research-article

CSpy: finding the best quality channel without probing

Authors:

Bozidar Radunovic,

Kyu-Han KimAuthors Info & Claims

MobiCom '13: Proceedings of the 19th annual international conference on Mobile computing & networking

Pages 267 - 278

https://doi.org/10.1145/2500423.2500452

Published: 30 September 2013 Publication History

Abstract

Wireless performance depends directly on the quality of the channel. A wireless transmitter can improve its performance by estimating and transmitting on only the strongest channel, which can be of significantly higher quality than a weak channel (yielding up to 100% rate improvement). It is considered impossible to predict the quality of the unseen channels. Thus, the only way to identify the strongest channel is by probing each channel individually, incurring large over- heads. The key contribution of this paper is a discovery of previously unobserved properties of the wireless channel that makes it possible to predict the the strongest of a set of channels from the measurements collected only on a single channel. We confirm the properties through measurements and present a theoretical analysis that explains their nature. Our proposed system, CSpy, utilizes these observations to predict the strongest channel. CSpy is the first to reliably estimate the strongest channel by utilizing channel responses extracted from off-the-shelf wireless chipsets, without probing any additional channels. By tracking the strongest channel, CSpy improves performance by up to 100% in comparison to channel agnostic schemes.

References

[1]

B. Radunovic et al. Dynamic channel, rate selection and scheduling for white spaces. In ACM CONEXT, 2011.

Digital Library

[2]

Jeongkeun Lee et al. Understanding the effectiveness of a co-located wireless channel monitoring system. In IEEE ICC, 2010.

[3]

Anand Subramanian et al. Understanding channel and interface heterogeneity in multi-channel multi-radio wireless mesh networks. PAM, 2009.

Digital Library

[4]

M. Mishra et al. How much white space is there? University of California, Berkeley, Tech. Rep. UCB/EECS-2009--3, 2009.

[5]

P. Chaporkar et al. Scheduling with limited information in wireless systems. In ACM MobiHoc, 2009.

Digital Library

[6]

A. Sabharwal et al. Opportunistic spectral usage: Bounds and a multi-band csma/ca protocol. IEEE ToN, 2007.

Digital Library

[7]

D. Tse and P. Viswanath. Fundamentals of Wireless Communication. Cambridge University Press, 2005.

Digital Library

[8]

S. Sen et al. Spot localization using phy layer information. In MobiSys, 2012.

Digital Library

[9]

A. Saleh et al. A statistical model for indoor multipath propagation. IEEE Journal on Selected Areas in Communications, 1987.

Digital Library

[10]

R. Murty et al. Senseless: A database-driven white spaces network. IEEE Transactions on Mobile Computing, 2012.

Digital Library

[11]

H. Zheng et al. Device-centric spectrum management. In IEEE DySPAN, 2005.

[12]

Q. Zhao et al. Decentralized cognitive mac for opportunistic spectrum access in ad hoc networks: A pomdp framework. IEEE Journal on Selected Areas in Communications, 2007.

Digital Library

[13]

N. Ahmed and S. Keshav. SMARTA: a self-managing architecture for thin access points. In CoNext, 2006.

Digital Library

[14]

D. Halperin et al. Predictable 802.11 packet delivery from wireless channel measurements. In ACM SIGCOMM, 2010.

Digital Library

[15]

M. Vutukuru et al. Cross-layer wireless bit rate adaptation. In ACM SIGCOMM, 2009.

Digital Library

[16]

S. Sen et al. Accurate: Constellation based rate estimation in wireless networks. In USENIX NSDI, 2010.

Digital Library

[17]

R. Chandra. A case for adapting channel width in wireless networks. In ACM SIGCOMM, 2008.

Digital Library

[18]

WIFI Aliance. Spectrum sharing in the 5 ghz band-dfs best practices. Spectrum and Regulatory Committee, 2007.

[19]

E.H. Ong et al. Ieee 802.11 ac: Enhancements for very high throughput wlans. In IEEE PIMRC 2011.

[20]

D. Halperin et al. Tool release: gathering 802.11 n traces with channel state information. ACM SIGCOMM CCR, 2011.

Digital Library

[21]

S. Ghassemzadeh et al. Measurement and modeling of an ultra-wide bandwidth indoor channel. IEEE Transactions on Communications, 2004.

[22]

I. Akyildiz et al. Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Computer Networks, 2006.

Digital Library

[23]

S. Huang et al. Optimal sensing-transmission structure for dynamic spectrum access. In IEEE INFOCOM 2009.

[24]

H. Kim et al. In-band spectrum sensing in cognitive radio networks: energy detection or feature detection? In ACM MobiCom, 2008.

Digital Library

[25]

N. Chang et al. Optimal channel probing and transmission scheduling for opportunistic access. In MobiCom'07.

Digital Library

[26]

S. Yoon et al. Quicksense: Fast and energy-efficient channel sensing for dynamic spectrum access networks.

[27]

N. Jain et al. A multichannel csma mac protocol with receiver-based channel selection for multihop wireless networks. In IEEE ICCN, 2001.

[28]

Jungmin So et al. Multi-channel mac for ad hoc networks: handling multi-channel hidden terminals using a single transceiver. In ACM MobiHoc, 2004.

Digital Library

[29]

P. Bahl et al. Ssch: slotted seeded channel hopping for capacity improvement in ieee 802.11 ad-hoc wireless networks. In ACM MobiCom, 2004.

Digital Library

[30]

K. Ramachandran et al. Interference-aware channel assignment in multi-radio wireless mesh networks. In IEEE INFOCOM, 2006.

[31]

E. Rozner et al. Traffic-aware channel assignment in enterprise wireless lans. In IEEE ICNP, 2007.

[32]

T. Moscibroda et al. Load-aware spectrum distribution in wireless lans. In IEEE ICNP, 2008.

Digital Library

[33]

S. Rayanchu et al. Fluid: Improving throughputs in enterprise wireless lans through flexible channelization. ACM MobiCom, 2011.

Digital Library

[34]

H. Rahul et al. Learning to share: narrowband-friendly wideband networks. ACM SIGCOMM, 2008.

Digital Library

[35]

Lei Yang et al. Supporting demanding wireless applications with frequency-agile radios. In USENIX NSDI, 2010.

Digital Library

[36]

Riccardo Crepaldi et al. CSI-SF: Estimating wireless channel state using csi sampling & fusion. In Infocom, 2012.

[37]

P. Chaporkar et al. Optimal joint probing and transmission strategy for maximizing throughput in wireless systems. IEEE Journal on Selected Areas in Communications, 2008.

Digital Library

[38]

A. Schulman et al. Bartendr: a practical approach to energy-aware cellular data scheduling. In ACM Mobicom, 2010.

Digital Library

[39]

E. Chai et al. Building efficient spectrum-agile devices for dummies. In ACM MobiCom, 2012.

Digital Library

[40]

K. Chintalapudi et al. Wifi-nc: Wifi over narrow channels. In USENIX NSDI, 2012.

Digital Library

[41]

Junxing Zhang et al. Advancing wireless link signatures for location distinction. In MobiCom. ACM, 2008.

Digital Library

[42]

A. Anandkumar et al. Opportunistic spectrum access with multiple users: learning under competition. In IEEE INFOCOM, 2010.

Digital Library

[43]

G. Kasbekar et al. Opportunistic medium access in multi-channel wireless systems: A learning approach. In Allerton. IEEE, 2010.

Cited By

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
Sur SNelakuditi S(2022)A Case for Line-Of-Sight Blockage Detection as a Primitive in Millimeter-Wave Networks2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)10.1109/MASS56207.2022.00084(564-569)Online publication date: Oct-2022
https://doi.org/10.1109/MASS56207.2022.00084
Chen ZZhang XWang SXu YXiong JWang X(2021)Enabling Practical Large-Scale MIMO in WLANs With Hybrid BeamformingIEEE/ACM Transactions on Networking10.1109/TNET.2021.307316029:4(1605-1619)Online publication date: Aug-2021
https://doi.org/10.1109/TNET.2021.3073160
Show More Cited By

Index Terms

CSpy: finding the best quality channel without probing
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

Recommendations

A carrier-independent non-data-aided real-time SNR estimator for M-PSK and D-MPSK suitable for FPGAs and ASICs

We present a channel signal-to-noise ratio (SNR) estimator for M-ary phase shift keying (M-PSK) and differential M-PSK. The estimator is non data aided and is shown to have the following advantages: 1) It does not require prior carrier synchronization; ...
Pilot-aided chip-interleaved DS-CDMA transmission over time-varying channels

Time-varying multipath fading associated with the wireless link limits the capacity of a wireless system. In order to adapt to this adverse radio environment efficiently, we investigate the use of a pilot-aided fade-resistant transmission scheme for the ...
Finite-SNR outage analysis for MIMO channels with imperfect channel state information

In this paper, a point-to-point multiple-input multiple-output (MIMO) channel with imperfect channel state information (CSI) at the receiver and no CSI at the transmitter is considered. Using Monte Carlo simulations, we compute the optimum number of ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

MobiCom '13: Proceedings of the 19th annual international conference on Mobile computing & networking

September 2013

504 pages

ISBN:9781450319997

DOI:10.1145/2500423

General Chair:
Sumi Helal
University of Florida, USA
,
Program Chairs:
Ranveer Chandra
Microsoft, USA
,
Robin Kravets
University of Illinois, Urbana-Champaign, USA

Copyright © 2013 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]

Sponsors

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 September 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

MobiCom'13

Sponsor:

SIGMOBILE

MobiCom'13: The 19th Annual International Conference on Mobile Computing and Networking

September 30 - October 4, 2013

Florida, Miami, USA

Acceptance Rates

MobiCom '13 Paper Acceptance Rate 28 of 207 submissions, 14%;

Overall Acceptance Rate 440 of 2,972 submissions, 15%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

22
Total Citations
View Citations
589
Total Downloads

Downloads (Last 12 months)8
Downloads (Last 6 weeks)2

Reflects downloads up to 16 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

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
Sur SNelakuditi S(2022)A Case for Line-Of-Sight Blockage Detection as a Primitive in Millimeter-Wave Networks2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)10.1109/MASS56207.2022.00084(564-569)Online publication date: Oct-2022
https://doi.org/10.1109/MASS56207.2022.00084
Chen ZZhang XWang SXu YXiong JWang X(2021)Enabling Practical Large-Scale MIMO in WLANs With Hybrid BeamformingIEEE/ACM Transactions on Networking10.1109/TNET.2021.307316029:4(1605-1619)Online publication date: Aug-2021
https://doi.org/10.1109/TNET.2021.3073160
Gadre ANarayanan RLuong ARowe AIannucci BKumar SBhagwan RPorter G(2020)Frequency configuration for low-power wide-area networks in a heartbeatProceedings of the 17th Usenix Conference on Networked Systems Design and Implementation10.5555/3388242.3388267(339-352)Online publication date: 25-Feb-2020
https://dl.acm.org/doi/10.5555/3388242.3388267
Fulara HSingh GJaisinghani DMaity MChakraborty TNaik V(2019)Use of Machine Learning to Detect Causes of Unnecessary Active Scanning in WiFi Networks2019 IEEE 20th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)10.1109/WoWMoM.2019.8793010(1-9)Online publication date: Jun-2019
https://doi.org/10.1109/WoWMoM.2019.8793010
Chowdhery AJamieson K(2018)Aerial Channel Prediction and User Scheduling in Mobile Drone HotspotsIEEE/ACM Transactions on Networking10.1109/TNET.2018.287828726:6(2679-2692)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1109/TNET.2018.2878287
Sun HFang ZLiu QLu ZZhu T(2017)Enabling LTE and WiFi Coexisting in 5 GHz for Efficient Spectrum UtilizationJournal of Computer Networks and Communications10.1155/2017/51561642017(1)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1155/2017/5156164
Sur SPefkianakis IZhang XKim KVan der Merwe KGreenstein BSrinivasan K(2017)WiFi-Assisted 60 GHz Wireless NetworksProceedings of the 23rd Annual International Conference on Mobile Computing and Networking10.1145/3117811.3117817(28-41)Online publication date: 4-Oct-2017
https://dl.acm.org/doi/10.1145/3117811.3117817
Wang WChen YWang ZZhang JWu KZhang Q(2017)Wideband Spectrum Adaptation Without CoordinationIEEE Transactions on Mobile Computing10.1109/TMC.2016.253822516:1(243-256)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1109/TMC.2016.2538225
Jaisinghani DNaik VKaul SRoy S(2017)Sniffer-based inference of the causes of active scanning in WiFi networks2017 Twenty-third National Conference on Communications (NCC)10.1109/NCC.2017.8077054(1-6)Online publication date: Mar-2017
https://doi.org/10.1109/NCC.2017.8077054
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten