Evidence map›Paper›PMID 42384736›Full record

ArticlePloS one2026

Double DQN-based secrecy energy efficiency and fairness performance in IRS-assisted NOMA systems with friendly jamming.

Hong Nguyen-Thi, Ngan Chu-Thi, Sang Quang-Nguyen, Dung Tran-Tien, Anh Le-Thi

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Hong Nguyen-ThiPosts and Telecommunications Institute of Technology, Hanoi, Vietnam.ORCID https://orcid.org/0009-0005-6063-5790
Ngan Chu-ThiSchool of Information and Communication, Hanoi University of Industry, Hanoi, Vietnam.
Sang Quang-NguyenPosts and Telecommunications Institute of Technology, Ho Chi Minh City, Vietnam.ORCID https://orcid.org/0000-0002-1798-2296
Dung Tran-TienSchool of Information and Communication, Hanoi University of Industry, Hanoi, Vietnam.
Anh Le-ThiSchool of Information and Communication, Hanoi University of Industry, Hanoi, Vietnam.ORCID https://orcid.org/0000-0001-9404-1417

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Faced with the challenge of increasing energy consumption and the need for sustainability in 6th generation (6G) wireless communication networks, this paper investigates the secrecy energy efficiency (SEE) and user fairness performance in an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) system in the presence of a friendly jammer and a passive eavesdropper over THz-Rician channels. We formulate both optimization objectives: maximizing the system's total SEE and maximizing the maximum-min SEE to guarantee fairness for the worst-case user. Additionally, Jain's fairness index is used to quantitatively evaluate the SEE balance among users. To solve these problems, we apply a Double Deep Q-Network (Double DQN)-based SEE of our proposed system model to jointly optimize power allocation and IRS phase shifts. This proposed approach enables efficient learning of optimal policies in dynamic environments without requiring explicit knowledge of the channel distribution. Furthermore, conventional Deep Q-Netowrk (DQN) and random allocation strategies are also implemented for comparison with Double DQN. Simulation results are presented for both IRS-assisted NOMA and OMA (orthogonal multiple access) systems to highlight the advantages of NOMA in terms of the secrecy-energy trade-off and spectral efficiency. Finally, the effects of system essential parameters, such as transmitted power, the number of IRS elements, atmospheric absorption coefficients, and the passive eavesdropper's position, are examined. These simulation results show that the proposed Double DQN-based scheme significantly outperforms DQN and random methods in both SEE maximization and fairness enhancement, and that the NOMA system outperforms the OMA system. These findings confirm that the proposed model provides a basis for deploying a secure, energy-efficient, and sustainable wireless communication for future 6G networks.

Indexed as

Computer Communication NetworksWireless TechnologyAlgorithmsComputer Simulation

Identifiers

PMID42384736
PMCPMC13322567

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.