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RSS Characterization in Wireless Heterogeneous Network

机译:无线异构网络中的RSS表征

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Increasing number of connected devices and the volume of data generated by these devices pushing current generation of cellular network to their limits. Cross layer designs (CLD) are recommended for the designing a better performing network applications. 5G standard for next generation network includes the provisions for CLD within the standard itself to cater resource demand from such devices. 5G along with its predecessors is going to coexist providing a heterogeneous connectivity for a user. Irrespective of generation, radio access network (RAN) still remained a bottleneck and drastically affects the performance. Signal strength is a metric for RAN which is used in several decisions and is an important parameter for CLD. In simulation of CLD signal strength is modeled using established path loss and fading models wherein distance is the only variable, similarly, noise is modeled as a Gaussian distribution. Thus, with static user received signal strength (RSS) appears as Gaussian distribution but in reality the RSS is non-uniform with sharp peaks and long tail. Simulation with incorrect models result into solutions that lag far apart in performance than the actual outcomes, hence, correct modeling of RSS is a decisive factor. In this empirical study data collected for RSS using NeSen App by colocated multiple smartphones. This study proves that RSS recorded follows t-Distribution with mean between [-71, -77]dbm, standard deviation between [3.75, 4.85] and degree of freedom in range of [6.8, 10.5].
机译:越来越多的连接设备和由这些设备产生的数据量将当前产生的蜂窝网络推向其限制。建议设计横梁设计(CLD),以设计更好的执行网络应用程序。下一代网络的5G标准包括标准本身内的CLD的规定,以满足这些设备的资源需求。 5G随着其前辈们将共存为用户提供异构连接。无论生成如何,无线电接入网络(RAN)仍然仍然是瓶颈,大大影响性能。信号强度是用于若干决定的RAN的度量,并且是CLD的重要参数。在CLD信号强度的仿真中使用建立的路径损耗和衰落模型建模,其中距离是唯一可变的,类似地,噪声被建模为高斯分布。因此,利用静态用户接收的信号强度(RSS)出现为高斯分布,但实际上,RSS是不均匀的,具有尖锐的峰和长尾。模拟模型的模拟结果进入解决方案,这些解决方案滞后于性能远远超过实际结果,因此,RSS的正确建模是一个决定性因素。在此经验研究中,使用NESEN应用通过CONOCOCATED多个智能手机收集数据。本研究证明,记录的RSS在[3.75,4.85]和[6.8,10.5]范围内的[3.75,4.85]和自由度之间的标准偏差之间的T分布遵循T分布。

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