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Research Article |

Proficient Bayesian Classifier for Predicting Congestion and Active Node Sensing Classification in Wireless Cognitive Radio

Author(s): Mohanaprakash T A*, A. Haja Alaudeen, A.Salman Ayaz, Surya U and S.Kaviarasan

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 4

Publisher : FOREX Publication

Published : 23 December 2023

e-ISSN : 2347-470X

Page(s) : 1176-1182

DOI: https://doi.org/10.37391/ijeer.110439

Abstract

This study researches into fixed range designation systems with diverse applications in remote sensing, specifically addressing the emerging issue of range deficiency, particularly concerning access points with reduced range delivery services for remote hubs. An analysis of the existing system reveals limitations in current approaches. To overcome these challenges, the study proposes leveraging remote cognitive radio, a dynamic range access approach that optimally utilizes existing resources. The central focus of cognitive radio is on acquiring sensing data, addressing the deficiencies observed in the existing system. The paper introduces dynamic cognitive radio transmission, employing Bayesian energy detection with range sensing features. Computational performance is rigorously analyzed through MATLAB simulations, with a specific emphasis on identification features and the false alarm rate. Through this comparative study with existing methods, utilizing Bayesian energy processing, the findings contribute to the field by significantly enhancing the efficiency of range access in remote communication systems, addressing the shortcomings identified in the current system analysis.

Keywords: Bayesian Classifier, Cognitive Radio, Feature Selection, Prediction and Accuracy.




Mohanaprakash T A*, Associate Professor, Department of CSE, Panimalar Engineering College, Chennai, India; Email: tamohanaprakash@gmail.com

A. Haja Alaudeen, Assistant Professor, Department of Computer Applications, B.S. Abdur Rahman Crescent Institute of Science and Technology, Vandalur, Chennai, India; Email: hajasoftware@gmail.com

A.Salman Ayaz, Assistant Professor, Department of CS, Islamiah College (Autonomous), Vaniyambadi, India; Email: salmanayaz@gmail.com

Surya U, Assistant Professor, Department of CSE, St. Joseph's Institute of Technology, OMR, Chennai, India; Email: surya07ananthi@gmail.com

S.Kaviarasan, Assistant Professor, Department of AI & DS, Panimalar Engineering College, Poonamallee, Chennai, Tamil Nadu, India; Email: arasan.kavi@gmail.com

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Mohanaprakash T A, A. Haja Alaudeen, A.Salman Ayaz, Surya U and S.Kaviarasan (2023), Proficient Bayesian Classifier for Predicting Congestion and Active Node Sensing Classification in Wireless Cognitive Radio. IJEER 11(4), 1176-1182. DOI: 10.37391/ijeer.110439.