Transfer Learning to adapt 5G AI-based Fingerprint Localization across Environments-Reference-Cited by-同舟云学术

Transfer Learning to adapt 5G AI-based Fingerprint Localization across Environments

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
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Author:

Stahlke Maximilian¹,Feigl Tobias¹,Garcia Mario H. Castaneda²,Stirling-Gallacher Richard A.²,Seitz Jochen¹,Mutschler Christopher¹

Affiliation:

1. Fraunhofer Institute for Integrated Circuits IIS,Fraunhofer IIS,Division Precise Positioning and Analytics Department,Nürnberg,Germany

2. Huawei Technologies Duesseldorf GmbH,Munich Research Center,Munich,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9860273/9860350/09860906.pdf?arnumber=9860906

Reference16 articles.

1. On Deep Learning-Based Massive MIMO Indoor User Localization

2. Transfer learning for convolutional indoor positioning systems;klus;International Conference on Indoor Positioning and Indoor Navigation (IPIN2010),2022

3. Towards Practical Indoor Positioning Based on Massive MIMO Systems

4. QuaDRiGa: A 3-D Multi-Cell Channel Model With Time Evolution for Enabling Virtual Field Trials

5. Study on channel model for frequencies from 0.5 to 100 GHz;3GPP Tech Rep TR 38 901,2020

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