Machine Learning Based Dynamic Restoration of Next Generation Wireless Networks-Reference-Cited by-同舟云学术

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Machine Learning Based Dynamic Restoration of Next Generation Wireless Networks

Published:2022-05-16 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Communications Workshops (ICC Workshops)
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Author:

Singh Sukhdeep¹,Saxena Navrati²,Jain Prasham³,Roy Abhishek⁴,Singh Harman Jit⁵,Bhutani Divay⁶,Qureshi Nawab Muhammad Faseeh⁷,Bashir Ali Kashif⁸

Affiliation:

1. Samsung R&D Institute,Bangalore,India

2. San Jose State University,NY,USA

3. University of British Columbia,Canada

4. MediaTek Inc.,CA,USA

5. Simon Fraser University,Canada

6. SigmaQuant Technologies Pvt. Ltd,India

7. Sungkyunkwan University,South Korea

8. Manchester Metropolitan University,UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9813727/9813734/09882152.pdf?arnumber=9882152

Reference15 articles.

1. Self-Healing in Emerging Cellular Networks: Review, Challenges, and Research Directions

2. Context-Aware Self-Healing: User Equipment as the Main Source of Information for Small-Cell Indoor Networks

3. Improving Cell Outage Management Through Data Analysis

4. Self-Healing Framework for Next-Generation Networks through Dimensionality Reduction

5. Smoothing and Differentiation of Data by Simplified Least Squares Procedures.

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