蜂窝网络中基于神经网络技术的移动管理位置预测

S. Parija, R. Ranjan, P. K. Sahu
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引用次数: 14

摘要

本文描述了用神经网络技术来解决位置管理问题。基于用户过去的预测信息,设计了多层神经网络模型来预测用户的未来预测。本文提出了一种基于预测的移动终端定位管理方案,使其在不丢失通信质量的前提下保持良好的响应。有各种用于移动用户预测的位置管理方案的方法。根据用户的个性特征,实现基于预测的位置管理。这项工作是纯粹的分析,需要用户过去的运动。移动目标的运动被认为是规则的和均匀的。采用人工神经网络模型进行机动管理,以降低总成本。可以预测单个或多个移动目标。在所有的神经技术中,多层感知器被用于这项工作。这些记录是从过去的运动中收集的,并用于训练网络以预测未来。该预测方法的分析结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Location prediction of mobility management using neural network techniques in cellular network
This work describes the neural network technique to solve location management problem. A multilayer neural model is designed to predict the future prediction of the subscriber based on the past predicted information of the subscriber. In this paper a prediction based location management scheme is proposed for locating a mobile terminal in a communication without losing quality maintain a good response. There are various methods of location management schemes for prediction of the mobile user. Based on individual characteristic of the user, prediction based location management can be implemented. This work is purely analytical which need the past movement of the subscriber. The movement of the mobile target is considered as regular and uniform. An artificial neural network model is used for mobility management to reducing the total cost. Single or multiple mobile targets can be predicted. Among all the neural techniques multilayer perceptron is used for this work. The records is collected from the past movement and is used to train the network for the future prediction. The analytical result of the prediction method is found to be satisfactory.
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