NDLI: Design of experiments based empirical models to support cognitive radio decision making

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2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

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Design of experiments based empirical models to support cognitive radio decision making

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Author index

2013 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications

2011 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications

2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications

Design of experiments based empirical models to support cognitive radio decision making

Content Provider	IEEE Xplore Digital Library
Author	Amanna, A. Ali, D. Gonzalez Fitch, D. Reed, J.H.
Copyright Year	2015
Description	Author affiliation: ANDRO Comput. Solutions, LLC, Rome, NY, USA (Amanna, A.) \|\| Virginia Tech, Blacksburg, VA, USA (Ali, D.; Gonzalez Fitch, D.; Reed, J.H.)
Abstract	Machine learning based link optimization of wireless communications often relies on past experience, accurate estimation of channel conditions, and theoretical performance models. Typically, theoretical models poorly match given situations, past experiences are limited, and spectrum sensing of noise and channel conditions pose many hurdles. Hence, traditional cognitive radio engines based on genetic algorithms and case based reasoning have faltered, especially when facing new environments. Our approach uses efficient experimental designs to generate an empirical performance model as an alternate to theoretical models. The procedure systematically probes the system by setting a unique combination of input parameters and transmitting a data file across the link. Performance metrics, such as packet error rate and throughput, associated with each row of a response surface methodology (RSM) design estimate simple models of performance. Goals of this research include validating accuracy of empirical models based on type and efficiency of experimental design, using empirical models in place of theoretical models during the optimization process, and comparing success of an experimental design driven decision compared to a benchmark genetic algorithm cognitive radio engine. Over-the-air implementation on software defined radios demonstrated the statistical approach performing within 4% of a traditional genetic algorithm cognitive engine even in cases where the statistical fit of the estimation model is poor.
Starting Page	1
Ending Page	7
File Size	376816
Page Count	7
File Format	PDF
e-ISBN	9781467375573
DOI	10.1109/CISDA.2015.7208627
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Charge coupled devices Adaptation models Cognitive Radio Design of Experiments Estimation Interference Central Composite Design Throughput Response Surface Methodology Encoding Box Behnken
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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