Anomaly Detection Algorithms for the Sleeping Cell Detection in LTE Networks
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/7145358/7145573/07145707.pdf?arnumber=7145707
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An Imbalanced Sequence Feature Extraction Approach for the Detection of LTE-R Cells with Degraded Communication Performance;Future Internet;2024-01-16
2. Detecting Sleeping Cells in Cellular Networks Based on One-Class Support Vector Machines Algorithm and Deep Autoencoders;2023 11th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC);2023-12-18
3. Unsupervised Anomaly Detection for Throughput Enhancement in Mobile Networks;2023 International Conference on Computer and Applications (ICCA);2023-11-28
4. A Machine Learning-Driven Analysis of Phantom E911 Calls;Proceedings of the 2022 ACM Workshop on Wireless Security and Machine Learning;2022-05-16
5. Sleeping Cell Detection for Resiliency Enhancements in 5G/B5G Mobile Edge-Cloud Computing Networks;ACM Transactions on Sensor Networks;2022-04-18
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