Artificial intelligence, machine learning and big data in natural resources management: a comprehensive bibliometric review of literature spanning 1975–2022
Applying artificial intelligence (AI), machine learning (ML), and big data to natural resource
management (NRM) is revolutionizing how natural resources are managed. To gain more …
management (NRM) is revolutionizing how natural resources are managed. To gain more …
Deep reinforcement learning for resource allocation in multi-band and hybrid OMA-NOMA wireless networks
Exploiting the advantages of both non-orthogonal multiple access technique and millimeter-
wave communications requires joint efficient resource allocation techniques toward …
wave communications requires joint efficient resource allocation techniques toward …
Joint ddpg and unsupervised learning for channel allocation and power control in centralized wireless cellular networks
M Sun, E Mei, S Wang, Y Jin - Ieee Access, 2023 - ieeexplore.ieee.org
In order to solve the resource allocation problem in scenarios of centralized wireless cellular
communication with multiple cells, users and channels, a novel resource allocation …
communication with multiple cells, users and channels, a novel resource allocation …
Soft frequency reuse with allocation of resource plans based on machine learning in the networks with flying base stations
MS Hossain, Z Becvar - IEEE Access, 2021 - ieeexplore.ieee.org
Flying base stations (FlyBSs) enable ubiquitous communications in the next generation
mobile networks with a flexible topology. However, a deployment of the FlyBSs intensifies …
mobile networks with a flexible topology. However, a deployment of the FlyBSs intensifies …
Joint deep reinforcement learning and unsupervised learning for channel selection and power control in D2D networks
M Sun, Y Jin, S Wang, E Mei - Entropy, 2022 - mdpi.com
Device-to-device (D2D) technology enables direct communication between devices, which
can effectively solve the problem of insufficient spectrum resources in 5G communication …
can effectively solve the problem of insufficient spectrum resources in 5G communication …
Experience replay-based power control for sum-rate maximization in multi-cell networks
A Anzaldo, ÁG Andrade - IEEE Wireless Communications …, 2022 - ieeexplore.ieee.org
Power allocation algorithms are implemented to deal with spectrum sharing interference.
Deep Reinforcement Learning-based models have recently been used in unpredictable …
Deep Reinforcement Learning-based models have recently been used in unpredictable …
User and resource allocation in latency constrained Xhaul via reinforcement learning
MN Chughtai, S Noor, I Laurinavicius… - Journal of Optical …, 2023 - opg.optica.org
The Flexible Ethernet (FlexE) is envisioned for the provisioning of different services and hard
slicing of the Xhaul in 5G and beyond networks. For efficient bandwidth utilization in the …
slicing of the Xhaul in 5G and beyond networks. For efficient bandwidth utilization in the …
A Collaborative Multi-agent Deep Reinforcement Learning-based Wireless Power Allocation with Centralized Training and Decentralized Execution
Despite the success of Deep Reinforcement Learning (DRL) in radio-resource management
within multi-cell wireless networks, applying it to power allocation in ultra-dense 5G and …
within multi-cell wireless networks, applying it to power allocation in ultra-dense 5G and …
On Reward Shaping Methods in Deep Reinforcement Learning for Radio Resource Management in Wireless Networks
This paper provides a comprehensive study on the learning models' power violation, sum-
rate performance while taking into consideration power constraint, and computational …
rate performance while taking into consideration power constraint, and computational …
On Effectiveness of Exploration Strategies in Deep Reinforcement Learning for Power Allocation in Multi-Carrier Wireless Systems
This paper presents a comprehensive study on the efficiency and effectiveness of
exploration policies for deep reinforcement (DRL) algorithms with applications to the power …
exploration policies for deep reinforcement (DRL) algorithms with applications to the power …