Research And Implement Of Fault Management System For Super Base Station

The super base station is a centralized access network platform consists of four parts,which are global resource control center,centralized multi-mode baseband pool,computing resource pool,high-bandwidth optical transmission networks and distributed remote radio unit.With the rapid development of mobile communication technology,the super base station's node size is gradually enlarged and it's structure becomes more complicated in order to support a large number of new services and new demands,thus increasing the risk of malfunction of the super base station.Once a super base station fails,the normal operation of multiple cells on the same basic equipment will be effected.This thesis focuses on the fault management system of the super base station.The research on fault management will improve the reliability and stability of the network,reduce the probability of failure,and provide a good user experience.Fault management is also economical and can manage a large number of base station equipment at a small cost.However,the fault management of the current super base station has the following difficulties:(1)Fault detection problem: There are many types of data to be detected,which takes a long time.(2)Fault diagnosis: The alarm scale is large,a large number of interference alarms are caused by the communication among the nodes,which increases the difficulty of fault diagnosis.Focusing on the above difficulties,the main work of this thesis are as follows:(1)The fault detection of the existing base station is to detect the abnormality in the network by sending the traffic probe,which increases the system overhead.This thesis proposes a negative selection algorithm,which is less overhead,to implement fault detection.The super base station needs to detect a large amount of data and takes a long time.Therefore,this thesis proposes an improved fault detection model-EFDM based on the principal component analysis method with the characteristics of data set compression,and implement it on the super base station.The experimental results show that EFDM can increase the detection speed and reduce the system overhead with sacrificing less accuracy of detection.(2)The existing fault diagnosis method of the super base station is mainly performed by the administrators,which locate the fault source according to the system alarm.However,the fault cannot be quickly located while facing the large scale alarms.This thesis combines the characteristics of hierarchical clustering analysis and super base station alarm format,and proposes a generalization fault diagnosis mechanism for alarms.Based on the generalized hierarchical structure of the alarm attributes,the mechanism combines and generalizes similar alarms to sort out alarm summaries for a period of time.Experimental results verify that this mechanism can diagnose the source of the fault.(3)Finally,this thesis redesigns the original fault management system,designs a hierarchical and modular fault management system based on fault detection and fault diagnosis,and realizes the functional interface display of the system.