The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
基于智能反射面辅助的无线供电通信网络鲁棒能效最大化算法
徐勇军， 高正念， 王茜竹， 周继华， 黄东 - 电子与信息学报, 2022 - jeit.ac.cn
为了解决能量收集效率易受到障碍物阻挡和信道不确定性影响的问题, 该文提出一种基于智能
反射面(IRS) 辅助的无线供电通信网络鲁棒能效(EE) 最大化算法. 首先, 考虑最小收集能量, IRS …
反射面(IRS) 辅助的无线供电通信网络鲁棒能效(EE) 最大化算法. 首先, 考虑最小收集能量, IRS …
Robust resource allocation algorithm for energy-harvesting-based D2D communication underlaying UAV-assisted networks
Energy efficiency (EE) is a significant performance indicator in unmanned aerial vehicle
(UAV)-assisted communication networks for providing a balance between power …
(UAV)-assisted communication networks for providing a balance between power …
[HTML][HTML] A survey on communication protocols and performance evaluations for Internet of Things
Abstract The Internet of Things (IoT) is a large-scale network of devices capable of sensing,
data processing, and communicating with each other through different communication …
data processing, and communicating with each other through different communication …
Pairing distance resolution and power control for massive connectivity improvement in NOMA systems
S Mounchili, S Hamouda - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
One of the main objectives of 5G is to ensure very high spectral efficiency. Non-Orthogonal
Multiple Access (NOMA) is one of the promising techniques to address this issue. Generally …
Multiple Access (NOMA) is one of the promising techniques to address this issue. Generally …
Federated learning for automatic modulation classification under class imbalance and varying noise condition
Automatic modulation classification (AMC) is a promising technology for identifying
modulation types, and deep learning (DL)-based AMC is one of its main research directions …
modulation types, and deep learning (DL)-based AMC is one of its main research directions …
Transfer learning for semi-supervised automatic modulation classification in ZF-MIMO systems
Automatic modulation classification (AMC) is an essential technology for the non-
cooperative communication systems, and it is widely applied into various communications …
cooperative communication systems, and it is widely applied into various communications …
Network slicing enabled resource management for service-oriented ultra-reliable and low-latency vehicular networks
Network slicing has been considered as a promising candidate to provide customized
services for vehicular applications that have extremely high requirements of latency and …
services for vehicular applications that have extremely high requirements of latency and …
Robust secure energy-efficiency optimization in SWIPT-aided heterogeneous networks with a nonlinear energy-harvesting model
Secure information transmission and energy efficiency (EE) optimization are very important
for simultaneous wireless information and power transfer (SWIPT)-aided heterogeneous …
for simultaneous wireless information and power transfer (SWIPT)-aided heterogeneous …
Resource and power allocation in SWIPT-enabled device-to-device communications based on a nonlinear energy harvesting model
Due to the limited battery capacity in mobile devices, simultaneous wireless information and
power transfer (SWIPT) has been proposed as a promising solution to improve the energy …
power transfer (SWIPT) has been proposed as a promising solution to improve the energy …