LR-WPAN). One of the MAC schemes proposed is slotted Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). This project analyzes the performance of this MAC, based on a state-of-the-art analytical model for a star topology, which captures the behavior of the MAC using two Markov chain models; the per-node state model and the channel state model. More importantly, we extend this model to include acknowledged tra c. The impact of including acknowledgments is evaluated in terms of energy consumption, throughput and latency. The performance predicted by the analytical model has been extensively veri ed with simulations using the ns-2 IEEE 802.15.4 contributed module. Throughput, energy consumption and latency analysis is performed. Additionally, we have simulated a statistical channel model describing the radio channel behavior around the human body to calculate the packet error rate (PER) found in a typical WBSN under the aforementioned standard. This PER is then introduced into our analytical model.
机译：无线人体传感器网络（WBSN）是无线传感器网络（WSN）的一种特殊类型，正在成为技术研究界的重要主题。这些网络在降低功耗和成本方面取得的进步已导致解决方案足够成熟，可以在运动员或健康监测等广泛的应用中使用。 IEEE 802.15.4标准的诞生刺激了这些应用的发展，该标准定义了低速无线个人局域网（LR-WPAN）的媒体访问控制（MAC）和物理层（PHY）。提出的MAC方案之一是带时隙避免冲突的载波侦听多路访问（CSMA / CA）。该项目基于星型拓扑的最新分析模型来分析该MAC的性能，该模型使用两个马尔可夫链模型捕获MAC的行为。每个节点状态模型和通道状态模型。更重要的是，我们将此模型扩展为包含公认的交易记录。包含确认的影响是根据能耗，吞吐量和延迟进行评估的。使用ns-2 IEEE 802.15.4贡献模块的仿真已广泛验证了分析模型预测的性能。进行吞吐量，能耗和等待时间分析。此外，我们模拟了统计信道模型，该模型描述了人体周围的无线电信道行为，以计算在上述标准下的典型WBSN中发现的分组错误率（PER）。然后将这个PER引入我们的分析模型。

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