##plugins.themes.academic_pro.article.main##
Abstract
Frequency band is valuable in communication media. Different Telecommunication regularity authority have the rights to assign the spectrum to the users and the policy to assign spectrum till date is static frequency allocation policy due to such policies scarcity of the spectrum present. It is required to implement the dynamic frequency allocation techniques (DSS) to improve the spectrum usage. There are different techniques for spectrum sensing like energy detection, matched filter, cyclostationary, compressive, cooperative etc. Every method has its loops and holes, Energy detection method is useful and very simple method for spectrum sensing. In energy detection method output of energy detector compares with predefined threshold value In this implementation analysis like different other parameters like ROC, probability of detection (Pd), False alarm probability (FAP), Power spectral density (PSD). The simulation results shows that use of DSS avoids the wastage of bandwidth, probability of false alarm can be attained as well as receiver operating characteristic can be monitored, the simulation results are verified.Index Terms—Cognitive radio, spectrum sensing, Energy detection, Matlab /Simulink simulation
##plugins.themes.academic_pro.article.details##
References
2. A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications Tevfik Y¨ucek and H¨useyin Arslan IEEE COMMUNICATIONS SURVEYS & TUTORIALS, VOL. 11, NO. 1, FIRST QUARTER 2009
3. ARCOR: Agile Rateless Coded Relaying for Cognitive Radios Xijun Wang, Wei Chen, Member, IEEE, and Zhigang Cao, Senior Member, IEEEIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 60, NO. 6, JULY 2011
4. Review of Spectrum Sensing in Cognitive Rdio L. N. T. Perera and H. M. V. R. Herath, Member, IEEE 2011 6 th International Conferenceon Industrial and Information Systems, ICIIS 2011, Aug.16-19, 2011\
5. Weighted-Collaborative Spectrum Sensing in Cognitive Radio Xiaoge Huang, Ning Han, Guanbo Zheng, Sunghwan Sohn, Jaemoung Kim The Graduate School of Information Technology & Telecommunications Inha University, Incheon, korea
6. A Low-Overhead Energy Detection Based Cooperative Sensing Protocol for Cognitive Radio Systems Shunqing Zhang, Tianyu Wu, and Vincent K. N. Lau
7. Optimization of Threshold for Energy Based Spectrum Sensing Using Differential Evolution Aravind Narayanan Krishnamoorthy, Arun Shivaram Pasupathy, Maheshkumar Mani, Santhoshkumar Krishnamurthi, Sathiesh Kumar Leelakrishnan, Kotheneth Achuthan Narayanankutty 2011.
8. J. Mitola III, May, 2000. “Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio,†PhD Dissertation Royal Institute of Technology, Stockholm, Sweden
9. ENERGY DETECTION BASED SPECTRUM SENSING FOR COGNi RADIO M.Lakshmi#1, R.Saravanan*2 , R.Muthaiah#3 School of Computing, SASTRA University, Thanjavur-613402, India #1mlakshmi.s15@gmail.com *2saravanan_r@ict.sastra.edu 3sjamuthaiah@core.sastra.edu
10. Implementation and Analysis of Cognitive Radio System eru R. Lavudiya1, Dr. K.D. Kulat2 and Jagdish D. Kene3 1M.Tech Scholar ECE, Department V.N.I.T., Nagpur, India 2Professor and Head ECE Department V.N.I.T., Nagpur, India 3PhD Research Scholar ECE Department V.N.I.T., Nagpur, India International Journal of Computer Science and Telecommunications [Volume 4, Issue 7, July 2013