Enhancing Security of Cognitive Radio Network with Rate Splitting
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This paper applies rate splitting with constructive interference precoding to enhance cognitive radio network security against eavesdroppers, demonstrating superior performance over zero forcing precoding.
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This preprint studies physical-layer security in cognitive radio networks with an eavesdropper by applying rate splitting, where each transmitted message is divided into common and private parts, enabling general decoding of the common portion and restricted decoding of the private portion by the intended user. The authors derive a mathematical model including a closed-form analytical expression for secrecy capacity, and then evaluate two precoding approaches combined with rate splitting: constructive interference (CI) precoding and zero forcing (ZF) precoding. They report that CI with rate splitting outperforms ZF with rate splitting. The paper is not peer reviewed, which is a stated limitation of its current form. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
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Abstract
In this paper, Rate Splitting (RS) technique has been proposed in Cognitive Radio Network (CRN) in the presence of eavesdropper. Applying RS the message transmitted from Primary User (PU) and Secondary User (SU) are splitted into common and private parts where the common message can be decoded by any one whereas the private one can only be decoded by the intended user. Authors are interested to develop a mathematical model consists of the closed-form analytical expression for the secrecy capacity (SC) to protect that confidential information from eavesdropping. After that, Constructive Interfrence (CI) precoding and Zero Forcing (ZF) precoding techniques have been applied with RS technology. The results shows that CI with RS outperforms ZF with RS.
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Enhancing Security of Cognitive Radio Network with Rate Splitting | 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 Enhancing Security of Cognitive Radio Network with Rate Splitting Rezwana Sultana This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2642571/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 this paper, Rate Splitting (RS) technique has been proposed in Cognitive Radio Network (CRN) in the presence of eavesdropper. Applying RS the message transmitted from Primary User (PU) and Secondary User (SU) are splitted into common and private parts where the common message can be decoded by any one whereas the private one can only be decoded by the intended user. Authors are interested to develop a mathematical model consists of the closed-form analytical expression for the secrecy capacity (SC) to protect that confidential information from eavesdropping. After that, Constructive Interfrence (CI) precoding and Zero Forcing (ZF) precoding techniques have been applied with RS technology. The results shows that CI with RS outperforms ZF with RS. Rate Splitting Zero Forcing Precoding Constructive Interference Precoding Secrecy Capacity 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. 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