Techniques for Performance Improvement of Cognitive Radio (PhD Thesis) (Record no. 361435)

MARC details
000 -LEADER
fixed length control field 03168nam a2200193Ia 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 150518s2015||||xx |||||||||||||| ||eng||
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
ISSN-L phd
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 621.384378242
Item number SHA
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Shaikh, Aamir Zeb
Relator term author
245 #0 - TITLE STATEMENT
Title Techniques for Performance Improvement of Cognitive Radio (PhD Thesis)
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Karachi :
Name of publisher, distributor, etc. NED University of Engineering and Technology Department of Telecommunications Engineering
Date of publication, distribution, etc. 2015
300 ## - PHYSICAL DESCRIPTION
Extent X, 89 p.
Other physical details : ill
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes Bibliographical References
520 ## - SUMMARY, ETC.
Summary, etc. Abstract :<br/><br/>Cognitive Radio is a promising technology to resolve spectrum scarcity issue by exploiting RF spectrum in opportunistic fashion. Spectrum Sensing is a key enabling step towards successful implementation of this emerging technology. Sensing refers to the detection of unused spectrum spaces also known as "white spaces". This dissertation proposes, investigates and analyses several algorithms for spectrum sensing cognitive radio applications. Receiver Operating Characteristic (ROC) is compared among different proposed algorithms. It is one of the most important measures to classify detectors. In the first part of the dissertation, ROC is analysed for multiple-antenna assisted spectrum sensing radios under shadowing and is derived using linear test statistic. Furthermore, a highly useful cluster-driven architecture for spectrum sensing is also proposed and analysed that improves detection probability by exploiting cooperation among cognitive radios using hard decision combining strategy. Hard decision combination strategy computes the detection probability by combining one bit decisions among various cooperative cognitive radios. Detection probability is achieved 80% at PFA rate of 10% for a single user, whereas using hard decision combing approach the same detection probability is achieved at 1% P. For Binary Symmetric Channel with 10 error probability, P results 32% (at P,, IO) for a single user whereas 65% for a five user case. In the second part of the dissertation, a novel channel model ie. double exponential correlation is incorporated for spectrum sensing algorithms under suburban environments. Asymptotic probability of detection is derived, analysed and compared with classical exponential correlation model (also known as Gudmundson's model). Using proposed model missed detection probability reaches Zero for less than ten sensors whereas Gudmundson's model results a constant 0. 7 missed detection probability even when the sensing users are increased to hundred. Thus, results verify that the proposed model performs significantly better than the classical one. In the third part of the dissertation, a cooperative sensing strategy is proposed for mobility-driven cognitive radio. It is also verified through simulation results that the proposed decision-fusion based architecture performs significantly better than the independent sensing radios. Using collaboration under urban environments, missed detection results in 30% in comparison to 62% for a single user under false alarm probability of 10%. <br/>
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Cognitive Radio Thesis
9 (RLIN) 99673
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Spectrum Sensing Thesis
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type PHD Thesis
Source of classification or shelving scheme Dewey Decimal Classification
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Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Stock Type Total Checkouts Full call number Barcode Date last seen Accession Date Koha item type
        Government Document Section Government Document Section Govt Publication Section 20/10/2022 Donation   621.384378242 SHA 93922 20/10/2022 15/05/2015 Reference Collection
        Government Document Section Government Document Section Govt Publication Section 20/10/2022 Donation   621.384378242 SHA 93923 20/10/2022 15/05/2015 Reference Collection
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