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A Hybrid Neighbor Optimization Algorithm for SON based on Network Topology, Handover Counters and RF Measurements

机译:基于网络拓扑,切换计数器和RF测量的儿子混合邻居优化算法

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With the increasing complexity of current wireless networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbor Cell List (NCL) for radio network cells. An algorithm composed by three decision criteria was developed: geographic localization and orientation, according network topology, Radio Frequency (RF) measurements collected by drive-tests or traces and Performance Management (PM) counters from Handover (HO) statistics. The first decision, proposes a new NCL taking into account the Base Station (BS) location and interference tiers, based on the quadrant method. The last two decision criteria consider signal strength and interference level measurements and HO statistics in a time period, respectively. They also define a priority to each cell and added, kept or removed neighbor relation, based on user defined constraints. The algorithms were developed and implemented over new radio network optimization professional tool. Several case studies were produced using real data from a mobile operator.
机译:随着当前无线网络的复杂性越来越大,它变得明显需要自组织网络(儿子),这旨在自动化大多数相关的无线电规划和优化任务。在儿子内,本文旨在优化无线电网络单元的邻居单元格列表(NCL)。开发了一种由三个决定标准组成的算法:地理位置和方向,根据网络拓扑,通过驱动测试或痕迹和性能管理(PM)计数器收集的射频(RF)测量从切换(HO)统计信息。第一个决定,基于象限方法考虑到基站(BS)位置和干扰层,提出了新的NCL。最后两个决策标准分别考虑分别在时间段中考虑信号强度和干扰水平测量和HO统计。它们还根据用户定义的约束来定义每个小区的优先级并添加,保存或删除邻居关系。通过新的无线电网络优化专业工具开发和实施该算法。使用来自移动运营商的真实数据产生了几种案例研究。

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