A multi-agent reinforcement learning approach for massive access in NOMA-URLLC networks
H Han, X Jiang, W Lu, W Zhai, Y Li… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Ultra-reliable low-latency communication (URLLC) enables diverse applications with
rigorous latency and reliability requirements. To provide a wide range of services, the future …
rigorous latency and reliability requirements. To provide a wide range of services, the future …
A reliable reinforcement learning for resource allocation in uplink NOMA-URLLC networks
In this paper, we propose a deep state-action-reward-state-action (SARSA) learning
approach for optimising the uplink resource allocation in non-orthogonal multiple access …
approach for optimising the uplink resource allocation in non-orthogonal multiple access …
A general deep reinforcement learning framework for grant-free NOMA optimization in mURLLC
Grant-free non-orthogonal multiple access (GF-NOMA) is a potential technique to support
massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the …
massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the …
Deep reinforcement learning-based grant-free NOMA optimization for mURLLC
Grant-free non-orthogonal multiple access (GF-NOMA) is a potential technique to support
massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the …
massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the …
Optimization of grant-free NOMA with multiple configured-grants for mURLLC
Massive Ultra-Reliable and Low-Latency Communications (mURLLC), which integrates
URLLC with massive access, is emerging as a new and important service class in the next …
URLLC with massive access, is emerging as a new and important service class in the next …
Spatial-Separable NOMA-Based Intelligent Hierarchical Fast Uplink Grant for mURLLC Over Cell-Free Networks
J Wang, J Li, P Zhu, D Wang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Massive ultra-reliable and low latency communications (mURLLC) has emerged as a
dominating 6G-standard service. Fast uplink grant is an effective means to solve the uplink …
dominating 6G-standard service. Fast uplink grant is an effective means to solve the uplink …
Multi-agent DRL approach for energy-efficient resource allocation in URLLC-enabled grant-free NOMA systems
Grant-free non-orthogonal multiple access (GF-NOMA) has emerged as a promising access
technology for the fifth generation and beyond wireless networks that enable ultra-reliable …
technology for the fifth generation and beyond wireless networks that enable ultra-reliable …
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 …
Cooperative deep reinforcement learning based grant-free NOMA optimization for mURLLC
Grant-free non-orthogonal multiple access (GF-NOMA) is a potential technique to support
massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the …
massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the …
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 …