Machine Learning Based NLOS Radio Positioning in Beamforming Networks-Reference-Cited by-同舟云学术

Machine Learning Based NLOS Radio Positioning in Beamforming Networks

Published:2022-07-04 Issue: Volume: Page:
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Container-title:2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)
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Author:

Klus Roman¹,Talvitie Jukka¹,Vinogradova Julia²,Torsner Johan²,Valkama Mikko¹

Affiliation:

1. Tampere University,Faculty of Information Technology and Communication Sciences,Tampere,Finland

2. Ericsson Research,Helsinki,Finland

Funder

Academy of Finland

Publisher

IEEE

Link

Reference16 articles.

2. Stage 2 functional specification of User Equipment (UE) positioning in NG-RAN;Tech Rep 38 305,2021

3. Physical layer measurements;Tech Rep 38 215,2021

5. Wireless InSite - 3D wireless prediction software,0

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4. ML-based Approaches for Wireless NLOS Localization: Input Representations and Uncertainty Estimation;2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (BigDataService);2023-07