Reinforcement learning in the sky: A survey on enabling intelligence in ntn-based communications
Non terrestrial networks (NTN) involving 'in the sky'objects such as low-earth orbit satellites,
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
When deep reinforcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5G ultradense …
Recently, smart cities, healthcare system, and smart vehicles have raised challenges on the
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
Resource allocation in 5G cloud‐RAN using deep reinforcement learning algorithms: A review
M Khani, S Jamali, MK Sohrabi… - Transactions on …, 2024 - Wiley Online Library
This paper reviews recent research on resource allocation in 5G cloud‐based radio access
networks (C‐RAN) using deep reinforcement learning (DRL) algorithms. It explores the …
networks (C‐RAN) using deep reinforcement learning (DRL) algorithms. It explores the …
[HTML][HTML] Reinforcement learning-based differential evolution for parameters extraction of photovoltaic models
In photovoltaic (PV) model, it is an urgent problem to control and optimize the accurate
parameters. Hence, many algorithms have been proposed for parameter extraction of …
parameters. Hence, many algorithms have been proposed for parameter extraction of …
Intelligent interactive beam training for millimeter wave communications
Millimeter wave communications, equipped with large-scale antenna arrays, are able to
provide Gbps data rates by exploring abundant spectrum resources. However, the use of a …
provide Gbps data rates by exploring abundant spectrum resources. However, the use of a …
Machine learning techniques in internet of UAVs for smart cities applications
FA Alqurashi, F Alsolami… - Journal of Intelligent …, 2022 - content.iospress.com
Recently, there were much interest in technology which has emerged greatly to the
development of smart unmanned systems. Internet of UAV (IoUAV) enables an unmanned …
development of smart unmanned systems. Internet of UAV (IoUAV) enables an unmanned …
Multi-agent reinforcement learning based distributed transmission in collaborative cloud-edge systems
Millimeter-wave (mmWave) cloud-edge collaboration has emerged as an effective solution
for low-latency transmission by harnessing the potentials of cloud and edge nodes (eNodes) …
for low-latency transmission by harnessing the potentials of cloud and edge nodes (eNodes) …
STAR-RISs assisted NOMA networks: A distributed learning approach
A novel simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-
RISs) aided downlink non-orthogonal multiple access (NOMA) communication framework is …
RISs) aided downlink non-orthogonal multiple access (NOMA) communication framework is …
Energy-efficient ultra-dense 5G networks: recent advances, taxonomy and future research directions
The global surge of connected devices and multimedia services necessitates increased
capacity and coverage of communication networks. One approach to address the …
capacity and coverage of communication networks. One approach to address the …
Distributed data collection in age-aware vehicular participatory sensing networks
The advent of vehicle-to-everything communication facilitates the emergence of vehicular
sensing networks, where vehicles equipped with advanced sensors continuously sample …
sensing networks, where vehicles equipped with advanced sensors continuously sample …