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- W3038017140 abstract "Fault diagnosis is an indispensable part of self-organizing networks (SONs), which facilitates a self-healing capability. However, most of the studies concentrate more on algorithm design and numerical simulation without verification on practical platforms. In this paper, a hardware platform based on OpenAirInterface is designed and implemented to address this issue, where an enhanced unsupervised method composed of self-organizing map and hierarchical clustering is deployed for fault diagnosis. Particularly, the platform is capable of delivering performance similar to a real Long-Term Evolution network, making the algorithm verification more convincing. Our results show that the adopted algorithm can diagnose different faults in a near real-time way and results in accuracy of 97.4%." @default.
- W3038017140 created "2020-07-02" @default.
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- W3038017140 date "2020-05-01" @default.
- W3038017140 modified "2023-09-24" @default.
- W3038017140 title "Unsupervised Fault Diagnosis Platform Implementation for Self-Healing in Cellular Networks" @default.
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- W3038017140 doi "https://doi.org/10.1109/ictc49638.2020.9123269" @default.
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