Empowering 6G Positioning and Tracking with Bayesian Neural Networks-Reference-Cited by-同舟云学术

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Empowering 6G Positioning and Tracking with Bayesian Neural Networks

Published:2024-06-09 Issue: Volume:41 Page:2276-2281
ISSN:
Container-title:ICC 2024 - IEEE International Conference on Communications
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Author:

Tedeschini Bernardo Camajori¹,Kwon Girim²,Nicoli Monica³,Win Moe Z.²

Affiliation:

1. Politecnico di Milano,Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB),Milan,Italy,20133

2. Massachusetts Institute of Technology,Wireless Information and Network Sciences Laboratory,Cambridge,MA,USA,02139

3. Politecnico di Milano,Dipartimento di Ingegneria Gestionale (DIG),Milan,Italy,20156

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622691.pdf?arnumber=10622691

Reference31 articles.

1. Study on artificial intelligence (AI)/machine learning (ML) for NR air interface;3rd Generation Partnership Project (3GPP), TR 38.843,2022

2. Summary of RAN rel-18 workshop;document RWS-210659, 3GPP RAN Chair, 3GPP Technical,2021

3. Asynchronous Cell-Free Massive MIMO With Rate-Splitting

4. An Overview of 5G Advanced Evolution in 3GPP Release 18

5. A tutorial on 5G positioning;Italiano;ArXiv,2023

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