Applications of multi-agent reinforcement learning in future internet: A comprehensive survey
Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
Edge QoE: Computation offloading with deep reinforcement learning for Internet of Things
H Lu, X He, M Du, X Ruan, Y Sun… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
In edge-enabled Internet of Things (IoT), computation offloading service is expected to offer
users with better Quality of Experience (QoE) than traditional IoT. Unfortunately, the growing …
users with better Quality of Experience (QoE) than traditional IoT. Unfortunately, the growing …
3D UAV trajectory and data collection optimisation via deep reinforcement learning
Unmanned aerial vehicles (UAVs) are now beginning to be deployed for enhancing the
network performance and coverage in wireless communication. However, due to the …
network performance and coverage in wireless communication. However, due to the …
RIS-assisted UAV communications for IoT with wireless power transfer using deep reinforcement learning
Many of the devices used in Internet-of-Things (IoT) applications are energy-limited, and
thus supplying energy while maintaining seamless connectivity for IoT devices is of …
thus supplying energy while maintaining seamless connectivity for IoT devices is of …
Proximal policy optimization for RIS-assisted full duplex 6G-V2X communications
In this work, we consider a novel reconfigurable intelligent surface (RIS)-assisted full-duplex
(FD) sixth generation (6G)-vehicle-to-everything (V2X) communication network having a FD …
(FD) sixth generation (6G)-vehicle-to-everything (V2X) communication network having a FD …
Reconfigurable intelligent surface-assisted multi-UAV networks: Efficient resource allocation with deep reinforcement learning
KK Nguyen, SR Khosravirad… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
In this paper, we propose reconfigurable intelligent surface (RIS)-assisted unmanned aerial
vehicles (UAVs) networks that can utilise both advantages of UAV's agility and RIS's …
vehicles (UAVs) networks that can utilise both advantages of UAV's agility and RIS's …
Multiagent deep-reinforcement-learning-based resource allocation for heterogeneous QoS guarantees for vehicular networks
Vehicle-to-vehicle communications can offer direct information interaction, including security-
centered information and entertainment information. However, the rapid proliferation of …
centered information and entertainment information. However, the rapid proliferation of …
Resource-Constrained eXtended Reality Operated With Digital Twin in Industrial Internet of Things
EXtended Reality (XR) alongside the Digital Twin (DT) in Industrial Internet of Things (IIoT)
emerges as a promising next-generation technology. Its diverse applications hod the …
emerges as a promising next-generation technology. Its diverse applications hod the …
[HTML][HTML] A power allocation scheme for MIMO-NOMA and D2D vehicular edge computing based on decentralized DRL
In vehicular edge computing (VEC), some tasks can be processed either locally or on the
mobile edge computing (MEC) server at a base station (BS) or a nearby vehicle. In fact …
mobile edge computing (MEC) server at a base station (BS) or a nearby vehicle. In fact …
Blockchain-based VEC network trust management: A DRL algorithm for vehicular service offloading and migration
To meet the execution requirements of delay-sensitive services in vehicular edge computing
(VEC) networks, vehicular services need to be offloaded to edge computing nodes. For …
(VEC) networks, vehicular services need to be offloaded to edge computing nodes. For …