Situation-aware resource allocation for multi-dimensional intelligent multiple access: A proactive deep learning framework
To meet the ever-increasing communication services with diverse requirements, situation-
aware intelligent utilization of multi-dimensional communication resources is becoming …
aware intelligent utilization of multi-dimensional communication resources is becoming …
On using Deep Reinforcement Learning to balance Power Consumption and Latency in 5G NR
K Boutiba, A Ksentini - ICC 2023-IEEE International …, 2023 - ieeexplore.ieee.org
Future generation cellular networks consider Power Consumption (PC) as a key concern in
designing and operating wireless communication systems. In this context, 3GPP has …
designing and operating wireless communication systems. In this context, 3GPP has …
Ultra-Reliable Deep-Reinforcement-Learning-Based Intelligent Downlink Scheduling for 5G New Radio-Vehicle to Infrastructure Scenarios
J Wang, Y Zheng, J Wang, Z Shen, L Tong, Y Jing… - Sensors, 2023 - mdpi.com
Higher standards for reliability and efficiency apply to the connection between vehicle
terminals and infrastructure by the fifth-generation mobile communication technology (5G). A …
terminals and infrastructure by the fifth-generation mobile communication technology (5G). A …
Qcell: Self-optimization of softwarized 5g networks through deep q-learning
With the unprecedented rise in traffic demand and mobile subscribers, real-time fine-grained
optimization frame-works are crucial for the future of cellular networks. Indeed, rigid and …
optimization frame-works are crucial for the future of cellular networks. Indeed, rigid and …
Network Selection over 5G-Advanced Heterogeneous Networks Based on Federated Learning and Cooperative Game Theory
5G-Advanced and Beyond claims a 3D ecosystem with cooperation between terrestrial and
non-terrestrial networks to achieve seamless coverage, improve capacity, and enable …
non-terrestrial networks to achieve seamless coverage, improve capacity, and enable …
AI-enabled radio resource allocation in 5G for URLLC and eMBB users
M Elsayed, M Erol-Kantarci - 2019 IEEE 2nd 5G World Forum …, 2019 - ieeexplore.ieee.org
The fifth generation (5G) network is expected to accommodate heterogeneous traffic with
diverse QoS demands. In this paper, we address the coexistence of Ultra-Reliable Low …
diverse QoS demands. In this paper, we address the coexistence of Ultra-Reliable Low …
Evolution toward 6G wireless networks: A resource management perspective
In this article, we first present the vision, key performance indicators, key enabling
techniques (KETs), and services of 6G wireless networks. Then, we highlight a series of …
techniques (KETs), and services of 6G wireless networks. Then, we highlight a series of …
Hierarchical multi-objective deep reinforcement learning for packet duplication in multi-connectivity for URLLC
In this paper, machine learning solutions have been investigated to improve the decision of
packet duplication in a multi-connectivity cellular network to optimize the satisfaction of delay …
packet duplication in a multi-connectivity cellular network to optimize the satisfaction of delay …
Mobility management in multi-RAT multiI-band heterogeneous networks
SMA Zaidi - 2021 - shareok.org
Support for user mobility is the raison d'etre of mobile cellular networks. However, mounting
pressure for more capacity is leading to adaption of multi-band multi-RAT ultra-dense …
pressure for more capacity is leading to adaption of multi-band multi-RAT ultra-dense …
Deep learning (DL) based joint resource allocation and RRH association in 5G-multi-tier networks
Fifth-Generation (5G) networks have adopted a multi-tier structural model which includes
femtocells, picocells, and macrocells to ensure the user quality-of-service (QoS). To meet …
femtocells, picocells, and macrocells to ensure the user quality-of-service (QoS). To meet …