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Bringing Mobility-Awareness to WLANs using PHY Layer Information

Authors:

Dimitrios KoutsonikolasAuthors Info & Claims

CoNEXT '14: Proceedings of the 10th ACM International on Conference on emerging Networking Experiments and Technologies

Pages 53 - 66

https://doi.org/10.1145/2674005.2675017

Published: 02 December 2014 Publication History

Abstract

With the proliferation of smartphones and tablets, mobile devices are soon becoming a preferred medium of Internet access in Wireless LANs (WLANs). Due to their smaller form factor, these truly mobile devices allow the users to access the wireless networks while undergoing different types of mobility, posing new challenges to wireless protocols. Current history-based protocols that maximize performance in static settings do not work well in mobile settings where wireless conditions change rapidly. Thus, today's WLANs need to be able to determine the type of the client's mobility and employ appropriate strategies in order to sustain high performance. While previous work tried to detect mobility using hints from sensors available in today's mobile devices, in this work, we demonstrate how different mobility modes can be distinguished by using physical layer information -- Channel State Information (CSI) and Time-of-Flight (ToF) -- available at commodity APs, with no modifications on the client side. In addition, we demonstrate how fine-grained mobility determination can be exploited to improve performance of client roaming, rate control, frame aggregation, and MIMO beamforming. Our testbed experiments show that our mobility classification algorithm achieves more than 92% accuracy in a variety of scenarios, and the combined throughput gain of all four mobility-aware protocols over their mobility-oblivious counterparts can be more than 100%.

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Cited By

Gong WWang HLi SChen S(2024)GLAC: High-Precision Tracking of Mobile Objects With COTS RFID SystemsIEEE/ACM Transactions on Networking10.1109/TNET.2023.334895032:3(2331-2343)Online publication date: Jun-2024
https://doi.org/10.1109/TNET.2023.3348950
Chen SGong WLiu JWang ZZhao J(2022)Interference-Aware Mobile Backscatter Communication: A PHY-Assisted Rate Adaptive ApproachIEEE Transactions on Mobile Computing10.1109/TMC.2022.3214533(1-12)Online publication date: 2022
https://doi.org/10.1109/TMC.2022.3214533
Su STan WZhu XListon RWildfeuer HAazhang B(2021)Motion-Aware Optimizations for Downlink MU-MIMO in 802.11ax NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2021.311759618:4(4088-4102)Online publication date: Dec-2021
https://doi.org/10.1109/TNSM.2021.3117596
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Index Terms

Bringing Mobility-Awareness to WLANs using PHY Layer Information
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

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Published In

cover image ACM Conferences

CoNEXT '14: Proceedings of the 10th ACM International on Conference on emerging Networking Experiments and Technologies

December 2014

438 pages

ISBN:9781450332798

DOI:10.1145/2674005

General Chairs:
Aruna Seneviratne
NICTA/UNSW, Australia
,
Christophe Diot
Technicolor, France
,
Jim Kurose
Umass, USA
,
Program Chairs:
Augustin Chaintreau
Columbia University, USA
,
Luigi Rizzo
University of Pisa, Italy

Copyright © 2014 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

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Published: 02 December 2014

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CoNEXT '14

Sponsor:

SIGCOMM

CoNEXT '14: Conference on emerging Networking Experiments and Technologies

December 2 - 5, 2014

Sydney, Australia

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CoNEXT '14 Paper Acceptance Rate 27 of 133 submissions, 20%;

Overall Acceptance Rate 198 of 789 submissions, 25%

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Cited By

Gong WWang HLi SChen S(2024)GLAC: High-Precision Tracking of Mobile Objects With COTS RFID SystemsIEEE/ACM Transactions on Networking10.1109/TNET.2023.334895032:3(2331-2343)Online publication date: Jun-2024
https://doi.org/10.1109/TNET.2023.3348950
Chen SGong WLiu JWang ZZhao J(2022)Interference-Aware Mobile Backscatter Communication: A PHY-Assisted Rate Adaptive ApproachIEEE Transactions on Mobile Computing10.1109/TMC.2022.3214533(1-12)Online publication date: 2022
https://doi.org/10.1109/TMC.2022.3214533
Su STan WZhu XListon RWildfeuer HAazhang B(2021)Motion-Aware Optimizations for Downlink MU-MIMO in 802.11ax NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2021.311759618:4(4088-4102)Online publication date: Dec-2021
https://doi.org/10.1109/TNSM.2021.3117596
Su STan WZhu XListon RAazhang B(2021)Data-Driven Mode and Group Selection for Downlink MU-MIMO With Implementation in Commodity 802.11ac NetworkIEEE Transactions on Communications10.1109/TCOMM.2021.304913069:3(1620-1634)Online publication date: Mar-2021
https://doi.org/10.1109/TCOMM.2021.3049130
Wang HChen SGong W(2021)Mobility Improves Accuracy: Precise Robot Manipulation with COTS RFID Systems2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)10.1109/PERCOM50583.2021.9439133(1-10)Online publication date: 22-Mar-2021
https://doi.org/10.1109/PERCOM50583.2021.9439133
Aggarwal SGhoshal MBanerjee PKoutsonikolas DWidmer J(2021)802.11ad in Smartphones: Energy Efficiency, Spatial Reuse, and Impact on ApplicationsIEEE INFOCOM 2021 - IEEE Conference on Computer Communications10.1109/INFOCOM42981.2021.9488763(1-10)Online publication date: 10-May-2021
https://doi.org/10.1109/INFOCOM42981.2021.9488763
Aggarwal SGhoshal MBanerjee PKoutsonikolas D(2021)An experimental study of the performance of IEEE 802.11ad in smartphonesComputer Communications10.1016/j.comcom.2021.01.006169(220-231)Online publication date: Mar-2021
https://doi.org/10.1016/j.comcom.2021.01.006
Aggarwal SSardesai USinha VKoutsonikolas DAguilar Igartua MBellavista PLoureiro AGiannelli C(2020)An Experimental Study of Rate and Beam Adaptation in 60 GHz WLANsProceedings of the 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems10.1145/3416010.3423219(171-180)Online publication date: 16-Nov-2020
https://dl.acm.org/doi/10.1145/3416010.3423219
He SWang WYang HCao YJiang TZhang Q(2020)State-Aware Rate Adaptation for UAVs by Incorporating On-Board SensorsIEEE Transactions on Vehicular Technology10.1109/TVT.2019.295028569:1(488-496)Online publication date: Jan-2020
https://doi.org/10.1109/TVT.2019.2950285
Aggarwal SThirumurugan AKoutsonikolas DSimić LPathak P(2019)A First Look at 802.11ad Performance on a SmartphoneProceedings of the 3rd ACM Workshop on Millimeter-wave Networks and Sensing Systems10.1145/3349624.3356766(13-18)Online publication date: 7-Oct-2019
https://dl.acm.org/doi/10.1145/3349624.3356766
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