Improving mmWave backhaul reliability: A machine-learning based approach-Reference-Cited by-同舟云学术

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Improving mmWave backhaul reliability: A machine-learning based approach

Published:2023-03 Issue: Volume:140 Page:103050
ISSN:1570-8705
Container-title:Ad Hoc Networks
language:en
Short-container-title:Ad Hoc Networks

Author:

Ferreira Tânia^ORCID,Figueiredo Alexandre,Raposo Duarte,Luís Miguel,Rito Pedro,Sargento Susana

Funder

Fundação para a Ciência e a Tecnologia

European Regional Development Fund

Programa Operacional Regional do Centro

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference33 articles.

1. Association, blockage, and handoffs in IEEE 802.11ad-based 60-GHz picocells - A closer look;Joshi;IEEE Syst. J.,2020

2. Millimeter-wave wireless LAN and its extension toward 5G heterogeneous networks;Sakaguchi;IEICE Trans. Commun.,2015

3. Millimeter-wave gigabit broadband evolution toward 5G: fixed access and backhaul;Pi;IEEE Commun. Mag.,2016

4. Meshed backhauling of small cells using IEEE 802.11ad at 60GHz;Legg,2018

5. EdgeHaul millimeter wave small cell backhaul system,2015

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. Experimental mmWave WiGig-based backhaul network dataset;Data in Brief;2024-02

2. A conformable artificial neural network model to improve the void fraction prediction in helical heat exchangers;International Communications in Heat and Mass Transfer;2023-11

3. A Flexible mmWave Layer 2 Protocol Implementation for Integrated Access and Backhaul Architecture;IEEE Access;2023

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