The role of artificial intelligence and machine learning in wireless networks security: Principle, practice and challenges
Security is one of the biggest challenges concerning networks and communications. The
problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence …
problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence …
Reinforcement learning for real-time optimization in NB-IoT networks
NarrowBand Internet of Things (NB-IoT) is an emerging cellular-based technology that offers
a range of flexible configurations for massive IoT radio access from groups of devices with …
a range of flexible configurations for massive IoT radio access from groups of devices with …
A survey on NB-IoT random access: approaches for uplink radio access network congestion management
L Iiyambo, G Hancke, AM Abu-Mahfouz - IEEE Access, 2024 - ieeexplore.ieee.org
Narrowband Internet of Things (NB-IoT) is one of the most promising technologies for
enabling reliable communication among low-power, and low cost devices present in …
enabling reliable communication among low-power, and low cost devices present in …
Dynamic backoff collision resolution for massive M2M random access in cellular IoT networks
HD Althumali, M Othman, NK Noordin… - IEEE Access, 2020 - ieeexplore.ieee.org
The deployment of machine-to-machine (M2M) communications on cellular networks
provides ubiquitous services to Internet-of-Things (IoT) systems. Cellular networks have …
provides ubiquitous services to Internet-of-Things (IoT) systems. Cellular networks have …
Joint control of random access and dynamic uplink resource dimensioning for massive MTC in 5G NR based on SCMA
The massive machine-type communication (mMTC) usage scenario, also known as the
massive Internet of Things (mIoT), involves a huge number of MTC devices having high …
massive Internet of Things (mIoT), involves a huge number of MTC devices having high …
A decoupled learning strategy for massive access optimization in cellular IoT networks
Cellular-based networks are expected to offer connectivity for massive Internet of Things
(mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from …
(mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from …
Deep reinforcement learning-based access class barring for energy-efficient mMTC random access in LTE networks
ATH Bui, AT Pham - IEEE Access, 2020 - ieeexplore.ieee.org
Long-Term Evolution (LTE) networks are expected to be a key enabler for the massive
Machine-Type Communications (mMTC) service in the 5G context. As highly synchronized …
Machine-Type Communications (mMTC) service in the 5G context. As highly synchronized …
[HTML][HTML] Deep Reinforcement Learning for QoS provisioning at the MAC layer: A Survey
Abstract Quality of Service (QoS) provisioning is based on various network management
techniques including resource management and medium access control (MAC). Various …
techniques including resource management and medium access control (MAC). Various …
Traffic prediction and random access control optimization: Learning and non-learning-based approaches
Random access channel (RACH) procedures in modern wireless communications are
generally based on multi-channel slotted-ALOHA, which can be optimized by flexibly …
generally based on multi-channel slotted-ALOHA, which can be optimized by flexibly …
[PDF][PDF] Mitigating the massive access problem in the internet of things
The traffic from the large number of IoT devices connected to the IoT is a source of
congestion known as the Massive Access Problem (MAP), that results in packet losses …
congestion known as the Massive Access Problem (MAP), that results in packet losses …