Improving The Minstrel Rate Adaptation Algorithm using Shallow Neural Networks in IEEE 802.11ah-Reference-Cited by-同舟云学术

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Improving The Minstrel Rate Adaptation Algorithm using Shallow Neural Networks in IEEE 802.11ah

Published:2022-04-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Wireless Communications and Networking Conference (WCNC)
language:
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Author:

Onasis Vincent¹,Kosasih Alva¹,Gu Yifan¹,Hardjawana Wibowo¹,Qu Xinwei¹,Vucetic Branka¹,Chikkam Kishore²

Affiliation:

1. The University of Sydney,Centre of Excellence in Telecommunications,Sydney,Australia

2. Morse Micro,Sydney,Australia

Funder

Australian Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9771381/9771540/09771795.pdf?arnumber=9771795

Cited by 3 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. Demo: B.A.T.M.A.N. Mesh Routing on Ultra Low-Power IEEE 802.11 Modules;2024 IEEE 49th Conference on Local Computer Networks (LCN);2024-10-08

2. Rate Adaptation Algorithm with LSTM in IEEE 802.11ac;2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring);2023-06

3. FTMRate: Collision-Immune Distance-based Data Rate Selection for IEEE 802.11 Networks;2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM);2023-06

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