Investigation of Network Selection Decisions for Mixed Deployment of SA and NSA 5G Network

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The paper investigates network selection decisions for a mixed 5G deployment in which non-standalone (NSA) and standalone (SA) architectures are used along the migration path toward a unified 5G network. Using a Markov model, it analyzes service blocking probabilities for MBB, eMBB, and uRLLC across user categories, incorporating users’ equipment capabilities and service subscription profiles, and also evaluates how equipment capability affects average utilization. Simulation results show that both equipment capability and subscription profiles significantly influence service blocking and utilization in the heterogeneous network, emphasizing dependence on user-side characteristics. The paper is presented as a preprint and provides limited methodological detail beyond the described modeling/simulation framework. 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

Abstract As migration from 4G network to 5G network gains momentum across the world, network operators are faced with different options when migrating from the 4G to a unified 5G network. These options have been broadly classified as standalone (SA) and non-standalone (NSA) options. While an operator can migrate from the 4G network to the 5G network in one step, using the SA 5G deployment option, for most network operators, the migration from the 4G network to a unified 5G network is a multistage process, starting with an NSA 5G deployment option. This paper investigates network selection decisions for a mixed deployment of NSA and SA 5G network, along the migration path to the realization of a unified 5G network. To the best of our knowledge, this is the first paper investigating network selection decisions in a 5G network with mixed deployment of NSA and SA options. A Markov model has been developed to investigate the blocking of MBB, eMBB, and uRLLC services from different categories of users in the network, based on their equipment capabilities and service subscription profiles. Moreover, the developed model has been used to investigate the effect of users’ equipment capability on average utilization of the heterogeneous network. Simulation results show that users’ equipment capability and users’ service subscription profiles significantly affect service blocking probabilities and average utilization in the heterogenous network. The study underscores the importance of upgrading users’ equipment and users’ subscription profiles before reaping the connection-level QoS benefit of deploying the 5G network.
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Investigation of Network Selection Decisions for Mixed Deployment of SA and NSA 5G Network | 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 Investigation of Network Selection Decisions for Mixed Deployment of SA and NSA 5G Network Olabisi Falowo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4162783/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 As migration from 4G network to 5G network gains momentum across the world, network operators are faced with different options when migrating from the 4G to a unified 5G network. These options have been broadly classified as standalone (SA) and non-standalone (NSA) options. While an operator can migrate from the 4G network to the 5G network in one step, using the SA 5G deployment option, for most network operators, the migration from the 4G network to a unified 5G network is a multistage process, starting with an NSA 5G deployment option. This paper investigates network selection decisions for a mixed deployment of NSA and SA 5G network, along the migration path to the realization of a unified 5G network. To the best of our knowledge, this is the first paper investigating network selection decisions in a 5G network with mixed deployment of NSA and SA options. A Markov model has been developed to investigate the blocking of MBB, eMBB, and uRLLC services from different categories of users in the network, based on their equipment capabilities and service subscription profiles. Moreover, the developed model has been used to investigate the effect of users’ equipment capability on average utilization of the heterogeneous network. Simulation results show that users’ equipment capability and users’ service subscription profiles significantly affect service blocking probabilities and average utilization in the heterogenous network. The study underscores the importance of upgrading users’ equipment and users’ subscription profiles before reaping the connection-level QoS benefit of deploying the 5G network. 5G NR LTE network selection radio resources user equipment 5G deployment blocking probability 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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