Joint resource management for MC-NOMA: A deep reinforcement learning approach

S Wang, T Lv, W Ni, NC Beaulieu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper presents a novel and effective deep reinforcement learning (DRL)-based
approach to addressing joint resource management (JRM) in a practical multi-carrier non …

Reconfigurable intelligent surface-aided cognitive NOMA networks: Performance analysis and deep learning evaluation

TH Vu, TV Nguyen, DB da Costa… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This paper investigates reconfigurable intelligent surface (RIS)-aided cognitive non-
orthogonal multiple access (NOMA) systems, where an RIS is deployed to serve two users …

AI empowered RIS-assisted NOMA networks: Deep learning or reinforcement learning?

R Zhong, Y Liu, X Mu, Y Chen… - IEEE Journal on Selected …, 2021 - ieeexplore.ieee.org
A reconfigurable intelligent surface (RIS)-assisted multi-user downlink communication
system over fading channels is investigated, where both non-orthogonal multiple access …

Super-modular game-based user scheduling and power allocation for energy-efficient NOMA network

G Liu, R Wang, H Zhang, W Kang… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
In this paper, we consider a single cell downlink non-orthogonal multiple access (NOMA)
network and aim at maximizing the energy efficiency. The energy-efficient resource …

Performance analysis of NOMA-based underlay cognitive radio networks with partial<? brk?> relay selection

V Aswathi, AV Babu - IEEE Transactions on Vehicular …, 2021 - ieeexplore.ieee.org
This paper investigates outage and throughput performance of non-orthogonal multiple
access (NOMA) based underlay cognitive radio (ie, CR-NOMA) network under partial relay …

Sum-rate maximization of wireless powered primary users for cooperative CRNs: NOMA or TDMA at cognitive users?

D Xu, H Zhu - IEEE Transactions on Communications, 2021 - ieeexplore.ieee.org
Recently, wireless powered cooperative cognitive radio networks (CRNs), which combine
the technologies of radio frequency (RF) energy harvesting and CR, have drawn great …

Deep Learning-Based Resource Allocation for Transmit Power Minimization in Uplink NOMA IoT Cellular Networks

HJ Park, HW Kim, SH Chae - IEEE Transactions on Cognitive …, 2023 - ieeexplore.ieee.org
For Internet of Things (IoT) networks, it is important to develop energy-efficient
communication schemes to extend the operating life of battery-powered IoT devices …

Performance of adaptive multi-user underlay NOMA transmission with simple user selection

A Jee, K Janghel, S Prakriya - IEEE Transactions on Cognitive …, 2022 - ieeexplore.ieee.org
In this paper, we demonstrate that despite the power constraints on all transmit nodes
caused by the interference temperature limit (ITL) imposed by the primary user, power …

Multi-agent DRL approach for energy-efficient resource allocation in URLLC-enabled grant-free NOMA systems

DD Tran, SK Sharma, VN Ha… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Grant-free non-orthogonal multiple access (GF-NOMA) has emerged as a promising access
technology for the fifth generation and beyond wireless networks that enable ultra-reliable …

DDPG-based joint resource management for latency minimization in NOMA-MEC networks

J Wang, Y Wang, P Cheng, K Yu… - IEEE Communications …, 2023 - ieeexplore.ieee.org
In this letter, we consider the latency minimization problem in NOMA-MEC networks. Each
user offloads partial tasks to the MEC server for remote execution and processes the …