Zero touch management: A survey of network automation solutions for 5G and 6G networks

E Coronado, R Behravesh… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Mobile networks are facing an unprecedented demand for high-speed connectivity
originating from novel mobile applications and services and, in general, from the adoption …

A survey of collaborative machine learning using 5G vehicular communications

SV Balkus, H Wang, BD Cornet… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
By enabling autonomous vehicles (AVs) to share data while driving, 5G vehicular
communications allow AVs to collaborate on solving common autonomous driving tasks …

NOMA and future 5G & B5G wireless networks: A paradigm

U Ghafoor, M Ali, HZ Khan, AM Siddiqui… - Journal of Network and …, 2022 - Elsevier
For the last few decades, wireless communication has been facing a technological
revolution. High data rate and continuous connectivity are the necessities because the …

Decentralized power allocation for MIMO-NOMA vehicular edge computing based on deep reinforcement learning

H Zhu, Q Wu, XJ Wu, Q Fan, P Fan… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is envisioned as a promising approach to process the
explosive computation tasks of vehicular user (VU). In the VEC system, each VU allocates …

Deep reinforcement learning-based cloud-edge collaborative mobile computation offloading in industrial networks

S Chen, J Chen, Y Miao, Q Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the rapid development of mobile industrial applications and due to the limited coverage
of static edge servers, traditional edge computing technology has great limitations in …

A power allocation scheme for MIMO-NOMA and D2D vehicular edge computing based on decentralized DRL

D Long, Q Wu, Q Fan, P Fan, Z Li, J Fan - Sensors, 2023 - mdpi.com
In vehicular edge computing (VEC), some tasks can be processed either locally or on the
mobile edge computing (MEC) server at a base station (BS) or a nearby vehicle. In fact …

Cost-effective task offloading in NOMA-enabled vehicular mobile edge computing

J Du, Y Sun, N Zhang, Z **ong, A Sun… - IEEE Systems …, 2022 - ieeexplore.ieee.org
Nonorthogonal multiple access (NOMA) and mobile edge computing (MEC) are two key
emerging technologies for vehicular networks, where NOMA allows multiple vehicular user …

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 …

[HTML][HTML] Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT

P Consul, I Budhiraja, R Arora, S Garg, BJ Choi… - Alexandria Engineering …, 2024 - Elsevier
The exponential proliferation of wearable medical apparatus and healthcare information
within the framework of the Internet of Medical Things (IoMT) introduces supplementary …

Evolution of road traffic congestion control: A survey from perspective of sensing, communication, and computation

W Yue, C Li, G Mao, N Cheng… - China Communications, 2021 - ieeexplore.ieee.org
Road traffic congestion can inevitably degrade road infrastructure and decrease travel
efficiency in urban traffic networks, which can be relieved by employing appropriate …