Intelligent Network Slicing in V2X Networks – A Comprehensive Review

ABSTRACT- The rise of the internet things (IoT) and autonomous systems has made connecting vehicles more critical. Connected can create diverse communication networks that improve environment offer contemporary applications. With advent 5G networks, vehicle-to-everything (V2X) are expected to be highly intelligent, reside on superfast, reliable, low-latency connections. Network slicing, Machine Learning (ML), Deep (DL) related network automation optimization in V2X communication. (ML/DL) with slicing aims optimize performance, reliability network, personalized services, reduced costs, scalability enhance overall driving experience. These advantages ultimately lead a safer efficient transportation system. However, existing Long-Term Evolution (LTE) enabling technologies cannot meet such dynamic requirements without adding higher complexity levels. learning algorithms mitigate levels, which instrumental vehicular systems. This study review based proposed taxonomy describes enablers different configuration ML algorithm used control manage slice. also reviews various research works established through enable use cases, focusing considering management. enabler considered light requirements, particular configurations, underlying methods algorithms, some critical challenges possible solutions available. paper concludes future roadmap by discussing open issues directions.