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The Learning and Prediction of Application-Level Traffic Data in Cellular Networks

  • Published:2017-06 Issue:6 Volume:16 Page:3899-3912
  • ISSN:1536-1276
  • Container-title:IEEE Transactions on Wireless Communications
  • language:
  • Short-container-title:IEEE Trans. Wireless Commun.

Author:

Li RongpengORCID,Zhao Zhifeng,Zheng JianchaoORCID,Mei Chengli,Cai Yueming,Zhang Honggang

Funder

Program for Zhejiang Leading Team of Science and Technology Innovation

Zhejiang Provincial Technology Plan of China

National Postdoctoral Program for Innovative Talents of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

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1. Cellular Data Analysis using Machine Learning for Crowd Gathering Prediction;International Journal of Information Technology;2024-07-19

2. TRACTOR: Traffic Analysis and Classification Tool for Open RAN;ICC 2024 - IEEE International Conference on Communications;2024-06-09

3. Traffic Prediction Based Energy Efficient Transfer for Point-to-Point Wireless Communications;2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE);2024-05-10

4. CLPREM: A real-time traffic prediction method for 5G mobile network;PLOS ONE;2024-04-01

5. Traffic prediction for 5G: A deep learning approach based on lightweight hybrid attention networks;Digital Signal Processing;2024-03
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