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Detection of Sleeping Cells in Self-Organizing Cellular Networks: An Adversarial Auto-Encoder Method

  • Published:2021-09 Issue:3 Volume:7 Page:739-751
  • ISSN:2332-7731
  • Container-title:IEEE Transactions on Cognitive Communications and Networking
  • language:
  • Short-container-title:IEEE Trans. Cogn. Commun. Netw.

Author:

Zhang TaoORCID,Zhu KunORCID,Niyato DusitORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture

Cited by 8 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. 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

2. Design and Optimization of RSMA for Coexisting HTC/MTC in 6G and Future Networks;IEEE Transactions on Wireless Communications;2023-12

3. Evolutionary Weighted Broad Learning and Its Application to Fault Diagnosis in Self-Organizing Cellular Networks;IEEE Transactions on Cybernetics;2023-05

4. A Cost-sensitive SVM Based Approach for Root Cause Diagnosis in Wireless Networks;2022 14th International Conference on Wireless Communications and Signal Processing (WCSP);2022-11-01

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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