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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

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Impact Factor : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 79

Article Submitted : 5528

Article Published : 3054

Total Authors : 7813

Total Reviewer : 540

Total Countries : 68

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Paper Title: Efficient Spectrum Sensing using Robust Statistical Approach in Cognitive Radio Networks (CRNs)
Authors Name: Sujatha Kumari
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IJRTI_183644
Published Paper Id: IJRTI2208095
Published In: Volume 7 Issue 8, August-2022
DOI:
Abstract: : Identification of spectrum holes in large frequency bands is quite important for primary users and Cognitive Radio Networks (CRNs) is a suitable approach for detection of spectrum holes and for efficient spectrum utilization. Moreover, one of the important feature of CRNs is spectrum sensing which detects presence or absence of primary user so that secondary user can switch to another frequency band in time. However, swift and accurate spectrum sensing is required due to change in frequency band occupation dynamically. Thus, a statistical model is presented to perform highly efficient spectrum sensing based on the probability density functions. The main focus of research is to enhance the sensing accuracy and spectrum detection results. Filtering mechanism is utilized to remove Gaussian noise present in received primary data samples. High Quality features are obtained based on the degree of randomness and classification is performed using Support Vector Machine (SVM) classifier. Simulation results are carried out in terms of detection probability and false alarm probability using two large datasets and compared with varied classifiers such as K- Nearest Neighbour (KNN) and Logistic Regression (LR).
Keywords: Spectrum Sensing, Sstatistical model, Support Vector Machine (SVM), Probability Density Function, Primary User (PU).
Cite Article: "Efficient Spectrum Sensing using Robust Statistical Approach in Cognitive Radio Networks (CRNs)", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 8, page no.555 - 566, August-2022, Available :http://www.ijrti.org/papers/IJRTI2208095.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2208095
Registration ID:183644
Published In: Volume 7 Issue 8, August-2022
DOI (Digital Object Identifier):
Page No: 555 - 566
Country: Bangalore, Karnataka, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2208095
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2208095
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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