FadeNet: Deep Learning-Based mm-Wave Large-Scale Channel Fading Prediction and its Applications

FadeNet: Deep Learning-Based mm-Wave Large-Scale Channel Fading Prediction and its Applications

Accurate prediction of the large-scale channel fading is fundamental to planning and optimization in 5G millimeter-wave cellular networks. The current prediction methods, which are either too computationally expensive or inaccurate, are unsuitable for city-scale cell planning and optimization. This...

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Bibliographic Details
Main Authors: Vishnu V. Ratnam, Hao Chen, Sameer Pawar, Bingwen Zhang, Charlie Jianzhong Zhang, Young-Jin Kim, Soonyoung Lee, Minsung Cho, Sung-Rok Yoon
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Cell planning
channel modeling
convolutional networks
deep learning
large scale fading
mm-Wave
Online Access:https://ieeexplore.ieee.org/document/9311729/

Internet

https://ieeexplore.ieee.org/document/9311729/

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