阴影-瑞利衰落下的神经网络切换

R. Suleesathira, S. Kunarak
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引用次数: 7

摘要

提出了一种基于阴影-瑞利衰落传播的蜂窝系统切换算法。该算法将时序推进应用于移动定位。所提出的径向基函数网络的输入包括阵列天线上MUSIC方法获得的移动方向、从服务小区和附近小区接收到的移动信号强度(rss)和通信量强度。因此,与迟滞规则相比,我们获得了显着改善的性能。评估是通过测量(1)切换率、阻塞率、丢弃率与流量强度和平均到达时间的关系,以及(2)移动信号强度与系统丢弃呼叫前所需的最小强度值之间的差值与切换次数的关系来完成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural network handoff in shadow-Rayleigh fading
A handoff algorithm in a cellular system under shadow-Rayleigh fading propagation is presented. The algorithm applies the timing advance for mobile positioning. The inputs of the proposed radial-basis function network consist of the mobile direction obtained by the MUSIC method on an array antenna, the received signal strengths (RSSs) of the mobile from the serving cell and from nearby cells and traffic intensities. Consequently, we obtain a significantly improved performance in comparison to the hysteresis rule. The evaluations are done in measurements of (1) handoff rate, blocking rate, dropping rate versus the traffic intensities and mean arrival times and (2) the difference between the mobile signal strength and the required minimum strength value before the system drop the calls versus the number of handoffs.
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