首页> 外文OA文献 >A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network
【2h】

A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network

机译:使用亲和传播算法和人工神经网络的毫微微小区网络的一种新颖的用户分类方法

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle. The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60% less training samples reducing the training time up to 50%. This procedure makes the femtocell more effective for closed access operation.
机译:提出了一种基于人工神经网络(ANN)和亲和力传播(AP)算法的基于用户分类技术。所提出的算法专为封闭访问毫微微小区网络而设计。 ANN用于用户分类过程,AP算法用于优化ANN培训过程。 AP选择最佳的培训样本,以实现更快的ANN培训周期。通过使用多元素毫微微小区装置中的接收信号强度的差异来区分用户。先前开发的指示微带天线用于配置毫微微小区设备。仿真结果表明,对于特定的房屋模式,没有AP算法的分类技术需要5个室内用户和10个室外用户以获得无错误的操作。在与ANN集成AP算法的同时,系统需要60%的训练样本,将培训时间降低至50%。该程序使毫微微小区对闭合访问操作更有效。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号