Multi-agent reinforcement learning for adaptive user association in dynamic mmWave networks

M Sana, A De Domenico, W Yu… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Network densification and millimeter-wave technologies are key enablers to fulfill the
capacity and data rate requirements of the fifth generation (5G) of mobile networks. In this …

Evolution of RAN Architectures Towards 6G: Motivation, Development, and Enabling Technologies

J Chen, X Liang, J Xue, Y Sun, H Zhou… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
In this survey paper, we first provide insights on the evolution of radio access networks
(RANs) through investigating the existing paradigms and future trends towards 6G. We then …

[HTML][HTML] Deep Reinforcement Learning for QoS provisioning at the MAC layer: A Survey

M Abbasi, A Shahraki, MJ Piran, A Taherkordi - Engineering Applications of …, 2021 - Elsevier
Abstract Quality of Service (QoS) provisioning is based on various network management
techniques including resource management and medium access control (MAC). Various …

Reinforcement learning meets wireless networks: A layering perspective

Y Chen, Y Liu, M Zeng, U Saleem, Z Lu… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Driven by the soaring traffic demand and the growing diversity of mobile services, wireless
networks are evolving to be increasingly dense and heterogeneous. Accordingly, in such …

Reinforcement learning for user association and handover in mmwave-enabled networks

A Alizadeh, M Vu - IEEE Transactions on Wireless …, 2022 - ieeexplore.ieee.org
Using a multi-armed bandit technique, we propose centralized and semi-distributed online
algorithms for load balancing user association and handover in mmWave-enabled networks …

Multi-agent deep reinforcement learning for distributed handover management in dense mmWave networks

M Sana, A De Domenico, EC Strinati… - ICASSP 2020-2020 …, 2020 - ieeexplore.ieee.org
The dense deployment of millimeter wave small cells combined with directional
beamforming is a promising solution to enhance the network capacity of the current …

An online algorithm for computation offloading in non-stationary environments

AU Rahman, G Ghatak… - IEEE Communications …, 2020 - ieeexplore.ieee.org
We consider the latency minimization problem in a task-offloading scenario, where multiple
servers are available to the user equipment for outsourcing computational tasks. To account …

Multi-armed bandit load balancing user association in 5G cellular HetNets

A Alizadeh, M Vu - GLOBECOM 2020-2020 IEEE Global …, 2020 - ieeexplore.ieee.org
Using a reinforcement learning multi-armed bandit (MAB) technique, we design a
centralized and a semi-distributed online algorithms, for performing load balancing user …

Low complexity closed‐loop strategy for mmWave communication in industrial intelligent systems

N Chen, H Lin, Y Zhao, L Huang, X Du… - … Journal of Intelligent …, 2022 - Wiley Online Library
Modern communication and computing technology is the basic support of the industrial
intelligent systems (IIS). As a key component of IIS, the smart port is essential to be offered …

Transferable and Distributed User Association Policies for 5G and Beyond Networks

M Sana, N Di Pietro, EC Strinati - 2021 IEEE 32nd Annual …, 2021 - ieeexplore.ieee.org
We study the problem of user association, namely finding the optimal assignment of user
equipment to base stations to achieve a targeted network performance. In this paper, we …