TUNE: Transfer Learning in Unseen Environments for V2X mmWave Beam Selection
Author:
Affiliation:
1. Institute for the Wireless Internet of Things, Northeastern University,Boston,MA,USA,02115
Funder
US National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10278505/10278554/10279177.pdf?arnumber=10279177
Reference20 articles.
1. 3D Scene-Based Beam Selection for mmWave Communications
2. LIDAR and Position-Aided mmWave Beam Selection With Non-Local CNNs and Curriculum Training
3. Optimized Transfer Learning For Wireless Channel Selection;askarizadeh;2021 IEEE Global Communications Conference (GLOBECOM),2021
4. Deep Transfer Learning for Location-Aware Millimeter Wave Beam Selection
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1. Multiverse at the Edge: Interacting Real World and Digital Twins for Wireless Beamforming;IEEE/ACM Transactions on Networking;2024-08
2. Position Aware 60 GHz mmWave Beamforming for V2V Communications Utilizing Deep Learning;ICC 2024 - IEEE International Conference on Communications;2024-06-09
3. AI‐EDGE: An NSF AI institute for future edge networks and distributed intelligence;AI Magazine;2024-02-10
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