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首页> 外文会议>2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications >Analytical framework for access class barring in machine type communication
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Analytical framework for access class barring in machine type communication

机译：机器类型通信中访问类别限制的分析框架

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Access class barring (ACB) is regarded as an efficient and practically implementable method to reduce the traffic overload in cellular networks. In this paper, we present a unified analytical framework to analyze the performance of the fixed ACB scheme for a simple random access procedure (i.e., one-shot transmission model) in machine type communication (MTC) over cellular networks. We derive the exact expressions for the probability of a machine's packet being served by the base station (BS), the average number of machine type devices (MTDs) successfully served by the BS per second and the noncollision slot access probability. We verify the accuracy of the derived expressions by comparison with simulations. Based on the analytical expressions, we then maximize the probability of a MTD's packet being served and obtain the sub-optimal probability factor value for the fixed ACB in closed-form. Our results confirm that, the use of ACB scheme is important for scenarios with high MTD packet arrival rate, which is relevant for massive MTC. The proposed framework allows fine tuning and accurate prediction of the MTC performance with ACB.
机译：接入类别限制（ACB）被认为是减少蜂窝网络中流量过载的一种有效且切实可行的方法。在本文中，我们提出了一个统一的分析框架，用于分析蜂窝网络上机器类型通信（MTC）中的简单随机访问过程（即单次传输模型）的固定ACB方案的性能。我们得出基站（BS）为机器数据包服务的概率，每秒由BS成功服务的机器类型设备（MTD）的平均数量以及非冲突时隙访问概率的精确表达式。通过与仿真比较，我们验证了导出表达式的准确性。然后，基于解析表达式，我们可以最大化服务MTD数据包的概率，并以封闭形式获得固定ACB的次优概率因子值。我们的结果证实，对于高MTD数据包到达率的场景，使用ACB方案非常重要，这与大规模MTC有关。提出的框架允许使用ACB进行MTC性能的微调和准确预测。

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