Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Genetic Algorithm for Selecting Optimal Secondary Users to Collaborate in Spectrum sensing
Blekinge Institute of Technology, School of Engineering.
Blekinge Institute of Technology, School of Engineering.
2010 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesisAlternative title
Genetisk algoritm för val av Optimal Sekundära användare att samarbeta i Spectrum avkänning (Swedish)
Abstract [en]

Cognitive Radio is an innovative technology that allows the secondary unlicensed users to share the spectrum with licensed primary users to utilize the spectrum. For maximum utilization of spectrum, in cognitive radio network spectrum sensing is an important issue. Cognitive user under extreme shadowing and channel fading can‟t sense the primary licensed user signal correctly and thus to improve the performance of spectrum sensing, collaboration between secondary unlicensed users is required. In collaborative spectrum sensing the observation of each secondary user is received by a base station acting as a central entity, where a final conclusion about the presence or absence of the primary user signal is made using a particular decision and fusion rule. Due to spatially correlated shadowing the collaborative spectrum sensing performance decreases, and thus optimum secondary users must be selected to, not only improve spectrum sensing performance but also lessen the processing overhead of the central entity. A particular situation is depicted in the project where according to some performance parameters, first those optimum secondary users that have enough spatial separation and high average received SNR are selected using Genetic Algorithm, and then collaboration among these optimum secondary users is done to evaluate the performance. The collaboration of optimal secondary user providing high probability of detection and low probability of false alarm, for sensing the spectrum is compared with the collaboration of all the available secondary users in that radio environment. At the end a conclusion has been made that collaboration of selected optimum secondary users provides better performance, then the collaboration of all the secondary users available.

Abstract [sv]

Cognitive Radio is an innovative technology that allows the secondary unlicensed users to share the spectrum with licensed primary users to utilize the spectrum. For maximum utilization of spectrum, in cognitive radio network spectrum sensing is an important issue. Cognitive user under extreme shadowing and channel fading can‟t sense the primary licensed user signal correctly and thus to improve the performance of spectrum sensing, collaboration between secondary unlicensed users is required. In collaborative spectrum sensing the observation of each secondary user is received by a base station acting as a central entity, where a final conclusion about the presence or absence of the primary user signal is made using a particular decision and fusion rule. Due to spatially correlated shadowing the collaborative spectrum sensing performance decreases, and thus optimum secondary users must be selected to, not only improve spectrum sensing performance but also lessen the processing overhead of the central entity. A particular situation is depicted in the project where according to some performance parameters, first those optimum secondary users that have enough spatial separation and high average received SNR are selected using Genetic Algorithm, and then collaboration among these optimum secondary users is done to evaluate the performance. The collaboration of optimal secondary user providing high probability of detection and low probability of false alarm, for sensing the spectrum is compared with the collaboration of all the available secondary users in that radio environment. At the end a conclusion has been made that collaboration of selected optimum secondary users provides better performance, then the collaboration of all the secondary users available.

Place, publisher, year, edition, pages
2010. , 76 p.
Keyword [en]
Geneticl Algorithm, secondary users, Cognitive radio, Spectrum sensing
National Category
Signal Processing Probability Theory and Statistics Telecommunications
Identifiers
URN: urn:nbn:se:bth-3418Local ID: oai:bth.se:arkivexDE5E1818A4AED8AAC12577C90068F537OAI: oai:DiVA.org:bth-3418DiVA: diva2:830724
Uppsok
Physics, Chemistry, Mathematics
Supervisors
Available from: 2015-04-22 Created: 2010-10-27 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

fulltext(1172 kB)210 downloads
File information
File name FULLTEXT01.pdfFile size 1172 kBChecksum SHA-512
5dc48e93f0b80b166ef832f0aea295a3029b4db41fd5429b3cf221611fa4eb85514fb0dda6dcfd713f0a85bf4c61ce77e536a368b714ca88223b86441594b05b
Type fulltextMimetype application/pdf
fulltext(1172 kB)232 downloads
File information
File name FULLTEXT02.pdfFile size 1172 kBChecksum SHA-512
5dc48e93f0b80b166ef832f0aea295a3029b4db41fd5429b3cf221611fa4eb85514fb0dda6dcfd713f0a85bf4c61ce77e536a368b714ca88223b86441594b05b
Type fulltextMimetype application/pdf

By organisation
School of Engineering
Signal ProcessingProbability Theory and StatisticsTelecommunications

Search outside of DiVA

GoogleGoogle Scholar
Total: 442 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 218 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf