Transfer reinforcement learning for 5G new radio mmWave networks
M Elsayed, M Erol-Kantarci… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we aim at interference mitigation in 5G millimeter-Wave (mm-Wave)
communications by employing beamforming and Non-Orthogonal Multiple Access (NOMA) …
communications by employing beamforming and Non-Orthogonal Multiple Access (NOMA) …
Machine learning-based inter-beam inter-cell interference mitigation in mmWave
M Elsayed, K Shimotakahara… - ICC 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
In this paper, we address inter-beam inter-cell interference mitigation in 5G networks that
employ millimetre-wave (mmWave), beamforming and non-orthogonal multiple access …
employ millimetre-wave (mmWave), beamforming and non-orthogonal multiple access …
FML: Fast machine learning for 5G mmWave vehicular communications
Millimeter-Wave (mmWave) bands have become the de-facto candidate for 5G vehicle-to-
everything (V2X) since future vehicular systems demand Gbps links to acquire the …
everything (V2X) since future vehicular systems demand Gbps links to acquire the …
Genetic algorithm‐based beam refinement for initial access in millimeter wave mobile networks
Initial access (IA) is identified as a key challenge for the upcoming 5G mobile
communication system operating at high carrier frequencies, and several techniques are …
communication system operating at high carrier frequencies, and several techniques are …
Fast MIMO beamforming via deep reinforcement learning for high mobility mmWave connectivity
M Fozi, AR Sharafat, M Bennis - IEEE Journal on Selected …, 2021 - ieeexplore.ieee.org
Future 5G/6G wireless networks will be increasingly using millimeter waves (mmWaves),
where fast and efficient beamforming is vital for providing continuous service to highly …
where fast and efficient beamforming is vital for providing continuous service to highly …
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 …
algorithms for load balancing user association and handover in mmWave-enabled networks …
Multi-agent reinforcement learning for adaptive user association in dynamic mmWave networks
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 …
capacity and data rate requirements of the fifth generation (5G) of mobile networks. In this …
[HTML][HTML] Interference coordination for millimeter wave communications in 5G networks for performance optimization
To address the increasing data rate demands for future wireless networks, a dense
deployment of base stations or access points is the most promising approach; however …
deployment of base stations or access points is the most promising approach; however …
An online context-aware machine learning algorithm for 5G mmWave vehicular communications
Millimeter-Wave (mmWave) bands have become the de-facto candidate for 5G vehicle-to-
everything (V2X) since future vehicular systems demand Gbps links to acquire the …
everything (V2X) since future vehicular systems demand Gbps links to acquire the …
Self-attention reinforcement learning for multi-beam combining in mmWave 3D-MIMO systems
Abstract Machine learning (ML) has been empowering all aspects of the wireless
communication system design, among which, the reinforcement learning (RL)-based …
communication system design, among which, the reinforcement learning (RL)-based …