Deep Reinforcement Learning for Uplink Scheduling in NOMA-URLLC Networks
BM Robaglia, M Coupechoux… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This article addresses the problem of Ultra Reliable Low Latency Communications (URLLC)
in wireless networks, a framework with particularly stringent constraints imposed by many …
in wireless networks, a framework with particularly stringent constraints imposed by many …
Puncture-Predictive Fairness Scheduling Scheme for eMBB and URLLC Based on TD3 Algorithm
J Guo, G Nie, H Tian, B Zhang… - 2023 IEEE/CIC …, 2023 - ieeexplore.ieee.org
This paper addresses the downlink scheduling problem in the coexistence scenario of
enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication …
enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication …
Machine Learning-Based Uplink Scheduling Approaches for Mixed Traffic in Cellular Systems
The problem of the uplink resource allocation of mixed-traffic types in cellular networks is a
challenging problem that has not been addressed sufficiently in the literature. In this paper …
challenging problem that has not been addressed sufficiently in the literature. In this paper …
Reinforcement Learning for Uncoordinated Multiple Access
BM Robaglia - 2024 - theses.hal.science
Distributed Medium Access Control (MAC) protocols are fundamental in wireless
communication, yet traditional random access-based protocols face significant limitations …
communication, yet traditional random access-based protocols face significant limitations …
Graph Convolutional Network Enabled Power-Constrained HARQ Strategy for URLLC
In this paper, a power-constrained hybrid automatic repeat request (HARQ) transmission
strategy is developed to support ultra-reliable low-latency communications (URLLC). In …
strategy is developed to support ultra-reliable low-latency communications (URLLC). In …
Interference-Aware Based Resource Configuration Optimization for URLLC Grant-Free Transmission
X Zhang, T Peng, Y Guo… - 2023 IEEE Wireless …, 2023 - ieeexplore.ieee.org
The fifth-generation (5G) wireless network is expected to support emerging applications
requiring ultra high reliability and low latency, such as self-driving cars, factory automation …
requiring ultra high reliability and low latency, such as self-driving cars, factory automation …
Hybrid Radio Resource Management Based on Multi-Agent Reinforcement Learning
In this paper, we propose a novel hybrid grant-based and grant-free radio access scheme.
We provide two multi-agent reinforcement learning algorithms to optimize a global network …
We provide two multi-agent reinforcement learning algorithms to optimize a global network …
Enhanced Mobile Networking Using Multi-Connectivity and Packet Duplication in Next-Generation Cellular Networks
PK Mishra - 2023 - search.proquest.com
Modern cellular communication systems need to handle an enormous number of users and
large amounts of data, including both users as well as system-oriented data. 5G is the fifth …
large amounts of data, including both users as well as system-oriented data. 5G is the fifth …
Enabling High Throughput and Reliable Low Latency Communication over Vehicular Mobility in Next-Generation Cellular Networks
S Kar - 2023 - search.proquest.com
Abstract The fifth-generation (5G) networks and beyond need paradigm shifts to realize the
exponentially increasing demands of next-generation services for high throughputs, low …
exponentially increasing demands of next-generation services for high throughputs, low …
Centralised orchestration and hybrid resource management for Ultra Reliable and Low Latency Communications (URLLC)
NL Dinh - 2023 - theses.hal.science
During the past decades, with the significant proliferation of 5G networks, Ultra Reliable and
Low Latency Communications (URLLC) has been becoming indispensable to support time …
Low Latency Communications (URLLC) has been becoming indispensable to support time …