research-article

The impact of channel bonding on 802.11n network management

Authors:

Eduard Garcia-Villegas,

Elizabeth Belding,

Kevin AlmerothAuthors Info & Claims

CoNEXT '11: Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies

Article No.: 11, Pages 1 - 12

https://doi.org/10.1145/2079296.2079307

Published: 06 December 2011 Publication History

Abstract

The IEEE 802.11n standard allows wireless devices to operate on 40MHz-width channels by doubling their channel width from standard 20MHz channels, a concept called channel bonding. Increasing channel width should increase bandwidth, but it comes at the cost of decreased transmission range and greater susceptibility to interference. However, with the incorporation of MIMO (Multiple-Input Multiple-Output) technology in 802.11n, devices can now exploit the increased transmission rates from wider channels at a reduced sacrifice to signal quality and range. The goal of our work is to understand the characteristics of channel bonding in 802.11n networks and the factors that influence that behavior to ultimately be able to predict behavior so that network performance is maximized. We discuss the impact of channel bonding choices as well as the effects of both co-channel and adjacent channel interference on network performance. We discover that intelligent channel bonding decisions rely not only on a link's signal quality, but also on the strength of neighboring links and their physical rates.

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Cited By

Ghoshal MKrishna SGringoli FWidmer JKoutsonikolas D(2024)A First Look at 160 MHz WiFi 6/6E in Action: Performance and Interference Characterization2024 IFIP Networking Conference (IFIP Networking)10.23919/IFIPNetworking62109.2024.10619856(489-495)Online publication date: 3-Jun-2024
https://doi.org/10.23919/IFIPNetworking62109.2024.10619856
Roy SFunabiki NRahman MWu BKuribayashi MKao W(2023)A Study of the Active Access-Point Configuration Algorithm under Channel Bonding to Dual IEEE 802.11n and 11ac Interfaces in an Elastic WLAN System for IoT ApplicationsSignals10.3390/signals40200154:2(274-296)Online publication date: 3-Apr-2023
https://doi.org/10.3390/signals4020015
Huang YChin K(2023)A Three-Tier Deep Learning-Based Channel Access Method for WiFi NetworksIEEE Transactions on Machine Learning in Communications and Networking10.1109/TMLCN.2023.32880901(90-106)Online publication date: 2023
https://doi.org/10.1109/TMLCN.2023.3288090
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Published In

cover image ACM Conferences

CoNEXT '11: Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies

December 2011

364 pages

ISBN:9781450310413

DOI:10.1145/2079296

General Chairs:
Kenjiro Cho
IIJ/Keio University, Japan
,
Mark Crovella
Boston University

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCOMM: ACM Special Interest Group on Data Communication

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 December 2011

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National Science Foundation
Spanish Government

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Co-NEXT '11

Sponsor:

SIGCOMM

Co-NEXT '11: Conference on emerging Networking Experiments and Technologies

December 6 - 9, 2011

Tokyo, Japan

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Cited By

Ghoshal MKrishna SGringoli FWidmer JKoutsonikolas D(2024)A First Look at 160 MHz WiFi 6/6E in Action: Performance and Interference Characterization2024 IFIP Networking Conference (IFIP Networking)10.23919/IFIPNetworking62109.2024.10619856(489-495)Online publication date: 3-Jun-2024
https://doi.org/10.23919/IFIPNetworking62109.2024.10619856
Roy SFunabiki NRahman MWu BKuribayashi MKao W(2023)A Study of the Active Access-Point Configuration Algorithm under Channel Bonding to Dual IEEE 802.11n and 11ac Interfaces in an Elastic WLAN System for IoT ApplicationsSignals10.3390/signals40200154:2(274-296)Online publication date: 3-Apr-2023
https://doi.org/10.3390/signals4020015
Huang YChin K(2023)A Three-Tier Deep Learning-Based Channel Access Method for WiFi NetworksIEEE Transactions on Machine Learning in Communications and Networking10.1109/TMLCN.2023.32880901(90-106)Online publication date: 2023
https://doi.org/10.1109/TMLCN.2023.3288090
Kandar DChyne PNath Sur SNandi S(2023)A study on the channel bonding in IoT networks: Requirements, applications, and challengesInternational Journal of Communication Systems10.1002/dac.544336:6Online publication date: 28-Jan-2023
https://doi.org/10.1002/dac.5443
Kanemasa HLi AIto YChauvet NNaruse MHasegawa M(2022)Dynamic channel bonding in WLANs by hierarchical laser chaos decision makerNonlinear Theory and Its Applications, IEICE10.1587/nolta.13.8413:1(84-100)Online publication date: 2022
https://doi.org/10.1587/nolta.13.84
Soto PCamelo MMets KWilhelmi FGóez DFletscher LGaviria NHellinckx PBotero JLatré S(2021)ATARI: A Graph Convolutional Neural Network Approach for Performance Prediction in Next-Generation WLANsSensors10.3390/s2113432121:13(4321)Online publication date: 24-Jun-2021
https://doi.org/10.3390/s21134321
Laghari MShahwani HShah SWagan RRauf ZAli IAlshamrani SFrnda J(2021)Towards Enabling Multihop Wireless Local Area Networks for Disaster CommunicationsWireless Communications & Mobile Computing10.1155/2021/55404802021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/5540480
Barrachina-Munoz SBellalta BKnightly E(2021)Wi-Fi Channel Bonding: An All-Channel System and Experimental Study From Urban Hotspots to a Sold-Out StadiumIEEE/ACM Transactions on Networking10.1109/TNET.2021.307777029:5(2101-2114)Online publication date: Oct-2021
https://doi.org/10.1109/TNET.2021.3077770
Voicu AAgbo PSimic LMahonen PPetrova M(2021)Measurement Study of Dense Networks with Heterogeneous IEEE 802.11ac Wi-Fi Devices2021 IEEE International Conference on Communications Workshops (ICC Workshops)10.1109/ICCWorkshops50388.2021.9473620(1-6)Online publication date: Jun-2021
https://doi.org/10.1109/ICCWorkshops50388.2021.9473620
Stojanova MBegin TBusson A(2021)A Markov model for performance evaluation of channel bonding in IEEE 802.11Ad Hoc Networks10.1016/j.adhoc.2021.102449(102449)Online publication date: Feb-2021
https://doi.org/10.1016/j.adhoc.2021.102449
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