Maximizing Secrecy Rate in IRS-Assisted Wireless Systems based on Modified Quantum Particle Swarm Optimization Algorithm

Maximizing Secrecy Rate in IRS-Assisted Wireless Systems based on Modified Quantum Particle Swarm Optimization Algorithm | 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 Maximizing Secrecy Rate in IRS-Assisted Wireless Systems based on Modified Quantum Particle Swarm Optimization Algorithm HaoFei Lu, ZiYi Wang, SiYao Chen, XiaoQian Guo, Weigang Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8047887/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 In the modern wireless communication system with multiple antennas located, the presence of eavesdroppers has threaten the security of the entire system. Aiming at the problem of inaccurate phase shift matrix design, we propose an innovative algorithm based on quantum particle swarm optimization to optimize the phase shift matrix of the intelligent reflecting surface. Furthermore, to decrease the problem of unreasonable adjustment of source transmit covariance matrix parameters, we explore a novel precoding and decomposition technology to optimize the beamforming vector. In addition, by using precoding technology, we improve a QPSO strategy to successfully suppress the influence of eavesdroppers and enhance the capacity of legal channels. Simulation results have testified that under low power conditions, our algorithms are significantly better than traditional schemes in terms of secrecy rate performance. Intelligent reflecting surface quantum particle swarm optimization secrecy rate physical layer security Full Text Additional Declarations No competing interests reported. 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-8047887","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":550661181,"identity":"e21e148c-176e-416e-8154-7a92dddac9cf","order_by":0,"name":"HaoFei Lu","email":"","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"HaoFei","middleName":"","lastName":"Lu","suffix":""},{"id":550661182,"identity":"edd5e563-de7c-4247-996d-1e20e9ff1bdd","order_by":1,"name":"ZiYi Wang","email":"","orcid":"","institution":"Nanjing University of Posts and 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