Research on Optimization of 4G-LTE Wireless Network Cells Anomaly Diagnosis Algorithm based on Multidimensional Time Series Data

Bing Qian, Chong Ma, Tong Zhang

Abstract

With the continuous increase of network terminal equipment, the operation scenarios of 4G-LTE wireless networks are becoming more and more complex. The traditional manual method of analysis and screening of network cell equipment can no longer meet the needs of production. Therefore, an efficient wireless network cell abnormality diagnosis algorithm is needed to screen abnormalities of equipment to improve operation and maintenance efficiency. In view of the fact that the existing single-dimensional anomaly diagnosis algorithm cannot achieve fully automated detection and the existing multidimensional anomaly diagnosis algorithm has low detection efficiency on multidimensional time series data, there are a large number of errors and omissions. This paper proposes a multidimensional time series data based on 4G-LTE wireless network cell anomaly diagnosis optimization algorithm uses small-sample supervised algorithms to assist the training of massive-sample unsupervised algorithms, thereby improving the detection performance of unsupervised learning algorithms. This paper verifies the effectiveness of the optimization algorithm through experiments, and has a great improvement in the four commonly used unsupervised algorithms, which can well improve the anomaly detection capabilities of the existing algorithms.

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Paper Citation


in Harvard Style

Qian B., Ma C. and Zhang T. (2021). Research on Optimization of 4G-LTE Wireless Network Cells Anomaly Diagnosis Algorithm based on Multidimensional Time Series Data. In Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-504-3, pages 48-57. DOI: 10.5220/0010434000480057


in Bibtex Style

@conference{iotbds21,
author={Bing Qian and Chong Ma and Tong Zhang},
title={Research on Optimization of 4G-LTE Wireless Network Cells Anomaly Diagnosis Algorithm based on Multidimensional Time Series Data},
booktitle={Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2021},
pages={48-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010434000480057},
isbn={978-989-758-504-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Research on Optimization of 4G-LTE Wireless Network Cells Anomaly Diagnosis Algorithm based on Multidimensional Time Series Data
SN - 978-989-758-504-3
AU - Qian B.
AU - Ma C.
AU - Zhang T.
PY - 2021
SP - 48
EP - 57
DO - 10.5220/0010434000480057