Semantic-Aware Resource Allocation Based on Deep Reinforcement Learning for 5G-V2X HetNets

Z Shao, Q Wu, P Fan, N Cheng, Q Fan… - arXiv preprint arXiv …, 2024 - arxiv.org
This letter proposes a semantic-aware resource allocation (SARA) framework with flexible
duty cycle (DC) coexistence mechanism (SARADC) for 5G-V2X Heterogeneous Network …

[PDF][PDF] AI-based Radio Resource and Transmission Opportunity Allocation for 5G-V2X HetNets: NR and NR-U networks

F Zeinali, S Norouzi, N Mokari… - International Journal of …, 2023 - researchgate.net
The capacity of fifth-generation(5G) vehicle-to-everything (V2X) networks poses significant
challenges. To address this challenge, this paper utilizes New Radio (NR) and New Radio …

Adaptive V2X user selection and resource allocation for ultra-dense 5G HetNet network

A Bouaziz, A Saddoud, LC Fourati… - … and Mobile Computing …, 2021 - ieeexplore.ieee.org
5G network is considered as an Heterogeneous networks (HetNets) able to support a
multitude of new services, where performance requirements will be extremely polarized. In …

Deep reinforcement learning for energy-efficient multi-channel transmissions in 5G cognitive hetnets: Centralized, decentralized and transfer learning based solutions

A Giannopoulos, S Spantideas, N Kapsalis… - IEEE …, 2021 - ieeexplore.ieee.org
Energy efficiency (EE) constitutes a key target in the deployment of 5G networks, especially
due to the increased densification and heterogeneity. In this paper, a Deep Q-Network …

A survey on applications of deep reinforcement learning in resource management for 5G heterogeneous networks

YL Lee, D Qin - 2019 Asia-Pacific Signal and Information …, 2019 - ieeexplore.ieee.org
Heterogeneous networks (HetNets) have been regarded as the key technology for fifth
generation (5G) communications to support the explosive growth of mobile traffics. By …

Towards low latency in 5G HetNets: A Bayesian cell selection/user association approach

M Elkourdi, A Mazin, RD Gitlin - 2018 IEEE 5G World Forum …, 2018 - ieeexplore.ieee.org
Expanding the cellular ecosystem to support an immense number of connected devices and
creating a platform that accommodates a wide range of emerging services of different traffic …

[HTML][HTML] Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks

J Zhao, F Hu, J Li, Y Nie - Digital Communications and Networks, 2023 - Elsevier
Abstract In Heterogeneous Vehicle-to-Everything Networks (HVNs), multiple users such as
vehicles and handheld devices and infrastructure can communicate with each other to …

A survey on resource allocation for 5G heterogeneous networks: Current research, future trends, and challenges

Y Xu, G Gui, H Gacanin, F Adachi - … Communications Surveys & …, 2021 - ieeexplore.ieee.org
In the fifth-generation (5G) mobile communication system, various service requirements of
different communication environments are expected to be satisfied. As a new evolution …

Deep reinforcement learning based wireless resource allocation for V2X communications

J Li, J Zhao, X Sun - 2021 13th International Conference on …, 2021 - ieeexplore.ieee.org
The shortage and low utilization of air-interface spectrum resources have always been the
bottleneck of the development of vehicle-to-everything (V2X) communications. In this paper …

Hybrid spectrum access for V2V heterogeneous networks with deep reinforcement learning

J Huang, J Peng, H Xiang, L Li… - 2022 14th International …, 2022 - ieeexplore.ieee.org
This paper studies the hybrid spectrum access for cellular vehicle-to-vehicle (V2V)
heterogeneous networks (Het-Nets) exploiting deep reinforcement learning (DRL) …