Bio-Hybrid 6G Networks: Mathematical Modelling of Synthetic Biology-Enabled Base Stations for Energy- Autonomous Telecommunications

Bio-Hybrid 6G Networks: Mathematical Modelling of Synthetic Biology-Enabled Base Stations for Energy- Autonomous Telecommunications | 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 Article Bio-Hybrid 6G Networks: Mathematical Modelling of Synthetic Biology-Enabled Base Stations for Energy- Autonomous Telecommunications Abdulrahman Al Ayidh, Mohammed M. Alammar, Mohamed Abbas, Muneer Parayangat, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7180864/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 14 You are reading this latest preprint version Abstract The rapid advancement of wireless communication technologies has led to a significant rise in energy consumption, presenting substantial challenges in terms of sustainability, environmental impact, and operational costs especially with the emergence of ultra-dense 6G networks. To address these issues, this paper introduces an innovative paradigm that integrates synthetic biology with telecommunications infrastructure to develop energy-autonomous, bio-hybrid base stations. These systems utilize bio-inspired energy harvesting techniques, such as microbial fuel cells and enzyme-catalyzed reactions, to convert organic waste into electricity, thereby reducing dependence on conventional power grids. A detailed mathematical modeling framework is proposed to analyze key factors including energy consumption patterns, bioenergy conversion efficiency, carbon emissions, and reliability under stochastic environmental conditions. The main objective of this study is to design, model, and optimize bio-hybrid base stations powered by synthetic biology to enable sustainable, scalable, and self-sufficient 6G networks for future smart environments. This study also incorporates AI-driven optimization for hybrid energy storage and power distribution, ensuring system stability and performance. In addition, it addresses critical concerns related to biocompatibility, biosecurity, public perception, and ethical deployment of living technologies. Simulation results validate the feasibility and resilience of the proposed bio-hybrid systems, demonstrating their potential to support the next generation of intelligent, decentralized, and carbon-neutral telecommunications infrastructure. Biological sciences/Biotechnology Physical sciences/Energy science and technology Physical sciences/Engineering Earth and environmental sciences/Environmental sciences Bio-hybrid networks Synthetic biology Energy-autonomous base stations 6G sustainability Microbial fuel cells AI-driven energy optimization Carbon-neutral telecommunications Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 15 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 03 Sep, 2025 Reviews received at journal 01 Sep, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviews received at journal 23 Aug, 2025 Reviews received at journal 19 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers agreed at journal 08 Aug, 2025 Reviewers invited by journal 07 Aug, 2025 Editor assigned by journal 04 Aug, 2025 Editor invited by journal 01 Aug, 2025 Submission checks completed at journal 31 Jul, 2025 First submitted to journal 31 Jul, 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. 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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-7180864","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":498932099,"identity":"edcbbb2c-fb47-4404-9301-d881d7b4d032","order_by":0,"name":"Abdulrahman Al Ayidh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYFAC5gaGBDYbAwkQm4c4LYwgLWmkamFgO0yCFv72g40fHpSdN5ackcD44G0bgz1/AwEtEmcSmyUSzt02k5ZIYDac28aQOOMAIWsOJDZIJLbdtpGTSGCT5m1jSGAgpEX+/MPmH4lt50Ba2H8DtdjLE9JicCOxDWjLAZDD2JiBWhg3ENJieONhm0XCuWRjyZ6HzZJzzkkkbiSkRe588uGbP8rsDGccTz744U2Zjb0cIS1IABRBDBLEqx8Fo2AUjIJRgBsAAHlmQGmaOWElAAAAAElFTkSuQmCC","orcid":"","institution":"King Khalid University","correspondingAuthor":true,"prefix":"","firstName":"Abdulrahman","middleName":"Al","lastName":"Ayidh","suffix":""},{"id":498932100,"identity":"76e1f7f4-da4d-446b-8d06-f132534a358c","order_by":1,"name":"Mohammed M. 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