IRS assisted NOMA aided mobile edge computing with queue stability: Heterogeneous multi-agent reinforcement learning

J Yu, Y Li, X Liu, B Sun, Y Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
By employing powerful edge servers for data processing, mobile edge computing (MEC) has
been recognized as a promising technology to support emerging computation-intensive …

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 …

Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends

HMF Noman, E Hanafi, KA Noordin, K Dimyati… - IEEE …, 2023 - ieeexplore.ieee.org
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …

Multi-agent reinforcement learning for dynamic resource management in 6G in-X subnetworks

X Du, T Wang, Q Feng, C Ye, T Tao… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The 6G network enables a subnetwork-wide evolution, resulting in a “network of
subnetworks”. However, due to the dynamic mobility of wireless subnetworks, the data …

Dynamic spectrum access for internet-of-things based on federated deep reinforcement learning

F Li, B Shen, J Guo, KY Lam, G Wei… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The explosive growth of Internet-of-Things (IoT) applications such as smart cities and
Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating …

Double-layer power control for mobile cell-free XL-MIMO with multi-agent reinforcement learning

Z Liu, J Zhang, Z Liu, H Xiao, B Ai - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Cell-free (CF) extremely large-scale multiple-input multiple-output (XL-MIMO) is regarded as
a promising technology for enabling future wireless communication systems. Significant …

Design and Optimization of RSMA for Coexisting HTC/MTC in 6G and Future Networks

S Zhang, J Liu, Z Shi, J Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the fast development of emerging Internet of Everything applications, human-type
communications (HTC) and machine-type communications (MTC) will inevitably coexist in …

A mixed-bouncing based non-stationary model for 6G massive MIMO mmWave UAV channels

L Bai, Z Huang, L Cui, T Feng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This paper proposes a novel three-dimensional (3D) mixed-bouncing based unmanned
aerial vehicle (UAV) channel model with space-time-frequency (STF) non-stationarity for …

Sparse code multiple access assisted resource allocation for 5G V2X communications

Z Shi, J Liu - IEEE Transactions on Communications, 2022 - ieeexplore.ieee.org
In 5G vehicle-to-everything (V2X) systems, the scarcity of spectrum resources and the
inefficiency of resource allocation make vehicle-to-vehicle (V2V) communications that …

Reinforcement learning based RSS-threshold optimization for D2D-aided HTC/MTC in dense NOMA systems

S Zhang, X Wang, Z Shi, J Liu - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
To fulfill the stringent requirements brought by human-type communication (HTC) along with
massive machine-type communication (MTC), device-to-device (D2D) and non-orthogonal …