Make smart decisions faster: Deciding D2D resource allocation via stackelberg game guided multi-agent deep reinforcement learning
Device-to-Device (D2D) communication enabling direct data transmission between two
mobile users has emerged as a vital component for 5G cellular networks to improve …
mobile users has emerged as a vital component for 5G cellular networks to improve …
Deep reinforcement learning based power allocation for D2D network
Z Bi, W Zhou - 2020 IEEE 91st vehicular technology conference …, 2020 - ieeexplore.ieee.org
In device-to-device (D2D) networks, when D2D communication shares cellular network
spectrum resources, it will cause serious co-channel interference. The problem of solving …
spectrum resources, it will cause serious co-channel interference. The problem of solving …
Multi-agent deep reinforcement learning-based power control and resource allocation for D2D communications
H Xiang, Y Yang, G He, J Huang… - IEEE Wireless …, 2022 - ieeexplore.ieee.org
Device-to-device (D2D) communications are envisioned as a critical technology to support
future ubiquitous mobile communications applications. However, the requirements of high …
future ubiquitous mobile communications applications. However, the requirements of high …
Multi-agent deep reinforcement learning based spectrum allocation for D2D underlay communications
Device-to-device (D2D) communication underlay cellular networks is a promising technique
to improve spectrum efficiency. In this situation, D2D transmission may cause severe …
to improve spectrum efficiency. In this situation, D2D transmission may cause severe …
A multi-agent deep reinforcement learning based spectrum allocation framework for D2D communications
Device-to-device (D2D) communication has been recognized as a promising technique to
improve spectrum efficiency. However, D2D transmission as an underlay causes severe …
improve spectrum efficiency. However, D2D transmission as an underlay causes severe …
[HTML][HTML] Joint resource allocation and power control for D2D communication with deep reinforcement learning in MCC
Mission-critical communication (MCC) is one of the main goals in 5G, which can leverage
multiple device-to-device (D2D) connections to enhance reliability for mission-critical …
multiple device-to-device (D2D) connections to enhance reliability for mission-critical …
Weighted cooperative reinforcement learning‐based energy‐efficient autonomous resource selection strategy for underlay D2D communication
Underlay Device‐to‐Device (D2D) communication is a key technology responsible for high
data rate, ultra‐low latency with high spectral and energy efficiency in 5G cellular networks …
data rate, ultra‐low latency with high spectral and energy efficiency in 5G cellular networks …
Cooperative reinforcement learning for adaptive power allocation in device-to-device communication
Mobile devices are an intrinsic part of the Internet of Things (IoT) paradigm. Device-to-device
(D2D) communication is emerging as one of the viable solutions for the radio resource …
(D2D) communication is emerging as one of the viable solutions for the radio resource …
Deep reinforcement learning for channel selection and power control in D2D networks
As a promising candidate to alleviate the mobile traffic explosion, device-to-device (D2D)
technology enables the direct communications between proximal devices. To mitigate the …
technology enables the direct communications between proximal devices. To mitigate the …
Deep reinforcement learning empowered joint mode selection and resource allocation for RIS-aided D2D communications
L Guo, J Jia, J Chen, A Du, X Wang - Neural Computing and Applications, 2023 - Springer
Abstract Device-to-device (D2D) communication has been regarded as a promising solution
to alleviate the mobile traffic explosion problem for its capabilities of improving system data …
to alleviate the mobile traffic explosion problem for its capabilities of improving system data …
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