[HTML][HTML] Deep Reinforcement Learning-Based Power Allocation for Minimizing Age of Information and Energy Consumption in Multi-Input Multi-Output and Non …

Q Wu, Z Zhang, H Zhu, P Fan, Q Fan, H Zhu, J Wang - Sensors, 2023 - mdpi.com
Multi-input multi-output and non-orthogonal multiple access (MIMO-NOMA) Internet-of-
Things (IoT) systems can improve channel capacity and spectrum efficiency distinctly to …

Deep Reinforcement Learning Based Power Allocation for Minimizing AoI and Energy Consumption in MIMO-NOMA IoT Systems

H Zhu, Q Wu, Q Fan, P Fan, J Wang, Z Li - arXiv preprint arXiv:2303.06411, 2023 - arxiv.org
Multi-input multi-out and non-orthogonal multiple access (MIMO-NOMA) internet-of-things
(IoT) systems can improve channel capacity and spectrum efficiency distinctly to support the …

Distributed reinforcement learning for age of information minimization in real-time IoT systems

S Wang, M Chen, Z Yang, C Yin… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
In this paper, the problem of minimizing the weighted sum of age of information (AoI) and
total energy consumption of Internet of Things (IoT) devices is studied. In the considered …

Deep Reinforcement Learning-Assisted NOMA Age-Optimal Power Allocation for S-IoT Network

Q Liu, J Jiao, S Wu, R Lu… - ICC 2022-IEEE …, 2022 - ieeexplore.ieee.org
In this paper, we consider a satellite-based Internet of Things (S-IoT) network under
shadowed-Rician fading channels, where a satellite transmits timely status updates to …

On the minimization of non-linear age of information in the internet of things

T Park, W Saad, B Zhou - ICC 2021-IEEE International …, 2021 - ieeexplore.ieee.org
In this paper, a novel centralized resource allocation scheme is proposed to enable a
wireless base station to adapt to heterogeneous Internet of Things (IoT) environments and …

Energy-Efficient Scheduling and Resource Allocation for Power-limited Cognitive IoT Devices

K Wang, P Wu, M Xia - 2023 19th International Conference on …, 2023 - ieeexplore.ieee.org
Energy-efficient scheduling and resource allocation strategies help reduce interference and
extend the lifetime of power-limited Internet of Things (IoT) devices. This paper focuses on …

[HTML][HTML] AoI-aware resource scheduling for industrial IoT with deep reinforcement learning

H Li, L Tang, S Chen, L Zheng, S Zhong - Electronics, 2024 - mdpi.com
Effective resource scheduling methods in certain scenarios of Industrial Internet of Things
are pivotal. In time-sensitive scenarios, Age of Information is a critical indicator for measuring …

Optimizing information freshness in RIS-assisted NOMA-based IoT networks

A Muhammad, M Elhattab, MA Arfaoui… - arXiv preprint arXiv …, 2022 - arxiv.org
This paper investigates the benefits of integrating reconfigurable intelligent surface (RIS) on
minimizing the average sum age of information (AoI) in uplink non-orthogonal multiple …

AoI-oriented Resource Allocation for NOMA-based Wireless Powered Cognitive Radio Networks based on Multi-agent Deep Reinforcement Learning

T He, Y Peng, Y Liu, H Song - IEEE Access, 2024 - ieeexplore.ieee.org
In this paper, we study a wireless powered cognitive internet of things (IoT) network, where
cognitive radio (CR) and non-orthogonal multiple access (NOMA) technologies are …

NOMA Versus OMA: Scheduling to Minimize the Age of Information

P Agarwal, S Moharir - IEEE Transactions on Vehicular …, 2023 - ieeexplore.ieee.org
In this work, we consider multiple internet-of-things devices (IoTDs) sensing and reporting
the status of a time-varying signal to a central node. We analytically compare the …