Integrated fluid antenna systems with reconfigurable intelligent surfaces via quadratic interpolation optimization

Integrated fluid antenna systems with reconfigurable intelligent surfaces via quadratic interpolation optimization | 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 Integrated fluid antenna systems with reconfigurable intelligent surfaces via quadratic interpolation optimization Ahmed S. Alwakeel, Abdullah Shaheen, Ghareeb Moustafa, Badr Alfaiya, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6775750/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The integration of Reconfigurable Intelligent Surface (RIS) and Fluid Antenna System (FAS) technologies offers a promising solution to the problems facing contemporary wireless networks, such as signal attenuation, interference reduction, and security vulnerabilities. In this paper, an innovative Quadratic Interpolation Optimization Algorithm (QIOA) is developed to improve wireless communication performance and reliability. The designed QIOA, also, seeks for maintaining the security requirements through the simultaneous deployment of FAS and RIS. Rooted in the Generalized Quadratic Interpolation Method (GQIM), the QIOA effectively balances exploration and exploitation within the search space. By leveraging the GQIM, the developed QIOA activates adaptive weight adjustments to dynamically configure RIS elements and fluid-based antennas, optimizing their deployment based on environmental conditions and communication requirements. By optimal deployment of both technologies using the proposed QIOA, the wireless coverage is effectively maximized, the signal strength is improved, and the system reliability is enhanced. Through simulations, QIOA outperformed different algorithms like Differential Evolution (DE), Honey Formation Optimization (HFO), Kepler Optimization Algorithm (KOA), and War Strategy Optimization (WSO) by retaining lower infeasibility rates and obtaining more consistency in optimization outcomes. The proposed QIOA had superior performance as evidenced by a 100% successfulness in finding feasible solution. On the other side, KOA, HFO, WSO and DE fail in achieving feasible solutions with 15%, 30%, 85% and 100%, respectively, of the whole experimental runs. Electrical Engineering Reconfigurable intelligent surfaces Fluid antenna systems Wireless communication Quadratic interpolation optimization algorithm Achievable rate limitation Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6775750","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":463589384,"identity":"c9c0174d-6811-447f-88af-c76b345a5912","order_by":0,"name":"Ahmed S. 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