Autonomous Radio Resource Provisioning in Multi-WAT Private 5G RANs based on DRL

Article Chemistry, Analytical

5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0

Lorena Chinchilla-Romero et al.

Summary: This article evaluates the effectiveness of infrastructure slicing in providing isolation in an industrial private 5G network. The results suggest that using dedicated slices for each production line can reduce downtime and associated costs, and the use of Time-Sensitive Networking (TSN) provides better isolation compared to standard Ethernet.

SENSORS (2022)

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Article Engineering, Electrical & Electronic

5G-CLARITY: 5G-Advanced Private Networks Integrating 5GNR, WiFi, and LiFi

Tezcan Cogalan et al.

Summary: The future of the manufacturing industry relies heavily on digital systems, specifically private 5G networks, to meet stringent requirements for availability, reliability, security, low latency, and high accuracy positioning. The 5G-CLARITY system integrates multiple access networks, provides high-precision positioning, and orchestrates private network slices, demonstrating its ability to monitor traffic, achieve centimeter-level positioning accuracy, and provision network slices quickly.

IEEE COMMUNICATIONS MAGAZINE (2022)

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Review Chemistry, Analytical

Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey

Johanna Andrea Hurtado Sanchez et al.

Summary: This paper discusses the importance of network slicing and deep reinforcement learning for achieving 5G and 6G networks, and analyzes the methods of using reinforcement learning and deep reinforcement learning algorithms in network slice resource management. It analyzes various aspects of the problem and provides research directions related to this field.

SENSORS (2022)

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Article Engineering, Multidisciplinary

Dynamic SDN-Based Radio Access Network Slicing With Deep Reinforcement Learning for URLLC and eMBB Services

Abderrahime Filali et al.

Summary: The proposed two time-scales RAN slicing mechanism optimizes the performance of ultra-reliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB) services. By modeling the problem as Markov decision processes and leveraging different algorithms, efficient resource allocation is achieved for different time scales.

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING (2022)

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Article Engineering, Electrical & Electronic

A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning

Changyang She et al.

Summary: This tutorial discusses the development of URLLCs in future 6G networks using deep learning algorithms and highlights the inadequacy of current mobile communication systems in meeting URLLCs requirements. It introduces the integration of domain knowledge into deep learning algorithms and suggests future research directions.

PROCEEDINGS OF THE IEEE (2021)

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Article Computer Science, Information Systems

5G Non-Public Networks: Standardization, Architectures and Challenges

Jonathan Prados-Garzon et al.

Summary: 5G is ushering in a new era of digitization and innovation opportunities across various sectors. Private networks are expected to play a significant role in providing exclusive services to enterprise customers in a myriad of 5G-enabled use cases. This article outlines the technical requirements, solutions, and challenges of private 5G networks, as well as the latest capabilities of 3GPP Release 16 in supporting these networks.

IEEE ACCESS (2021)

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Article Computer Science, Hardware & Architecture