Enabling LTE RACH Collision Multiplicity Detection via Machine Learning-Reference-Cited by-同舟云学术

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Enabling LTE RACH Collision Multiplicity Detection via Machine Learning

Published:2019-06 Issue: Volume: Page:
ISSN:
Container-title:2019 International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOPT)
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Author:

Magrin Davide,Pielli Chiara,Stefanovic Cedomir,Zorzi Michele

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9137828/9144084/09144126.pdf?arnumber=9144126

Cited by 8 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. A Novel RACH Scheme for Efficient Access in 5G and Beyond Networks using Hash Function;2022 IEEE Future Networks World Forum (FNWF);2022-10

2. Proactive approach for preamble detection in 5G-NR PRACH using supervised machine learning and ensemble model;Scientific Reports;2022-05-19

3. SIC-RSRA for Massive Machine-to-Machine Communications in 5G Cellular IoT;2022 IEEE Wireless Communications and Networking Conference (WCNC);2022-04-10

4. Early Collision Detection for Massive Random Access in Satellite-Based Internet of Things;IEEE Transactions on Vehicular Technology;2021-05

5. Traffic load access barring scheme for random‐access channel in massive machine‐to‐machine and human‐to‐human devices coexistence in LTE‐A;International Journal of Communication Systems;2021-03-13

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