An ensemble and cost-sensitive learning-based root cause diagnosis scheme for wireless networks with spatially imbalanced user data distribution  

作　　者：Qi WANG Zhiwen PAN Nan LIU 

机构地区：[1]National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China [2]Purple Mountain Laboratories,Nanjing 211100,China

出　　处：《Science China(Information Sciences)》2024年第7期327-328,共2页中国科学（信息科学）（英文版）

基　　金：supported by National Key Research and Development Project(Grant No.2020YFB1806805)and Qualcomm.

摘　　要：Root cause diagnosis,a key component of self-healing,plays a vital role in fault management.The spatially imbalanced network key performance indicators(KPIs)reported by users increase the difficulty of identifying root causes.In^([1,2]),the image inpainting technique is inspired to address issues caused by sparse reports across the coverage area.However,the assumption that reports are sparse throughout entire coverage areas is impractical,as it is rare for reports to be uniformly unavailable.

关 键 词：DIAGNOSIS spatially NETWORKS 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]