Intelligent Resource Allocation for Grant-Free Access: A Reinforcement Learning Approach
M Elsayem, H Abou-Zeid, A Afana… - IEEE Networking …, 2023 - ieeexplore.ieee.org
Future wireless networks will support applications demanding high data-rates, ultra-low
latency, and high reliabilities. One technology for such ultra-reliable low latency …
latency, and high reliabilities. One technology for such ultra-reliable low latency …
Reinforcement learning-based dynamic resource allocation for grant-free access
M Elsayem, H Abou-Zeid, A Afana… - GLOBECOM 2022-2022 …, 2022 - ieeexplore.ieee.org
Cellular networks have evolved to deliver high-speed broadband services to support the
requirements of IoT applications, which demand high speed, low latency, and massive …
requirements of IoT applications, which demand high speed, low latency, and massive …
Experienced deep reinforcement learning with generative adversarial networks (GANs) for model-free ultra reliable low latency communication
In this paper, a novel experienced deep reinforcement learning (deep-RL) framework is
proposed to provide model-free resource allocation for ultra reliable low latency …
proposed to provide model-free resource allocation for ultra reliable low latency …
Improved grant-free access for URLLC via multi-tier-driven computing: Network-load learning, prediction, and resource allocation
Z Zhao, Q Du, GK Karagiannidis - IEEE Journal on Selected …, 2023 - ieeexplore.ieee.org
Grant-Free (GF) access has been recognized as a promising candidate for Ultra-Reliable
and Low-Latency Communications (URLLC). However, even with GF access, URLLC still …
and Low-Latency Communications (URLLC). However, even with GF access, URLLC still …
Deep reinforcement learning based massive access management for ultra-reliable low-latency communications
With the rapid deployment of the Internet of Things (IoT), fifth-generation (5G) and beyond
5G networks are required to support massive access of a huge number of devices over …
5G networks are required to support massive access of a huge number of devices over …
Machine learning for 6G enhanced ultra-reliable and low-latency services
Ultra-reliable and low-latency communications (URLLC), as one of the major communication
services of the fifth-generation (5G) and the sixth-generation (6G) cellular networks, is critical …
services of the fifth-generation (5G) and the sixth-generation (6G) cellular networks, is critical …
Intelligent Resource Management for eMBB and URLLC in 5G and beyond Wireless Networks
In the era of 5G and beyond wireless networks, the simultaneous support of enhanced
Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) …
Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) …
Experienced Deep Reinforcement Learning with Generative Adversarial Networks (GANs) for Model-Free Ultra Reliable Low Latency Communication
In this paper, a novel experienced deep reinforcement learning (deep-RL) framework is
proposed to provide model-free resource allocation for ultra reliable low latency …
proposed to provide model-free resource allocation for ultra reliable low latency …
DRL-based Joint Resource Scheduling of eMBB and URLLC in O-RAN
This work addresses resource allocation challenges in multi-cell wireless systems catering
to enhanced Mobile Broad-band (eMBB) and Ultra-Reliable Low Latency Communications …
to enhanced Mobile Broad-band (eMBB) and Ultra-Reliable Low Latency Communications …
Distributed resource allocation for URLLC in IIoT scenarios: A multi-armed bandit approach
This paper addresses the problem of enabling inter-machine Ultra-Reliable Low-Latency
Communication (URLLC) in future 6G Industrial Internet of Things (IIoT) networks. As far as …
Communication (URLLC) in future 6G Industrial Internet of Things (IIoT) networks. As far as …