C-GRBFnet: A Physics-Inspired Generative Deep Neural Network for Channel Representation and Prediction

Author:

Xiao Zhuoran1ORCID,Zhang Zhaoyang1ORCID,Huang Chongwen1,Chen Xiaoming1ORCID,Zhong Caijun1ORCID,Debbah Merouane2

Affiliation:

1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

2. Technology Innovation Institute, Abu Dhabi, United Arab Emirates

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Reference44 articles.

1. DeepMIMO: A generic deep learning dataset for millimeter wave and massive MIMO applications;alkhateeb;arXiv 1902 06435,2019

2. Prediction of radio wave propagation in four blocks of New York City using 3D ray tracing

3. Learning Implicit Fields for Generative Shape Modeling

4. NeRF: Representing scenes as neural radiance fields for view synthesis;mildenhall;Vision Computer,2020

5. Fourier features let networks learn high frequency functions in low dimensional domains;tancik;arXiv 2006 10739,2020

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