Deep reinforcement learning powered IRS-assisted downlink NOMA
In this work, we examine an intelligent reflecting surface (IRS) assisted downlink non-
orthogonal multiple access (NOMA) scenario intending to maximize the sum-rate of users …
orthogonal multiple access (NOMA) scenario intending to maximize the sum-rate of users …
Optimal resource allocation for RF-powered underlay cognitive radio networks with ambient backscatter communication
Y Zhuang, X Li, H Ji, H Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we study radio frequency (RF)-powered underlay cognitive radio networks
(CRNs) with power-domain non-orthogonal multiple access (NOMA). In these networks, by …
(CRNs) with power-domain non-orthogonal multiple access (NOMA). In these networks, by …
Multi‐agent deep reinforcement learning‐based energy efficient power allocation in downlink MIMO‐NOMA systems
S Jo, C Jong, C Pak, H Ri - IET Communications, 2021 - Wiley Online Library
NOMA and MIMO are considered to be the promising technologies to meet huge access
demands and high data rate requirements of 5G wireless networks. In this paper, the power …
demands and high data rate requirements of 5G wireless networks. In this paper, the power …
Learning-assisted optimization for energy-efficient scheduling in deadline-aware NOMA systems
In this paper, we study a class of minimum-energy scheduling problems in non-orthogonal
multiple access (NOMA) systems. NOMA is adopted to enable efficient channel utilization …
multiple access (NOMA) systems. NOMA is adopted to enable efficient channel utilization …
Cognitive non-orthogonal multiple access with energy harvesting: An optimal resource allocation approach
We consider a cognitive radio system, in which a secondary transmitter harvests energy from
a primary transmitter's RF signal. The secondary transmitter, which provides decode-and …
a primary transmitter's RF signal. The secondary transmitter, which provides decode-and …
Resource allocation for NOMA-MEC systems in ultra-dense networks: A learning aided mean-field game approach
Attracted by the advantages of multi-access edge computing (MEC) and non-orthogonal
multiple access (NOMA), this article studies the resource allocation problem of a NOMA …
multiple access (NOMA), this article studies the resource allocation problem of a NOMA …
[HTML][HTML] Achievable rate optimization for space–time block code-aided cooperative NOMA with energy harvesting
Cooperative non-orthogonal multiple access (C-NOMA) is one of the promising techniques
that support the massive connectivity of users and improve the fair allocation of network …
that support the massive connectivity of users and improve the fair allocation of network …
Machine learning for user partitioning and phase shifters design in RIS-aided NOMA networks
A novel reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access
(NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic …
(NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic …
Wireless powered cognitive NOMA-based IoT relay networks: Performance analysis and deep learning evaluation
In this article, we study novel wireless powered cognitive nonorthogonal multiple access
(NOMA)-based Internet-of-Things (IoT) relay networks to improve the performance of a cell …
(NOMA)-based Internet-of-Things (IoT) relay networks to improve the performance of a cell …
Deep cognitive perspective: Resource allocation for NOMA-based heterogeneous IoT with imperfect SIC
The Internet of Things (IoT) has attracted significant attentions in the fifth generation mobile
networks and the smart cities. However, considering the large numbers of connectivity …
networks and the smart cities. However, considering the large numbers of connectivity …