Next-gen resource optimization in NB-IoT networks: Harnessing soft actor-critic reinforcement learning
S Anbazhagan, RK Mugelan - Computer Networks, 2024 - Elsevier
Abstract Resource allocation in Narrowband Internet of Things (NB-IoT) networks is a
complex challenge due to dynamic user demands, variable channel conditions, and …
complex challenge due to dynamic user demands, variable channel conditions, and …
Reinforcement learning-enabled cross-layer optimization for low-power and lossy networks under heterogeneous traffic patterns
The next generation of the Internet of Things (IoT) networks is expected to handle a massive
scale of sensor deployment with radically heterogeneous traffic applications, which leads to …
scale of sensor deployment with radically heterogeneous traffic applications, which leads to …
[HTML][HTML] Energy-efficient joint resource allocation in 5G HetNet using Multi-Agent Parameterized Deep Reinforcement learning
Small cells are a promising technique to improve the capacity and throughput of future
wireless networks. However, user association and power allocation in heterogeneous …
wireless networks. However, user association and power allocation in heterogeneous …
Distributed multi-agent empowered resource allocation in deep edge networks
The sixth generation wireless communication networks (6G) are anticipated to bring a
disruptive innovation on multiple scenarios, where deep edge networks (DENs) turn into a …
disruptive innovation on multiple scenarios, where deep edge networks (DENs) turn into a …
Multi-granularity fusion resource allocation algorithm based on dual-attention deep reinforcement learning and lifelong learning architecture in heterogeneous IIoT
Y Wang, F Shang, J Lei - Information Fusion, 2023 - Elsevier
Deep reinforcement learning (DRL) is a promising technology to address the resource
allocation problem for efficient data transmission in complex network environments …
allocation problem for efficient data transmission in complex network environments …
Deep Q-network based resource allocation for UAV-assisted ultra-dense networks
With the rapid development of the fifth-generation (5G) wireless communications, the
number of users is increasing dramatically and Ultra-Dense Networks (UDN) are becoming …
number of users is increasing dramatically and Ultra-Dense Networks (UDN) are becoming …
Joint task offloading and resource allocation for mobile edge computing in ultra-dense network
Mobile edge computing (MEC) enabled user-centric ultra-dense network (UDN) is a
promising solution to the energy constrained mobile users with delay-sensitive and …
promising solution to the energy constrained mobile users with delay-sensitive and …
A fully distributed and clustered learning of power control in user-centric ultra-dense HetNets
In this paper, we investigate a power control of uplink connection in the user-centric ultra-
dense heterogeneous networks (HetNets), which are studied as different types of access …
dense heterogeneous networks (HetNets), which are studied as different types of access …
DA-DRLS: Drift adaptive deep reinforcement learning based scheduling for IoT resource management
In order to fulfill the tremendous resource demand by diverse IoT applications, the large-
scale resource-constrained IoT ecosystem requires a robust resource management …
scale resource-constrained IoT ecosystem requires a robust resource management …
Joint uplink and downlink power allocation for maximizing the energy efficiency in ultra-dense networks
U Mir - International Journal of Information Technology, 2022 - Springer
Ultra-dense network (UDN) is a promising solution to meet the huge data requirements of
future 5G wireless communication systems. With many irregularly deployed small cell base …
future 5G wireless communication systems. With many irregularly deployed small cell base …