The next generation heterogeneous satellite communication networks: Integration of resource management and deep reinforcement learning
This article proposes an innovative resource management framework for the next generation
heterogeneous satellite networks (HSNs), which can achieve cooperation between …
heterogeneous satellite networks (HSNs), which can achieve cooperation between …
Intelligent user association for symbiotic radio networks using deep reinforcement learning
In this paper, we are interested in symbiotic radio networks (SRNs), in which an Internet-of-
Things (IoT) network parasitizes in a primary cellular network to achieve spectrum-, energy …
Things (IoT) network parasitizes in a primary cellular network to achieve spectrum-, energy …
Incorporating distributed DRL into storage resource optimization of space-air-ground integrated wireless communication network
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The
effective management of SAGIN resources is a prerequisite for high-reliability …
effective management of SAGIN resources is a prerequisite for high-reliability …
DeepRAT: A DRL-based framework for multi-RAT assignment and power allocation in HetNets
Wireless heterogeneous networks (HetNets), where several systems with multi-radio access
technologies (multi-RATs) coexist for massive multi-connectivity networks, are in service …
technologies (multi-RATs) coexist for massive multi-connectivity networks, are in service …
AoI-aware resource allocation for platoon-based C-V2X networks via multi-agent multi-task reinforcement learning
This paper investigates the problem of age of information (AoI) aware radio resource
management for a platooning system. Multiple autonomous platoons exploit the cellular …
management for a platooning system. Multiple autonomous platoons exploit the cellular …
Resource allocation for joint energy and spectral efficiency in cloud radio access network based on deep reinforcement learning
The rapid increase of user data traffic demand has promoted the telecommunication sector
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …
Dynamic channel access and power control in wireless interference networks via multi-agent deep reinforcement learning
Due to the scarcity in the wireless spectrum and limited energy resources especially in
mobile applications, efficient resource allocation strategies are critical in wireless networks …
mobile applications, efficient resource allocation strategies are critical in wireless networks …
Age-oriented access control in GEO/LEO heterogeneous network for marine IoRT: A deep reinforcement learning approach
With the growing interest in the smart ocean, the satellite-based marine Internet of Remote
Things (IoRT) network has been regarded as a promising architecture for sensory data …
Things (IoRT) network has been regarded as a promising architecture for sensory data …
Intelligent resource allocation for edge-cloud collaborative networks: A hybrid DDPG-D3QN approach
To handle the ever-increasing IoT devices with computation-intensive and delay-critical
applications, it is imperative to leverage the collaborative potential of edge and cloud …
applications, it is imperative to leverage the collaborative potential of edge and cloud …
Joint UAV 3D Trajectory Design and Resource Scheduling for Space-Air-Ground Integrated Power IoRT: A Deep Reinforcement Learning Approach
J Liu, X Zhao, P Qin, F Du, Z Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The terrain-independent space-air-ground integrated power Internet of Remote Things (SAG-
PIoRT) is able to bring efficient communication services with seamless coverage for sensors …
PIoRT) is able to bring efficient communication services with seamless coverage for sensors …