作者
Mohammad Asif Hossain, Rafidah Md Noor, Kok-Lim Alvin Yau, Saaidal Razalli Azzuhri, Muhammad Reza Z’aba, Ismail Ahmedy
发表日期
2020/4/23
来源
IEEE Access
卷号
8
页码范围
78054-78108
出版商
IEEE
简介
Nowadays, machine learning (ML), which is one of the most rapidly growing technical tools, is extensively used to solve critical challenges in various domains. Vehicular ad hoc network (VANET) is expected to be the key role player in reducing road casualties and traffic congestion. To ensure this role, a gigantic amount of data should be exchanged. However, current allocated wireless access for VANET is inadequate to handle such massive data amounts. Therefore, VANET faces a spectrum scarcity issue. Cognitive radio (CR) is a promising solution to overcome such an issue. CR-based VANET or CR-VANET must achieve several performance enhancement measures, including ultra-reliable and low-latency communication. ML methods can be integrated with CR-VANET to make CR-VANET highly intelligent, achieve rapid adaptability to the dynamicity of the environment, and improve the quality of service in an …
引用总数
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