各种窗口函数下广义分布的 CM-3 场景通道模型

Shekhar Singh, S. P. Singh, L. M
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引用次数: 0

摘要

就基础研究和技术发展水平而言,无线体域网(WBAN)是一种成熟的无线系统范例。然而,与其他无线系统一样,WBAN 的信道建模也是最具挑战性的研究领域之一。此外,文献表明,基于纳米天线定位的信道模型-3(称为 CM-3 方案)是 WBAN 最有用的部署方案之一。此外,在 WBAN 的 CM-3 方案中起重要作用的到达时间和到达次数是使用泊松分布建模的。 然而,在泊松分布中,方差和均值相等,成功概率固定不变。因此,由于参数有限,基于泊松分布的信道模型的通用性受到了限制。另一方面,带有额外参数的负二项分布(NB)是一种更通用的分布。因此,本稿件采用负二项分布来呈现 CM-3 场景下更通用的信道模型。此外,还分析了泊松分布和负二项分布下不同窗口技术(如巴特利特窗口和高斯窗口)对信道模型的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Channel Model for CM-3 Scenario Over Generalized Distribution Under Various Window Functions
In terms of fundamental research and technology development level, Wireless Body Area Network (WBAN) is a well-established paradigm of wireless system. However, like any wireless system, channel modeling of WBAN is one of the most challenging research eras. Also, literature suggests Channel Model-3, termed as CM-3 scenario based on the positioning of the Nano antenna, is one of the most useful deployment scenarios of WBAN. Further, arrival time and the number of arrivals, which plays an important role in the CM-3 scenario of WBAN, are modeled using the Poisson distribution.  However, in Poisson distribution the variance and mean are equal and the probability of success is kept fixed. Hence, the versatility of the channel model based Poisson distribution is limited due to limited parameters. On the other hand, Negative Binomial (NB) distribution with extra parameters is a more general distribution. Therefore, this manuscript employs Negative Binomial distribution to present a more general channel model under the CM-3 scenario. In addition, effects of different windowing techniques, such as Bartlett and Gaussian window, on the channel model are analyzed under both, Poisson distribution and Negative Binomial distributions.
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