Design of An Iterative Adaptive and Energy-Efficient Polar Code Architectures for Low-Latency 5G Communication Systems

Design of An Iterative Adaptive and Energy-Efficient Polar Code Architectures for Low-Latency 5G Communication Systems | 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 Design of An Iterative Adaptive and Energy-Efficient Polar Code Architectures for Low-Latency 5G Communication Systems Atish A. Peshattiwar, Atish S. Khobragade This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8871440/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract The increasing demands in 5G networks for ultra-reliable low-latency communication require advanced techniques for decoding polar codes with balanced throughput, energy efficiency, and error resilience sets. Although the decoding algorithms of polar codes for existing techniques are backed by theory, they usually operate with high latencies, high energy consumption, and limited adaptability to dynamic channels and hardware conditions, challenges that limit their applicability in real-time edge-based 5G applications. To ameliorate these limitations, this study lays down a complete performance analysis and an algorithmic framework incorporating five new techniques for the optimization of polar code processing to 5G system constraints. Channel-Conditioned Adaptive Decoding Tree Pruning (C-ADTP) prunes the decoding tree based on real-time Channel State Information (CSI) and Quality-of-Service (QoS) constraints, which translates into 25–35% reduction in latency, and 18–22% energy savings with negligible degradation of the FER. The Sparse Instruction-Level Polar Vectorization Engine (SIL-PVE) offers acceleration through sparse bitwise vectorization in conjunction with architectures such as SIMD/VLIW and exhibits a 1.8×–2.4× increase in throughput with a 30% reduction in decoding time. To further enhance adaptability to mobile environments, the Reliability-Latency Optimized Polar Graph Generator (RLO-PGG) integrates user mobility patterns and delay spread profiles into a dynamic bit-channel assignment strategy, thereby reducing latency by 20–30% under high-speed scenarios. The thermodynamic Core Balancer for Polar Decoding (TCB-PD) introduces thermal-aware task scheduling that reduces energy consumption by 28–32% without compromising the integrity of decoding. Finally, the Hybrid Interleaved Polar Puncturing Optimizer (HIPPO) achieves coding rate flexibility with the help of a bit-difficulty predictor and hybrid interleaving, while enhancing throughput by up to 15% during constrained bandwidth regimes. Collectively, these techniques create a combined framework that significantly enhances the polar code decoding performance and presents a scalable solution for real-time implementation in next-generation wireless systems. 5G Communication Channel Adaptivity Energy Efficiency Low Latency Polar Decoding Process Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 04 May, 2026 Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers agreed at journal 14 Apr, 2026 Reviewers agreed at journal 14 Apr, 2026 Reviewers invited by journal 13 Apr, 2026 Editor assigned by journal 05 Apr, 2026 Submission checks completed at journal 27 Feb, 2026 First submitted to journal 13 Feb, 2026 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-8871440","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626320893,"identity":"a9f13f79-8502-4acb-bea6-d2fbe0904ea1","order_by":0,"name":"Atish A. 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Although the decoding algorithms of polar codes for existing techniques are backed by theory, they usually operate with high latencies, high energy consumption, and limited adaptability to dynamic channels and hardware conditions, challenges that limit their applicability in real-time edge-based 5G applications. To ameliorate these limitations, this study lays down a complete performance analysis and an algorithmic framework incorporating five new techniques for the optimization of polar code processing to 5G system constraints. Channel-Conditioned Adaptive Decoding Tree Pruning (C-ADTP) prunes the decoding tree based on real-time Channel State Information (CSI) and Quality-of-Service (QoS) constraints, which translates into 25\u0026ndash;35% reduction in latency, and 18\u0026ndash;22% energy savings with negligible degradation of the FER. The Sparse Instruction-Level Polar Vectorization Engine (SIL-PVE) offers acceleration through sparse bitwise vectorization in conjunction with architectures such as SIMD/VLIW and exhibits a 1.8\u0026times;\u0026ndash;2.4\u0026times; increase in throughput with a 30% reduction in decoding time. To further enhance adaptability to mobile environments, the Reliability-Latency Optimized Polar Graph Generator (RLO-PGG) integrates user mobility patterns and delay spread profiles into a dynamic bit-channel assignment strategy, thereby reducing latency by 20\u0026ndash;30% under high-speed scenarios. The thermodynamic Core Balancer for Polar Decoding (TCB-PD) introduces thermal-aware task scheduling that reduces energy consumption by 28\u0026ndash;32% without compromising the integrity of decoding. Finally, the Hybrid Interleaved Polar Puncturing Optimizer (HIPPO) achieves coding rate flexibility with the help of a bit-difficulty predictor and hybrid interleaving, while enhancing throughput by up to 15% during constrained bandwidth regimes. Collectively, these techniques create a combined framework that significantly enhances the polar code decoding performance and presents a scalable solution for real-time implementation in next-generation wireless systems.\u003c/p\u003e","manuscriptTitle":"Design of An Iterative Adaptive and Energy-Efficient Polar Code Architectures for Low-Latency 5G Communication Systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-21 15:32:47","doi":"10.21203/rs.3.rs-8871440/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-04T08:42:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T05:18:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316950864569369660478605947130645973117","date":"2026-04-20T12:39:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103961904109789786543523502988711224493","date":"2026-04-17T04:22:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165483514381095112196869642086628338016","date":"2026-04-14T19:59:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18233686568677599388265251927927765894","date":"2026-04-14T15:53:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T13:58:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-05T22:06:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-27T06:29:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Wireless Personal Communications","date":"2026-02-13T11:35:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"wireless-personal-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wire","sideBox":"Learn more about [Wireless Personal Communications](https://www.springer.com/journal/11277)","snPcode":"11277","submissionUrl":"https://submission.nature.com/new-submission/11277/3","title":"Wireless Personal Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"756e2e16-c220-4c0b-a8da-09fed1697177","owner":[],"postedDate":"April 21st, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-04T08:42:27+00:00","index":22,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T15:32:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-21 15:32:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8871440","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8871440","identity":"rs-8871440","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}