A dynamic affinity propagation clustering algorithm for cell outage detection in self-healing networks

With the rapid development of the mobile wireless system, the operator is experiencing unprecedented challenges on service maintenance and operational expenditure, which drives the demand for realizing automation in current networks. The cell outage detection is considered as an effective way to aut...

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Bibliographic Details
Published in:2013 IEEE Wireless Communications and Networking Conference (WCNC) pp. 2266 - 2270
Main Authors: Yu Ma, Mugen Peng, Wenqian Xue, Xiaodong Ji
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2013
Subjects:
Antennas
Clustering algorithms
Heuristic algorithms
Indexes
Measurement
Monitoring
Wireless communication
ISBN:9781467359382, 1467359386
ISSN:1525-3511
Online Access:Get full text
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Summary:With the rapid development of the mobile wireless system, the operator is experiencing unprecedented challenges on service maintenance and operational expenditure, which drives the demand for realizing automation in current networks. The cell outage detection is considered as an effective way to automatically detect network fault. Our work presents an automated cell outage detection mechanism in which a clustering technique called Dynamic Affinity Propagation (DAP) clustering algorithm is introduced. Performance metrics are collected from the network during its regular operation and then fed into the algorithm to produce optimal clusters for further anomaly detection. The proposed mechanism has been implemented in the LTE-Advanced simulation environment, through which we have successfully detected the configured cell outages and located their specific outage areas.
ISBN:9781467359382
1467359386
ISSN:1525-3511
DOI:10.1109/WCNC.2013.6554913