An Investigation of Non-Cooperative Spectrum Sensing Techniques Used In CR-VANET

Md. Asif Hossain¹ , Md. Ashifur Rahman² , Baker Hosen³ , Mohammad Toriqul Islam⁴ , Md. Nasim Miah⁵ , Md. Sadikur Rahman⁶

1. Department of Electrical and Electronic Engineering, Southeast University, Dhaka, Bangladesh.
2. Department of Electrical and Electronic Engineering, Southeast University, Dhaka, Bangladesh.
3. Department of Electrical and Electronic Engineering, Southeast University, Dhaka, Bangladesh.
4. Department of Electrical and Electronic Engineering, Southeast University, Dhaka, Bangladesh.
5. Department of Electrical and Electronic Engineering, Southeast University, Dhaka, Bangladesh.
6. Department of Electrical and Electronic Engineering, Southeast University, Dhaka, Bangladesh.

Section:Research Paper, Product Type: Journal-Paper
Vol.11 , Issue.4 , pp.58-66, Aug-2023

Online published on Aug 31, 2023

Copyright © Md. Asif Hossain, Md. Ashifur Rahman, Baker Hosen, Mohammad Toriqul Islam, Md. Nasim Miah, Md. Sadikur Rahman . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Cognitive radio vehicular networks (CR-VANETs) have gained significant attention as a means to improve spectrum utilization and communication efficiency in vehicular environments. A critical duty in CR-VANETs is spectrum sensing, which enables secondary users (SUs) to utilize underused frequency bands without interfering with prime users (PUs). Non-cooperative spectrum sensing techniques have emerged as an alternative to cooperative approaches due to practical challenges in achieving cooperation among vehicles. In this investigation, we review and categorize existing non-cooperative spectrum sensing techniques in CR-VANETs, including individual sensing, decision fusion, and game-theoretic methods. We analyze the advantages, limitations, and trade-offs of each approach, and investigate the impact of factors such as fading, interference, and mobility. Match filter detection, energy detection, and cyclo-stationary feature detection, the three widely used sensing techniques, have all been contrasted.

Key-Words / Index Term :
Vehicular Network, Cognitive Radio, Spectrum Sensing, Energy Detection, Matched Filter detection, Cyclo-stationary Detection

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