Machine Learning-Based Cooperative Spectrum Sensing in Dynamic Segmentation Enabled Cognitive Radio Vehicular Network Article Swipe
Md. Asif Hossain
,
Rafidah Md Noor
,
Kok‐Lim Alvin Yau
,
Saaidal Razalli Azzuhri
,
Muhammad Reza Z’aba
,
Ismail Ahmedy
,
Mohammad Reza Jabbarpour
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/en14041169
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/en14041169
A vehicle ad hoc network (VANET) is a solution for road safety, congestion management, and infotainment services. Integration of cognitive radio (CR), known as CR-VANET, is needed to solve the spectrum scarcity problems of VANET. Several research efforts have addressed the concerns of CR-VANET. However, more reliable, robust, and faster spectrum sensing is still a challenge. A novel segment-based CR-VANET (Seg-CR-VANET) architecture is therefore proposed in this paper. Roads are divided equally into segments, and they are sub-segmented based on the probability value. Individual vehicles or secondary users produce local sensing results by choosing an optimal spectrum sensing (SS) technique using a hybrid machine learning algorithm that includes fuzzy and naïve Bayes algorithms. We used dynamic threshold values for the sensing techniques. In this proposed cooperative SS, the segment spectrum agent (SSA) made the global decision using the tri-agent reinforcement learning (TA-RL) algorithm. Three environments (network, signal, and vehicle) are learned by this proposed algorithm to determine primary (licensed) users’ activities. The simulation results indicate that, compared to current works, the proposed Seg-CR-VANET produces better results in spectrum sensing.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/en14041169
- https://www.mdpi.com/1996-1073/14/4/1169/pdf?version=1614244664
- OA Status
- gold
- Cited By
- 32
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3132221436
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Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3132221436Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/en14041169Digital Object Identifier
- Title
-
Machine Learning-Based Cooperative Spectrum Sensing in Dynamic Segmentation Enabled Cognitive Radio Vehicular NetworkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-02-22Full publication date if available
- Authors
-
Md. Asif Hossain, Rafidah Md Noor, Kok‐Lim Alvin Yau, Saaidal Razalli Azzuhri, Muhammad Reza Z’aba, Ismail Ahmedy, Mohammad Reza JabbarpourList of authors in order
- Landing page
-
https://doi.org/10.3390/en14041169Publisher landing page
- PDF URL
-
https://www.mdpi.com/1996-1073/14/4/1169/pdf?version=1614244664Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1996-1073/14/4/1169/pdf?version=1614244664Direct OA link when available
- Concepts
-
Cognitive radio, Vehicular ad hoc network, Computer science, Spectrum management, Reinforcement learning, Segmentation, Spectrum (functional analysis), Computer network, Fuzzy logic, Wireless ad hoc network, Real-time computing, Artificial intelligence, Wireless, Telecommunications, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
32Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7, 2024: 4, 2023: 10, 2022: 6, 2021: 5Per-year citation counts (last 5 years)
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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