QoE based Joint Adaptive User Grouping and Power Allocation in Indoor VLC-NOMA Network

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Abstract The growing demand for high data rate and the increasing scarcity of spectrum resources have attracted non-orthogonal multiple access (NOMA) into visible light communication (VLC) network. For improving user’s quality of experience (QoE) in VLC-NOMA network, a joint optimization problem of user grouping and power allocation is formulated to maximize the sum mean opinion scores (MOS) of users in the VLC-NOMA network. Then, we decompose it into an inner power allocation and an outer user grouping subproblems. For the inner power allocation subproblem, we propose a power adjustment-based power allocation (PAPA) algorithm to guaranteeing the QoE and successive interference cancellation (SIC). For the outer user grouping subproblem, a hierarchical agglomerative clustering-based (HAC) user grouping algorithm is proposed that users can adaptively select NOMA groups and transmission modes. Then, we propose a joint adaptive user grouping and power allocation (JAUGPA) algorithm to solve user grouping and power allocation iteratively. The simulation results show that the proposed algorithm can increase the sum MOS and guarantee the fairness of users in the VLC-NOMA network.
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QoE based Joint Adaptive User Grouping and Power Allocation in Indoor VLC-NOMA Network | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article QoE based Joint Adaptive User Grouping and Power Allocation in Indoor VLC-NOMA Network Huanlin Liu, Wencai Wang, Haonan Chen, Yong Chen, Yangyang Hou, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7332921/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Apr, 2026 Read the published version in Telecommunication Systems → Version 1 posted 10 You are reading this latest preprint version Abstract The growing demand for high data rate and the increasing scarcity of spectrum resources have attracted non-orthogonal multiple access (NOMA) into visible light communication (VLC) network. For improving user’s quality of experience (QoE) in VLC-NOMA network, a joint optimization problem of user grouping and power allocation is formulated to maximize the sum mean opinion scores (MOS) of users in the VLC-NOMA network. Then, we decompose it into an inner power allocation and an outer user grouping subproblems. For the inner power allocation subproblem, we propose a power adjustment-based power allocation (PAPA) algorithm to guaranteeing the QoE and successive interference cancellation (SIC). For the outer user grouping subproblem, a hierarchical agglomerative clustering-based (HAC) user grouping algorithm is proposed that users can adaptively select NOMA groups and transmission modes. Then, we propose a joint adaptive user grouping and power allocation (JAUGPA) algorithm to solve user grouping and power allocation iteratively. The simulation results show that the proposed algorithm can increase the sum MOS and guarantee the fairness of users in the VLC-NOMA network. VLC-NOMA network QoE Hierarchical agglomerative clustering User grouping Power allocation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Apr, 2026 Read the published version in Telecommunication Systems → Version 1 posted Editorial decision: Revision requested 27 Nov, 2025 Reviews received at journal 21 Nov, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviews received at journal 12 Oct, 2025 Reviewers agreed at journal 18 Sep, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviewers invited by journal 16 Sep, 2025 Editor assigned by journal 12 Aug, 2025 Submission checks completed at journal 12 Aug, 2025 First submitted to journal 09 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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