Multi-agent DRL-based task offloading in multiple RIS-aided IoV networks
This article considers an internet of vehicles (IoV) network, where multi-access edge
computing (MAEC) servers are deployed at base stations (BSs) aided by multiple …
computing (MAEC) servers are deployed at base stations (BSs) aided by multiple …
A long short-term memory network-based radio resource management for 5G network
Nowadays, the Long-Term Evolution-Advanced system is widely used to provide 5G
communication due to its improved network capacity and less delay during communication …
communication due to its improved network capacity and less delay during communication …
MUTS-based cooperative target stalking for a multi-USV system
C Wang, Y Wang, QL Han, Y Wu - IEEE/CAA Journal of …, 2022 - ieeexplore.ieee.org
This paper is concerned with the cooperative target stalking for a multi-unmanned surface
vehicle (multi-USV) system. Based on the multi-agent deep deterministic policy gradient …
vehicle (multi-USV) system. Based on the multi-agent deep deterministic policy gradient …
Deep reinforcement learning-based sum rate fairness trade-off for cell-free mMIMO
The uplink of a cell-free massive multiple-input multiple-output with maximum-ratio
combining (MRC) and zero-forcing (ZF) schemes are investigated. A power allocation …
combining (MRC) and zero-forcing (ZF) schemes are investigated. A power allocation …
Improving the performance of tasks offloading for internet of vehicles via deep reinforcement learning methods
With the rapid development of communication technologies, the quality of our daily life has
been improved with the applications of smart communications and networking, such as …
been improved with the applications of smart communications and networking, such as …
QoS and energy-efficiency aware scheduling and resource allocation scheme in LTE-A uplink systems
C Jong, YC Kim, JH So, KC Ri - Telecommunication Systems, 2023 - Springer
With the fast evolution of the wireless communications, the energy consumption of mobile
network and the data flow in the network are increasing. Thus, it is very important to increase …
network and the data flow in the network are increasing. Thus, it is very important to increase …
Scalable-MADDPG-Based Cooperative Target Invasion for a Multi-USV System
CC Wang, YL Wang, P Shi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This article concentrates on proposing a scalable deep reinforcement learning (DRL)
method for a multiple unmanned surface vehicle (multi-USV) system to operate cooperative …
method for a multiple unmanned surface vehicle (multi-USV) system to operate cooperative …
Joint Power Allocation and User Fairness Optimization for Reinforcement Learning Over mmWave-NOMA Heterogeneous Networks
In this paper, the problem of joint power allocation and user fairness is investigated for an
mmWave heterogeneous network (HetNet) including hybrid non-orthogonal multiple access …
mmWave heterogeneous network (HetNet) including hybrid non-orthogonal multiple access …
A reinforcement learning based energy optimization approach for household fridges
JP Giraldo-Pérez, R Mejía-Gutiérrez… - Sustainable Energy, Grids …, 2023 - Elsevier
The use of machine learning algorithms for the control of schedulable loads like Heating,
ventilation, and air conditioning (HVAC), illumination, dryers and irrigation systems to …
ventilation, and air conditioning (HVAC), illumination, dryers and irrigation systems to …
Maximizing the Downlink Data Rates in Massive Multiple Input Multiple Output with Frequency Division Duplex Transmission Mode Using Power Allocation …
The expected development of the future generation of wireless communications systems
such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) …
such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) …