NDLI: Spectrum prediction and channel selection for sensing-based spectrum sharing scheme using online learning techniques

Content Provider	IEEE Xplore Digital Library
Author	Zhao Zhang Kaiqing Zhang Feifei Gao Shun Zhang
Copyright Year	2015
Description	Author affiliation: Tsinghua Nat. Lab. for Inf. Sci. & Technol., Beijing, China (Zhao Zhang; Kaiqing Zhang; Feifei Gao) \|\| State Key Lab. of Integrated Service Networks, Xidian Univ., Xi'an, China (Shun Zhang)
Abstract	The cognitive radio technology allows secondary user (SU) to share the licensed spectrum by adapting its transmission power in a sensing-based spectrum sharing manner. Reliable spectrum prediction and channel selection could alleviate the processing delays and enhance the spectrum utilization. In this paper, we propose a new strategy for spectrum prediction and channel selection using online machine learning techniques, which consists of three stages: 1) SU utilizes online learning techniques for the regression of received transmit power on different licenced frequency bands; 2) SU predicts the probability of each primary user's status (busy/idle) based on the power regression results; 3) SU optimizes channel selection in terms of expected ergodic capacities from the prediction outcomes. The proposed strategy can not only save time and energy, but also enhance the throughput of SU. The performance of the proposed strategy is evaluated through extensive simulations.
Starting Page	355
Ending Page	359
File Size	176786
Page Count	5
File Format	PDF
e-ISBN	9781467367820
DOI	10.1109/PIMRC.2015.7343323
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensors History Support vector machines Hidden Markov models Optimization Predictive models Land mobile radio
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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