research-article

Mining spectrum usage data: a large-scale spectrum measurement study

Authors:

Shufang LiAuthors Info & Claims

MobiCom '09: Proceedings of the 15th annual international conference on Mobile computing and networking

Pages 13 - 24

https://doi.org/10.1145/1614320.1614323

Published: 20 September 2009 Publication History

Abstract

Dynamic spectrum access has been a subject of extensive research activity in recent years. The increasing volume of literature calls for a deeper understanding of the characteristics of current spectrum utilization. In this paper we present a detailed spectrum measurement study, with data collected in the 20MHz to 3GHz spectrum band and at four locations concurrently in South China. We examine the first and second order statistics of the collected data, including channel occupancy/vacancy statistics, channel utilization within each individual wireless service, and the temporal, spectral, and spatial correlation of these measures. Main findings include that the channel vacancy durations follow an exponential-like distribution, but are not independently distributed over time, and that significant spectral and spatial correlations are found between channels of the same service. We then exploit such spectrum correlation to develop a 2-dimensional frequent pattern mining algorithm that can accurately predict channel availability based on past observations.

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https://doi.org/10.1109/INFOCOM52122.2024.10621271
Li SSun YZhang ZZhang HLin Y(2024)Spectrum Data Graph Structure Learning Based On Dual-View Contrastive Learning For Spectrum Prediction Of ISCC2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)10.1109/ICASSPW62465.2024.10627103(234-238)Online publication date: 14-Apr-2024
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Mining spectrum usage data: a large-scale spectrum measurement study

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cover image ACM Conferences

MobiCom '09: Proceedings of the 15th annual international conference on Mobile computing and networking

September 2009

368 pages

ISBN:9781605587028

DOI:10.1145/1614320

General Chairs:
Kang G. Shin
University of Michigan, USA
,
Yongguang Zhang
Microsoft Research Asia, China
,
Program Chairs:
Rajive Bagrodia
University of California, Los Angeles, USA
,
Ramesh Govindan
University of Southern California, USA

Copyright © 2009 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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Publication History

Published: 20 September 2009

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MobiCom'09

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MobiCom'09: Annual International Conference on Mobile Computing and Networking

September 20 - 25, 2009

Beijing, China

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

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Cited By

Zou RWang W(2024)Effi-Ace: Efficient and Accurate Prediction for High-Resolution Spectrum TenancyIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621271(2199-2208)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621271
Li SSun YZhang ZZhang HLin Y(2024)Spectrum Data Graph Structure Learning Based On Dual-View Contrastive Learning For Spectrum Prediction Of ISCC2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)10.1109/ICASSPW62465.2024.10627103(234-238)Online publication date: 14-Apr-2024
https://doi.org/10.1109/ICASSPW62465.2024.10627103
Li SSun YHan YAlfarraj OTolba ASharma P(2023)A Novel Joint Time-Frequency Spectrum Resources Sustainable Risk Prediction Algorithm Based on TFBRL Network for the Electromagnetic EnvironmentSustainability10.3390/su1506477715:6(4777)Online publication date: 8-Mar-2023
https://doi.org/10.3390/su15064777
Wen XFang SXu ZLiu H(2023)Joint Multidimensional Pattern for Spectrum Prediction Using GNNSensors10.3390/s2321888323:21(8883)Online publication date: 1-Nov-2023
https://doi.org/10.3390/s23218883
Su ZPahlavan KIslam B(2023)An Empirical Study of Interference Features in Licensed and Unlicensed Bands for Intelligent Spectrum Management2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM57956.2023.00040(252-260)Online publication date: Jun-2023
https://doi.org/10.1109/WoWMoM57956.2023.00040
Kim KLiu HWen MTsiftsis TOrlik PPoor H(2023)QR Decomposition-Based Cyclic Prefixed Single-Carrier Transmissions for Cooperative Communications: Concepts and Research LandscapeIEEE Communications Surveys & Tutorials10.1109/COMST.2022.319499725:1(133-155)Online publication date: Sep-2024
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Kandaurova EChirov D(2021)Intelligent Algorithms for Dynamic Spectrum Access a Secondary User in Cognitive Radio Systems2021 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO10.1109/SYNCHROINFO51390.2021.9488377(1-6)Online publication date: 30-Jun-2021
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https://doi.org/10.1109/GLOBECOM46510.2021.9685339
Suganthi NKumar K(2021)Efficient Spectrum Allocation in Wireless Networks Using Channel Aggregation Fragmentation with Reservation ChannelsProceedings of Data Analytics and Management10.1007/978-981-16-6285-0_52(647-663)Online publication date: 22-Nov-2021
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Liang DZhang JJiang SZhang XWu JSun Q(2019)Mobile Traffic Prediction Based on Densely Connected CNN for Cellular Networks in Highway Scenarios2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)10.1109/WCSP.2019.8927980(1-5)Online publication date: Oct-2019
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