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Cognitive radio techniques for wide area networks

Authors:

William Krenik,

Anuj BatraAuthors Info & Claims

DAC '05: Proceedings of the 42nd annual Design Automation Conference

Pages 409 - 412

https://doi.org/10.1145/1065579.1065688

Published: 13 June 2005 Publication History

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Abstract

The cellular wireless market has begun the transition to data centric services including high speed internet access, video, high quality audio, and gaming. Communications technology can meet the need for very high data link speeds, and can also improve network throughput, but dramatically more spectrum will be needed to provide ubiquitous wireless data service. Cognitive radio is a new technology that allows spectrum to be dynamically shared between users. It offers the potential to dramatically change the way spectrum is used in systems and to substantially increase the amount of spectrum available for wireless communications. This paper introduces cognitive radio and explains the promise, possible operating modes, and benefits it may offer.

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Federal Communications Commission, "Unlicensed Operation in the TV Broadcast Bands," ET Docket No. 04--186, 2004.

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J. Mitola, III, "Cognitive Radio for Flexible Mobile Multimedia Communications," Mobile Multimedia Communications, 1999. IEEE International Workshop, page 3.

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B. Krenik and C. Panasik, "The Potential for Unlicensed Wide Area Networks," Wireless Advanced Architectures Group, Texas Instruments White Paper, November 2004.

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J. Reed, L. DaSilva, J. Suris, L. Morales, "Potential for Unlicensed Wide Area Networks Using Cognitive Radios and Available Resource Maps," Mobile and Portable Radio Research Group, Bradley Department of Electrical and Computer Engineering, Virginia Tech, White Paper, Feb. 5, 2005.

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Cited By

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Qian JChen YChen C(2018)Energy Consumption Analysis of K Rank Fusion Detection Under Noise UncertaintyProceedings of the 2018 International Conference on Electronics and Electrical Engineering Technology10.1145/3277453.3277487(191-195)Online publication date: 19-Sep-2018
https://dl.acm.org/doi/10.1145/3277453.3277487
Liu XJia MNa ZLu WLi F(2018)Multi-Modal Cooperative Spectrum Sensing Based on Dempster-Shafer Fusion in 5G-Based Cognitive RadioIEEE Access10.1109/ACCESS.2017.27619106(199-208)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2017.2761910
Liu XJia M(2017)Joint optimal fair cooperative spectrum sensing and transmission in cognitive radioPhysical Communication10.1016/j.phycom.2017.08.01525:P2(445-453)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1016/j.phycom.2017.08.015
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Cognitive radio techniques for wide area networks
1. General and reference
  1. Document types
    1. General conference proceedings

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Published In

DAC '05: Proceedings of the 42nd annual Design Automation Conference

June 2005

984 pages

ISBN:1595930582

DOI:10.1145/1065579

General Chair:
William H. Joyner
IBM Corp./SRC
,
Program Chairs:
Grant E. Martin
Tensilica, Inc.
,
Andrew B. Kahng
University of California at San Diego, CA

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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Association for Computing Machinery

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Published: 13 June 2005

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June 13 - 17, 2005

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Qian JChen YChen C(2018)Energy Consumption Analysis of K Rank Fusion Detection Under Noise UncertaintyProceedings of the 2018 International Conference on Electronics and Electrical Engineering Technology10.1145/3277453.3277487(191-195)Online publication date: 19-Sep-2018
https://dl.acm.org/doi/10.1145/3277453.3277487
Liu XJia MNa ZLu WLi F(2018)Multi-Modal Cooperative Spectrum Sensing Based on Dempster-Shafer Fusion in 5G-Based Cognitive RadioIEEE Access10.1109/ACCESS.2017.27619106(199-208)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2017.2761910
Liu XJia M(2017)Joint optimal fair cooperative spectrum sensing and transmission in cognitive radioPhysical Communication10.1016/j.phycom.2017.08.01525:P2(445-453)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1016/j.phycom.2017.08.015
Misra GAgarwal AMisra SAgarwal K(2017)Cognitive Radio: A Technological Review on Technologies, Spectrum Awareness, Channel Awareness, and ChallengesComputational Intelligence in Data Mining10.1007/978-981-10-3874-7_28(299-307)Online publication date: 20-May-2017
https://doi.org/10.1007/978-981-10-3874-7_28
Elshafie HFisal NAbbas MHassan WMohamad HRamli NJayavalan SZubair S(2015)A survey of cognitive radio and TV white spaces in MalaysiaTransactions on Emerging Telecommunications Technologies10.1002/ett.277826:6(975-991)Online publication date: 1-Jun-2015
https://dl.acm.org/doi/10.1002/ett.2778
Galindo-Serrano ASayrac BJemaa SRiihijärvi JMähönen P(2014)Cellular Coverage Optimization: A Radio Environment Map for Minimization of Drive TestsCognitive Communication and Cooperative HetNet Coexistence10.1007/978-3-319-01402-9_10(211-236)Online publication date: 17-Jan-2014
https://doi.org/10.1007/978-3-319-01402-9_10
Liu XZhang CTan X(2014)Double-threshold cooperative detection for cognitive radio based on weighingWireless Communications & Mobile Computing10.1002/wcm.221914:13(1231-1243)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1002/wcm.2219
Liu XTan X(2014)Optimization algorithm of periodical cooperative spectrum sensing in cognitive radioInternational Journal of Communication Systems10.1002/dac.237727:5(705-720)Online publication date: 1-May-2014
https://dl.acm.org/doi/10.1002/dac.2377
Salih SErman MMohammed A(2013)A Novel Spectrum Sensing Scheduling Algorithm for Cognitive Radio NetworksSelf-Organization and Green Applications in Cognitive Radio Networks10.4018/978-1-4666-2812-0.ch007(136-153)Online publication date: 2013
https://doi.org/10.4018/978-1-4666-2812-0.ch007
Sayrac BGalindo‐Serrano AJemaa SRiihijärvi JMähönen P(2013)Bayesian spatial interpolation as an emerging cognitive radio application for coverage analysis in cellular networksTransactions on Emerging Telecommunications Technologies10.1002/ett.272424:7-8(636-648)Online publication date: 31-Oct-2013
https://doi.org/10.1002/ett.2724
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Distributed Shared Spectrum Techniques for Cognitive Wireless Radio Networks

Fully Distributed Cooperative Spectrum Sensing for Cognitive Radio Ad Hoc Networks

Dynamic spectrum leasing in cognitive radio networks via primary-secondary user power control games

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