A new approach for spectrum sensing in cognitive radio using modified threshold and filtering Method

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2017 by IJETT Journal
Volume-49 Number-5
Year of Publication : 2017
Authors : Davinder Kaur, Er. Mandeep Kaur
DOI :  10.14445/22315381/IJETT-V49P245

Citation 

Davinder Kaur, Er. Mandeep Kaur "A new approach for spectrum sensing in cognitive radio using modified threshold and filtering Method", International Journal of Engineering Trends and Technology (IJETT), V49(5),295-298 July 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Cognitive radio is one of the communication mean that resolves the issue related to inefficient utilization of spectrum by facilitating the secondary user to utilize the unused licensed bands. To perform more improvisations in cognitive radio the concept of spread spectrum has been developed which sense the spectrum and detect the primary user efficiently, In this the specific amount of spectrum is allotted to the primary users and no other users have authority to utilize this band. In this form of communication the carrier signals can also get affected by noise or narrow bandwidth. To resolve the noise related issue various modulation and filtering techniques have been developed in last decades. In this study a novel approach has been developed by using Matched Filters to perform filtration of the signals so that the SNR of the system can be more efficient and effective. The proposed work also overcome a disadvantage of traditional work by using the concept of double threshold value to enhance the detection probability of the system. The performance of the proposed work is evaluated in the term of SNR and detection probability. The result section renders the comparison of proposed work with conventional work and proves that the proposal outnumbered the traditional spread spectrum sensing mechanisms.

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Keywords
Cognitive Radio, Spread Spectrum Sensing, Filtration, Noise, Matched Filters, SNR.