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UTRAN OM Support System with Statistical Fault Identification and Customizable Rule Sets

机译:UTRAN O&M支持统计故障识别和可自定义规则集的系统

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With the proliferation of mobile-network services, mobile networks have become one of the core social infrastructures and are therefore required to operate stably. Conventional mobile-network-management systems can detect and recover from faults according to previously formulated rules. However, such semi-static rules are vulnerable to large variation in quality of networks and to sudden increases in traffic, which are inherent to radio access networks. Maintenance personnel often had to perform case-by-case analyses for the vast numbers of abnormal cases and such analyses and creation of rules may have taken more time when new faults appeared. In addition, providing network elements timely is essential to maintaining network quality but it is becoming more difficult as mobile networks become larger and more complicated. To overcome these problems, we have developed a system that enhances the conventional UMTS Terrestrial Radio Access Network (UTRAN) management system of mobile networks and improves stability during network operation. In this paper, we present main features of the system and its fundamental technologies: fault detection based on statistical reliability, root-cause analysis of the fault, a rule editor easy to create and modify fault-analysis rules for maintenance personnel, and guidance on expansion based on long-term analysis of trends. We tested this system then confirmed it could reduce fault-detection errors in a conventional management system through theoretical calculations and trials in a cellular mobile network.
机译:随着移动网络服务的扩散,移动网络已成为核心社交基础设施之一,因此需要稳定运行。传统的移动网络管理系统可以根据先前制定的规则从故障中检测和恢复。然而,这种半静态规则容易受到网络质量的大变化以及流量突然增加,这是无线电接入网络所固有的。维护人员常常必须对大量异常情况进行逐个案例分析,并且在出现新故障时可能需要更多的时间进行这种分析和规则的创建。此外,提供网络元件对维护网络质量至关重要,但随着移动网络变得更大,更复杂,它变得越来越困难。为了克服这些问题,我们开发了一种系统,该系统增强了移动网络的传统UMTS地面无线电接入网络(UTRAN)管理系统,并在网络操作期间提高了稳定性。在本文中,我们提出了系统的主要特点及其基本技术:基于统计可靠性的故障检测,故障的根本原因分析,规则编辑器易于创建和修改维护人员的故障分析规则,以及指导基于长期分析趋势的扩展。我们测试了该系统,然后通过蜂窝移动网络中的理论计算和试验来证实它可以降低传统管理系统中的故障检测错误。

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