Real-time blind spectrum sensing using USRP

Proceedings - IEEE International Symposium on Circuits and Systems

Volumn 2015-July, Issue , 2015, Pages 986-989

  Srivastava, Saket ^a   Hashmi, Mohammad ^b   Das, Supratim ^b   Barua, Dibakar ^c  

^a UNIVERSITY OF LINCOLN   (United Kingdom)

^b INDRAPRASTHA INSTITUTE OF INFORMATION TECHNOLOGY   (India)

^c NETAJI SUBHAS INSTITUTE OF TECHNOLOGY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

LOGISTIC REGRESSION; OPEN SOURCE SOFTWARE;

BLIND SPECTRUM SENSING; CLASSIFICATION ACCURACY; ENERGY DETECTION; LOGISTIC REGRESSION CLASSIFIER; SPECTRUM SENSING; SPECTRUM SENSING TECHNIQUES; THRESHOLD-VALUE; WIRELESS TECHNOLOGIES;

CLASSIFICATION (OF INFORMATION);

EID: 84946231594     PISSN: 02714310     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISCAS.2015.7168801     Document Type: Conference Paper

References (12)

1. R. A. Rashid et al. Enabling Dynamic Spectrum Access for Cognitive Radio Using Software Defined Radio Spectrum sensing, access and coexistence testbed for Cognitive Radio using USRP in proceedings of 2011 IEEE Symposium on Wireless Technology and Applications (ISWTA), Langkawi, Malaysia, 2011.
2. George Nychis et al. Reclaiming the Whitespaces: Spectrum Efficient Coexistence with Primary Users Carnegie Mellon University, Microsoft Research.
3. J. Mitola III. Cognitive Radio: An integrated Agent Architecture for Software Defined Radio dissertation for Royal Institute of Technology (KTH), Sweden, 2000.
4. Mrs. R. S Kale(Sandikar) et al. Efficient Spectrum Sensing in Cognitive Radio Using Energy Detection with New Threshold Formulation in proceedings of the International Conference on Microelectronics, Communication and Renewable Energy (ICMiCR), Kanjirapally, India, 2013.
5. Md. A. Rahman et al. Development of Spectrum Sensing System with GNU Radio and USRP to Detect Emergency Radios The Institute of Electronics, Information and Communications Engineers (IEICE) Technical Report, 2009-10.
6. A. Mate et al. Spectrum Sensing based on Time Covariance Matrix using GNU-Radio and USRP for Cognitive Radio Department of Electrical and Computer Engineering, Polytechnic Institute of New York University, Brooklyn, New York, USA.
7. C. Ha et al. Efficient Cooperative Spectrum Sensing Methods for Cognitive Radio networks in proceedings of the Fourth International Conference on Digital Manufacturing and Automation, 2013.
8. J. Zheng et al. Cognitive Radio: methods for detecting free bands in proceedings of International Conference on Networks Security, Wireless Communications and Trusted Computing, Wuhan, China, 25-26 April, 2009.
9. H. Liu et al. Cyclic Stepping Spectrum Sensing based on energy detection in proceedings of the Internation Conference on Mechatronic Science, Electric Engineering and Computer, Jilin, China, 19-22 August, 2011.
10. Universal Software Radio Peripheral and Universal Hardware Driver Wiki (Ettus Research): code. ettus. com/redmine/ettus/projects/uhd/wiki.
11. The GNU-Radio Project Wiki (Eric Blossom, Tom Rondeau and Jonathan Corgan) gnuradio. org/redmine/projects/gnuradio/wiki/ development.
12. S. B. Kotsiantis et al. Supervised machine learning: A review of classification techniques, Emerging Artificial Intelligence Applications in Computer Engineering, 2007.