AI models for green communications towards 6G
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
Evolution of NOMA toward next generation multiple access (NGMA) for 6G
Due to the explosive growth in the number of wireless devices and diverse wireless
services, such as virtual/augmented reality and Internet-of-Everything, next generation …
services, such as virtual/augmented reality and Internet-of-Everything, next generation …
The applicability of reinforcement learning methods in the development of industry 4.0 applications
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …
problems. Our article gives a systematic overview of major types of RL methods, their …
On the performance of IRS-assisted multi-layer UAV communications with imperfect phase compensation
This work presents the symbol error rate (SER) and outage probability analysis of multi-layer
unmanned aerial vehicles (UAVs) wireless communications assisted by intelligent reflecting …
unmanned aerial vehicles (UAVs) wireless communications assisted by intelligent reflecting …
Cooperative trajectory design of multiple UAV base stations with heterogeneous graph neural networks
Unmanned aerial vehicles as base stations (UAV-BSs) are recognized as effective means
for tackling eruptive communication service requirements especially when terrestrial …
for tackling eruptive communication service requirements especially when terrestrial …
Deep reinforcement learning-based joint task and energy offloading in UAV-aided 6G intelligent edge networks
Edge networks are expected to play an important role in 6G where machine learning-based
methods are widely applied, which promote the concept of Edge Intelligence. Meanwhile …
methods are widely applied, which promote the concept of Edge Intelligence. Meanwhile …
Joint UAV placement optimization, resource allocation, and computation offloading for THz band: A DRL approach
H Wang, H Zhang, X Liu, K Long… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of internet of things, latency-sensitive applications such as
telemedicine are constantly emerging. Unfortunately, due to the limited computation capacity …
telemedicine are constantly emerging. Unfortunately, due to the limited computation capacity …
Resource allocation in UAV-assisted networks: A clustering-aided reinforcement learning approach
S Zhou, Y Cheng, X Lei, Q Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As an aerial base station, unmanned aerial vehicle (UAV) has been considered as a
promising technology to assist future wireless communications due to its flexible, swift and …
promising technology to assist future wireless communications due to its flexible, swift and …
Graph-embedded multi-agent learning for smart reconfigurable THz MIMO-NOMA networks
With the accelerated development of immersive applications and the explosive increment of
internet-of-things (IoT) terminals, 6G would introduce terahertz (THz) massive multiple-input …
internet-of-things (IoT) terminals, 6G would introduce terahertz (THz) massive multiple-input …
Joint optimization framework for minimization of device energy consumption in transmission rate constrained UAV-assisted IoT network
Due to their high maneuverability and flexible deployment, unmanned aerial vehicles
(UAVs) could be an alternative option for a scenario where Internet of Things (IoT) devices …
(UAVs) could be an alternative option for a scenario where Internet of Things (IoT) devices …