Reinforcement-learning-based resource allocation for energy-harvesting-aided D2D communications in IoT networks
This article proposes a novel approach to improve the energy efficiency (EE) of an energy-
harvesting (EH)-enabled IoT network supported by simultaneous wireless information and …
harvesting (EH)-enabled IoT network supported by simultaneous wireless information and …
Resource allocation scheme for guarantee of QoS in D2D communications using deep neural network
In this letter, we propose a hybrid resource allocation scheme for multi-channel underlay
device-to-device (D2D) communications. In our proposed scheme, the transmit power of …
device-to-device (D2D) communications. In our proposed scheme, the transmit power of …
Power control with qos guarantees: A differentiable projection-based unsupervised learning framework
M Alizadeh, H Tabassum - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep neural networks (DNNs) are emerging as a potential solution to solve NP-hard
wireless resource allocation problems. However, in the presence of intricate constraints, eg …
wireless resource allocation problems. However, in the presence of intricate constraints, eg …
Power control for 6G in-factory subnetworks with partial channel information using graph neural networks
DAR Adeogun, G Berardinelli - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
Transmit power control (PC) will become increasingly crucial in alleviating interference as
the densification of the wireless networks continues towards 6G. However, the practicality of …
the densification of the wireless networks continues towards 6G. However, the practicality of …
Energy- and Spectral-Efficiency Tradeoff With -Fairness in Energy Harvesting D2D Communication
Z Kuang, L Zhang, L Zhao - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
Energy Harvesting (EH) technology enables Device-to-Device (D2D) User Equipments
(DUEs) to harvest energy from ambient energy, making contributions to green …
(DUEs) to harvest energy from ambient energy, making contributions to green …
Deep learning framework for secure communication with an energy harvesting receiver
In this paper, we consider wireless-powered secure communication with an energy
harvesting receiver, which is allowed to harvest energy from the transmitted signals but not …
harvesting receiver, which is allowed to harvest energy from the transmitted signals but not …
Deep learning-based energy efficient resource allocation for underlay cognitive MISO interference channels
In this paper, we investigate a deep learning (DL)-based resource allocation strategy for an
underlay cognitive radio network with multiple-input-single-output interference channels …
underlay cognitive radio network with multiple-input-single-output interference channels …
A stochastic geometry analysis for energy-harvesting-based device-to-device communication
The rapidly developing energy harvesting (EH) technology is a promising solution to the
durability issue in the battery-powered Internet of Things (IoT) systems. In this article …
durability issue in the battery-powered Internet of Things (IoT) systems. In this article …
Deep Learning Framework for Two-Way MISO Wireless-Powered Interference Channels
In this paper, we present a realistic and novel protocol for two-way communication in
multiple-input-single-output (MISO) wireless-powered interference channels, namely, a …
multiple-input-single-output (MISO) wireless-powered interference channels, namely, a …
Multicell power control under rate constraints with deep learning
Y Li, S Han, C Yang - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
In the paper we study a deep learning based method to solve the multicell downlink power
control problem for sum rate maximization subject to per-user rate constraints and per-base …
control problem for sum rate maximization subject to per-user rate constraints and per-base …