Propagation Graph Representation Learning and Its Implementation in Direct Path Representation-Reference-Cited by-同舟云学术

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Propagation Graph Representation Learning and Its Implementation in Direct Path Representation

Published:2023-03 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Wireless Communications and Networking Conference (WCNC)
language:
Short-container-title:

Author:

Suto Katsuya¹,Bannai Shinsuke¹,Sato Koya²,Fujii Takeo³

Affiliation:

1. The University of Electro-Communications,Graduate School of Information and Engineering

2. The University of Electro-Communications,Artificial Intelligence eXploration (AIX) Research Center

3. The University of Electro-Communications,Advanced Wireless & Communication Research Center (AWCC)

Funder

National Institute of Information and Communications Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10118584/10118587/10118812.pdf?arnumber=10118812

Reference15 articles.

1. A General Method for Calibrating Stochastic Radio Channel Models with Kernels

2. Calibration of Stochastic Radio Propagation Models Using Machine Learning

3. Modeling of Reverberant Radio Channels Using Propagation Graphs

Cited by 2 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. CNN-Based Path Loss Prediction With Enhanced Satellite Images;IEEE Antennas and Wireless Propagation Letters;2024-01

2. A Single-Layer Periodic Leaky-Wave Antenna With Full-Space Scanning Capability;IEEE Antennas and Wireless Propagation Letters;2024-01

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