Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks-Reference-Cited by-同舟云学术

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Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks

Published:2023-05-28 Issue: Volume: Page:
ISSN:
Container-title:ICC 2023 - IEEE International Conference on Communications
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Author:

Kozlov Igor,Rivkin Dmitriy,Chang Wei-Di,Wu Di,Liu Xue,Dudek Gregory

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10278505/10278554/10278818.pdf?arnumber=10278818

Reference34 articles.

1. Cellular KPI Anomaly Detection with GAN and Time Series Decomposition

2. Interpretable Unsupervised Anomaly Detection For RAN Cell Trace Analysis

3. LSTM Recurrent Neural Network (RNN) for Anomaly Detection in Cellular Mobile Networks

4. Deep RAN: A Scalable Data-driven platform to Detect Anomalies in Live Cellular Network Using Recurrent Convolutional Neural Network

Cited by 1 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. Anomaly Detection for Scalable Task Grouping in Reinforcement Learning-Based RAN Optimization;2024 IEEE International Conference on Communications Workshops (ICC Workshops);2024-06-09

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