Implementation and Analysis of Spectrum Sensing Algorithms for SIMO Links
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Cognitive radio is an autonomous transceiver that is continuously sensing theongoing communication in its environment, it then starts the communication whenever it is appropriate. Therefore, cognitive radio helps improving the spectrum utilization of the overall communication system. However, without suitable spectrum sensing techniques, cognitive radio would fail. Hence, in this thesis we investigate and implement various spectrum sensing algorithms via software defined radio for both single antenna and multiple antenna cases. The main communi-cation scheme that we are using is OFDM. Moreover, both computer simulations and real-world measurements, have also been done for comparison and analysis ofthe detector’s performance. The detectors we are using are based on correlationfunction of the received signal and generalized likelihood ratio test with its eigen-value. The results from the simulations and measurements are then representedas probability of missed detection curves for different signal to noise ratios. Ourresults show that the performance of the generalized likelihood ratio test baseddetectors are at least 2 dB better than the correlation based detector in our mea-surement. Moreover, our simulations show that they are able to outperform thecorrelation function detector by more than 6 dB. Although, generalized likelihoodratio test based detectors seem to be better than the correlation function baseddetector, it requires more computational power which may limit its practical use.
Place, publisher, year, edition, pages
2013. , 57 p.
cognitive radio, USRP, OFDM, Spectrum sensing, GLRT, SDR
IdentifiersURN: urn:nbn:se:liu:diva-98211ISRN: LiTH-ISY-EX--13/4696--SEOAI: oai:DiVA.org:liu-98211DiVA: diva2:653113
Subject / course
2013-06-14, Systemet, B building, Linkoping University, Linkoping, 11:00 (English)