Spectrum sensing challenges & their solutions in cognitive radio based vehicular networks

Hossain, Mohammad Asif and Md Noor, Rafidah and Azzuhri, Saaidal Razalli and Z'aba, Muhammad Reza and Ahmedy, Ismail and Yau, Kok-Lim Alvin and Chembe, Christopher (2021) Spectrum sensing challenges & their solutions in cognitive radio based vehicular networks. International Journal of Communication Systems, 34 (7). ISSN 1074-5351, DOI https://doi.org/10.1002/dac.4748.

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Abstract

Vehicular ad hoc network (VANET) has been established to mitigate road collisions and traffic congestion and provide infotainment facilities to users. Allocated channels to VANET, which is the DSRC (Dedicated Short-Range Communication), are not adequate for the full implementation of VANET. Cognitive radio (CR) can be used to alleviate this issue. CR is a programmable and intelligent radio system capable of reaching various frequency ranges. CR needs to conduct spectrum sensing to get these bands. A vehicle fitted with a CR can sense the licensed spectrum to locate the vacant spectrum (which is not used by any licensed user) when the DSRC is wholly occupied. Compared to other CR networks, VANET faces specific additional difficulties related to spectrum sensing, such as periodic topological shifts due to high-speed mobility, multipath fading and shadowing issues, and heterogeneous quality of service (QoS) specifications. This paper explains these problems in depth. All the problems and issues were explored from the perspective of the CR focused on VANET. Probable ideas and directions to overcome these problems have also been presented. We have provided a conceptual framework for spectrum sensing. The framework resolves a variety of issues and concerns that are discussed in the paper. It gives much better results than conventional sensing techniques.

Item Type: Article
Funders: Universiti Malaya [RK004-2017] [CR-UM-SST-DCIS-2018-01]
Uncontrolled Keywords: Cognitive radio; High-; Speed mobility; Machine learning; Multipath fading; Shadowing; Spectrum sensing; VANET
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Computer Science & Information Technology > Department of Computer System & Technology
Depositing User: Ms Zaharah Ramly
Date Deposited: 21 Apr 2022 07:32
Last Modified: 21 Apr 2022 07:32
URI: http://eprints.um.edu.my/id/eprint/28845

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