Intelligent Network Operation and Maintenance Based on Deep Learning Technology
Artificial Intelligence is booming nowadays and has developed tremendous effect in many areas. For Telecommunication, due to the growing network complexity and business diversity, it has been a challenge for operation and maintenance (O&M) of a wirele
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Abstract. Artificial Intelligence is booming nowadays and has developed tremendous effect in many areas. For Telecommunication, due to the growing network complexity and business diversity, it has been a challenge for operation and maintenance (O&M) of a wireless network. This paper analyzes the requirement for intelligent network O&M, sorts out the selection of artificial intelligence (AI) algorithm, and discusses the application scenarios of relevant algorithms in the field of network O&M. Based on 4 cases of intelligent application, this paper reveals how efficiency and quality of network O&M will be improved by AI technology. Keywords: Artificial intelligence (AI) Network operation and maintenance (O&M) Deep learning Network intelligence
1 Introduction Network quality is the lifeline of telecommunication enterprises. Because the network structure of China Mobile is complicated, it is challenging for network O&M to overcome the difficulties, understaffing, and process differences. At present, network maintenance and support are still following traditional patterns, where malfunction handling is passive. With the evolution of AI and deep learning technology, the massive application of cloud computing and GPU, the development of the Internet of Things (IoT), the enrichment of big data and its maturing processing technology [1], AI has exceeded human in many areas [2]. The combination of AI and industries has accelerated the industrial transformation, which means intelligent recognition and data analysis could partially or even wholly substitute for human work. How to use AI technology to promote the intelligence of the telecommunication industry itself is exceptionally urgent, directly affecting the implementation quality of national and enterprise strategies [3]. Based on the perspective of network O&M in the telecommunication area, this paper studies network intelligent O&M technology, replacing passive handling with active precautions, aiming at the front-line O&M problems. In this way, labor-intensive
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Q. Liu et al. (Eds.): CENet 2020, AISC 1274, pp. 200–207, 2021. https://doi.org/10.1007/978-981-15-8462-6_23
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O&M will be substituted, which leads to O&M methods innovation, efficiency improvement and better resource utilization.
2 Requirement Analysis and Technology Selection for Intelligent Network O&M More than 300 kinds of AI algorithms, among which over 40 are based on neural networks. The requirement of the AI algorithm for Intelligent Network O&M can be concluded as follows. First, the algorithms should be applied for modeling and prediction using critical data of network malfunction, performance, and power environment [4]. Meanwhile, they should be able to cover the deep mining, learning, and decision task based on the network O&M experiences, cases and handling orders. Furthermore, they should be able to achieve dimension reduction of
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