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Implementation of Spectrum Sensing Techniques Using GNU Radio and Universal Software Radio Peripheral
Abstract
Cognitive Radio (CR) is a solution to the growing issue of spectrum scarcity and radio resource management. A CR exploits underutilized spectrum. It senses the spectrum for occupancy by the licensed users, also called as primary users and transmits its data only when the spectrum is sensed to be available. For the efficient utilization of the spectrum while also guaranteeing adequate protection to the licensed user from harmful interference, the receiver should be able to sense the spectrum for primary occupancy accurately. In this paper, different varieties of spectrum sensing techniques are presented and assessed. After studying and comparing them, two spectrum sensing techniques viz. Energy Detection and Matched Filter were selected. These two methods are implemented using a GNU Radio and using Universal Software Radio Peripheral (USRP). Integration of Spectrum Sensing techniques with wireless standards such as IEEE 802.11 and IEEE 802.22 will result in effective spectrum utilization.
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References
ReenaRatheeJaglan, SandeepSarowa, Rashid Mustafa, Sunil Agrawal, Naresh Kumar, “Comparative Study of Single-user Spectrum Sensing Techniques in Cognitive Radio Networks” 1877-0509, Second International Symposium on Computer Vision and the Internet (VisionNet’15).
BodepudiMounika,, Kolli Ravi Chandra, Rayala Ravi Kumar, “Spectrum Sensing Techniques and Issues in Cognitive Radio”, International Journal of Engineering Trends and Technology (IJETT) – Volume 4 , Page 695, 2013
AvendañoFernández Eduardo, René Geovani González Caballero, “Experimental evaluation of Performance for Spectrum Sensing: Matched filter vs Energy detector”, IEEE COLCOM, 2015.
Mahmood A. Abdulsattar and Zahir A. Hussein, “Energy Detection Technique For Spectrum Sensing In Cognitive Radio: A Survey”, International Journal of Computer Networks & Communications (IJCNC).
USRP B200 and B210 Ettus Research Datasheet.
FarrukhJaved, Imran Shafi and AsadMahmood, “A Novel Radio Mode Identification Approach for Spectrum Sensing in Cognitive Radios”, International Journal of Communication Networks and Information Security, Vol. 4, 2012.
Aparna P.S, M. Jayasheela, “Cyclostationary Feature Detection in Cognitive Radio using Different Modulation Schemes”, International Journal of Computer Applications (0975 – 8887), Volume 47– No.21, 2012.
Ireyuwa E. Igbinosa, Olutayo O. Oyerinde, Viranjay M. Srivastava, Stanley Mneney, “Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 12, 2015.
Fatima Salahdine, Hassan El Ghazi, NaimaKaabouch, WassimFassiFihri, “Matched Filter Detection with Dynamic Threshold for Cognitive Radio Networks”, Wireless Networks and Mobile CommunicationsIEEE, 2015.
Matched Filter Documentation for explaining UAVRT-SDR’s current matched filter Flagstaff, AZ.
Fabrício B. S. de Carvalhoabc, Waslon T. A. Lopesac, Marcelo S. Alencarac, “Performance of Cognitive Spectrum Sensing Based on Energy Detector in Fading Channel”, International Conference on Communication, Management and Information Technology (ICCMIT), 2015.
Fatty M. Salem, Maged H. Ibrahim, Ihab A. Ali, I. I. Ibrahim, “Matched-Filter-based Spectrum Sensing for Secure Cognitive Radio Network Communications”, International Journal of Computer Applications,Volume 87, 2014.
American J. of Engineering and Applied Sciences, “Novel Approach to Signal Detection of Sensor Array Units Using 5-3-1 Rule Based Matched Filter Algorithm with Intelligent Identifiers”, American J. of Engineering and Applied Sciences, 2010.
Daniela Mercedes MartínezPlataa, Ángel Gabriel Andrade Reátiga, “Evaluation of energy detection for spectrum sensing based on the dynamic selection of detection-threshold”, International Meeting of Electrical Engineering Research ENIINVIE, 2012.
SrikanthMunjuluria,Rama Murthy Garimellab, “Towards faster spectrum sensing techniques in cognitive radio architectures”, International Conference on Information and Communication Technologies, 2014.
R.GaneshBabua, Dr.V.Amudhab, “Spectrum Sensing Cluster Techniques In Cognitive Radio Networks”, International Conference on Computational Science, 2016.
Avinash P, Gandhiraj R, Soman K, “Spectrum Sensing using Compressed Sensing Techniques for Sparse Multiband Signals”, International Journal of Scientific & Engineering Research, Volume 3,Issue 5, 2012.
Jayanta Mishra, Deepak Kumar Barik, Ch. Manoj Kumar Swain, “Cyclostationary Based Spectrum Sensing in Cognitive Radio: Windowing Approach”, International Journal of Recent Technology and Engineering (IJRTE), Volume-3, Issue-1, March 2014.
Aparna P.S, M. Jayasheela, “Cyclostationary Feature Detection in Cognitive Radio using Different Modulation Schemes”, International Journal of Computer Applications, Volume 47, 2012
Roohi and Naseeb Singh Dhillon, “Hybrid spectrum sensing Technique based on energy and Cyclostationary techniques in cognitive radio: A Review”, International Journal on Emerging Technologies, 2016.
Smriti Bajpai, “Intelligent Spectrum Sensing Techniques for Cognitive Radio Network”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 5, Issue 4, April 2016
S V R K Rao, G Singh, “Wavelet Based Spectrum Sensing Techniques in Cognitive Radio”, ICMOC 2012.
Bastian Bloessl, Michele Segata, ChristophSommer, Falko Dressler, “An IEEE 802.11a/g/p OFDM Receiver for GNU Radio”.
G.V.Rangaraj, M.R.Raghavendra, K.Giridhar, “Improved Channel Estimation ForOfdm Based Wlan Systems, Telecommunication and Networking (TeNeT) Group”, Department of Electrical Engineering, Indian Institute of Technology, Madras.
RachanaKhanduri, S. S. Rattan, Performance “Comparison Analysis between IEEE 802.11a/b/g/n Standards”, International Journal of Computer Applications, Volume78– No.1, September, 2013.
Carlos Cordeiro, KiranChallapali, DagnachewBirru, Sai Shankar N, “IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radio”, Journal of Communications, Vol. 1, No. 1, April 2006.
Stephen J. Shellhammer, “Spectrum Sensing In IEEE 802.22”, Qualcomm Inc.
S. Sharma and C. C. Tripathi, “A Wide Spectrum Sensing and Frequency Reconfigurable Antenna for Cognitive Radio”, Progress In Electromagnetics Research C, Vol. 67, 11-20, 2016.
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