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On the road to 6G: Visions, requirements, key technologies, and testbeds
Fifth generation (5G) mobile communication systems have entered the stage of commercial
deployment, providing users with new services, improved user experiences as well as a host …
deployment, providing users with new services, improved user experiences as well as a host …
A comprehensive review on artificial intelligence/machine learning algorithms for empowering the future IoT toward 6G era
The evolution of the wireless network systems over decades has been providing new
services to the users with the help of innovative network and device technologies. In recent …
services to the users with the help of innovative network and device technologies. In recent …
Applications of machine learning in resource management for RAN-slicing in 5G and beyond networks: A survey
One of the key foundations of 5th Generation (5G) and beyond 5G (B5G) networks is
network slicing, in which the network is partitioned into several separated logical networks …
network slicing, in which the network is partitioned into several separated logical networks …
Towards deep learning-aided wireless channel estimation and channel state information feedback for 6G
Deep learning (DL), a branch of artificial intelligence (AI) techniques, has shown great
promise in various disciplines such as image classification and segmentation, speech …
promise in various disciplines such as image classification and segmentation, speech …
[HTML][HTML] Federated deep reinforcement learning-based task offloading and resource allocation for smart cities in a mobile edge network
X Chen, G Liu - Sensors, 2022 - mdpi.com
Mobile edge computing (MEC) has become an indispensable part of the era of the intelligent
manufacturing industry 4.0. In the smart city, computation-intensive tasks can be offloaded to …
manufacturing industry 4.0. In the smart city, computation-intensive tasks can be offloaded to …
How to attack and defend nextg radio access network slicing with reinforcement learning
In this paper, reinforcement learning (RL) for network slicing is considered in next
generation (NextG) radio access networks, where the base station (gNodeB) allocates …
generation (NextG) radio access networks, where the base station (gNodeB) allocates …
PandORA: Automated design and comprehensive evaluation of deep reinforcement learning agents for Open RAN
The highly heterogeneous ecosystem of Next Generation (NextG) wireless communication
systems calls for novel networking paradigms where functionalities and operations can be …
systems calls for novel networking paradigms where functionalities and operations can be …
Resource allocation for co-existence of embb and urllc services in 6g wireless networks: A survey
Next generation of wireless networks are characterized by two main features named
Enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications …
Enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications …
Using distributed reinforcement learning for resource orchestration in a network slicing scenario
The Network Slicing (NS) paradigm enables the partition of physical and virtual resources
among multiple logical networks, possibly managed by different tenants. In such a scenario …
among multiple logical networks, possibly managed by different tenants. In such a scenario …
An in-depth survey on virtualization technologies in 6g integrated terrestrial and non-terrestrial networks
6G networks are envisioned to deliver a large diversity of applications and meet stringent
Quality of Service (QoS) requirements. Hence, integrated Terrestrial and Non-Terrestrial …
Quality of Service (QoS) requirements. Hence, integrated Terrestrial and Non-Terrestrial …