Traffic prediction scheme for resource assignment of satellite/terrestrial frequency sharing mobile communication system

T. Aman, T. Yamazato, M. Katayama
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引用次数: 4

Abstract

The recent development of large aperture on-board multi-beam antennas enables a small-size, low-powered and cellular phone like hand-held terminal as a satellite earth terminal. A single mobile terminal can communicate to both mobile satellite systems and terrestrial systems depend upon his location, QoS and availability of resources among satellite and terrestrial communication systems. In this paper, we propose a new traffic prediction scheme for the integrated satellite/terrestrial frequency sharing mobile communication system. The system shares a common frequency bandwidth in order to enhance the total capacity by a dynamic bandwidth allocation. A key for this allocation depends on a traffic prediction scheme of a few hundreds of terrestrial cells under a footprint of a satellite with a large aperture onboard multi-beam antennas. We propose three traffic predictors based on neural networks for dynamic resource allocation. The performances of the proposed schemes are evaluated in terms of the Relative Traffic Prediction Error and Maximum Traffic Prediction Error by the computer simulation. For the evaluation, we adopt the actual traffic statistic published by Ministry of Internal Affairs and Communications of Japan with population density of terrestrial cells based on the actual population of Aichi, Japan. As results, average traffic prediction error of less than 0.25 is achieved for the prediction interval of one hour, enough for dynamic resource allocation.
星/地共频移动通信系统资源分配的业务预测方案
近年来大口径机载多波束天线的发展,使小尺寸、低功耗、像蜂窝电话一样的手持终端成为卫星地球终端。单个移动终端可以与移动卫星系统和地面系统通信,这取决于其在卫星和地面通信系统之间的位置、QoS和资源可用性。本文提出了一种新的星地共频移动通信系统话务预测方案。系统共享一个共同的频率带宽,通过动态分配带宽来提高总容量。这种分配的一个关键取决于在带有大口径机载多波束天线的卫星的足迹下几百个地面小区的流量预测方案。我们提出了三种基于神经网络的流量预测方法,用于动态资源分配。通过计算机仿真,从相对流量预测误差和最大流量预测误差两方面对所提方案的性能进行了评价。评估采用日本总务省公布的实际流量统计数据,以日本爱知县实际人口为基础,采用地面小区人口密度。结果表明,在1小时的预测间隔内,平均流量预测误差小于0.25,足以实现资源的动态分配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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