Role of machine learning in resource allocation strategy over vehicular networks: a survey

I Nurcahyani, JW Lee - Sensors, 2021 - mdpi.com
The increasing demand for smart vehicles with many sensing capabilities will escalate data
traffic in vehicular networks. Meanwhile, available network resources are limited. The …

Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends

HMF Noman, E Hanafi, KA Noordin, K Dimyati… - IEEE …, 2023 - ieeexplore.ieee.org
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …

Integration of D2D, network slicing, and MEC in 5G cellular networks: Survey and challenges

L Nadeem, MA Azam, Y Amin, MA Al-Ghamdi… - IEEE …, 2021 - ieeexplore.ieee.org
With the tremendous demand for connectivity anywhere and anytime, existing network
architectures should be modified. To cope with the challenges that arise due to the …

Deep reinforcement learning for adaptive network slicing in 5G for intelligent vehicular systems and smart cities

A Nassar, Y Yilmaz - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Intelligent vehicular systems and smart city applications are the fastest growing Internet-of-
Things (IoT) implementations at a compound annual growth rate of 30%. In view of the …

Consortium blockchain-based spectrum trading for network slicing in 5G RAN: A multi-agent deep reinforcement learning approach

GO Boateng, G Sun, DA Mensah… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Network slicing (NS) is envisioned as an emerging paradigm for accommodating different
virtual networks on a common physical infrastructure. Considering the integration of …

Machine learning in network slicing—a survey

HP Phyu, D Naboulsi, R Stanica - IEEE Access, 2023 - ieeexplore.ieee.org
5G and beyond networks are expected to support a wide range of services, with highly
diverse requirements. Yet, the traditional “one-size-fits-all” network architecture lacks the …

Collaborative and intelligent resource optimization for computing and caching in IoV with blockchain and MEC using A3C approach

X Ye, M Li, P Si, R Yang, Z Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, the rise of the Internet of Vehicles (IoV) has driven the broad development of
intelligent transportation and smart cities. In order to promote the computing power of mobile …

Intelligent reflecting vehicle surface: A novel IRS paradigm for moving vehicular networks

W Jiang, HD Schotten - MILCOM 2022-2022 IEEE Military …, 2022 - ieeexplore.ieee.org
Intelligent reflecting surface (IRS) has recently received much attention from the research
community due to its potential to achieve high spectral and power efficiency cost-effectively …

Orthogonal and non-orthogonal multiple access for intelligent reflection surface in 6G systems

W Jiang, HD Schotten - 2023 IEEE Wireless Communications …, 2023 - ieeexplore.ieee.org
Intelligent reflecting surface (IRS) is envisioned to become a key technology for the
upcoming six-generation (6G) wireless system due to its potential of reaping high …

Minimum Latency‐Secure Key Transmission for Cloud‐Based Internet of Vehicles Using Reinforcement Learning

V Akilandeswari, A Kumar… - Computational …, 2022 - Wiley Online Library
The Internet of Vehicles (IoV) communication key management level controls the
confidentiality and security of its data, which may withstand user identity‐based attacks such …