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Enhancing QoE Assessment in FWA: Leveraging Network KPIs and User Feedback Analysis
Quality of Experience (QoE) evaluation plays a pivotal role in assessing user satisfaction, usability, performance and content quality across diverse services, applications and technologies. In the context of Fixed Wireless Access (FWA) systems, this research presents a novel and refined method for...
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creator | Gokcesu, Hakan Ercetin, Ozgur Kalem, Gokhan |
description | Quality of Experience (QoE) evaluation plays a pivotal role in assessing user satisfaction, usability, performance and content quality across diverse services, applications and technologies. In the context of Fixed Wireless Access (FWA) systems, this research presents a novel and refined method for precise QoE evaluations tailored to FWA users. The cornerstone of our proposed approach lies in adjusting a fundamental metric known as the Customer Experience Index (CEI). This proprietary metric is commonly utilized by network operators. It enables the development of an innovative, low-complexity and highly efficient approach to construct QoE using many available metrics. To achieve greater accuracy and relevance, the proposed method integrates user feedback and, thus, allows the identification of deviations in service Key Performance Indicators (KPIs). By aligning the metrics with user perceptions, we enhance the method's ability to capture subtle nuances in user experience. The calibrated base metric (which is constructed from CEI) is a robust foundation that accommodates the identified deviations and yields more reliable QoE evaluations. The calibration process ensures that the metric accurately represents the intricate interplay between user feedback and network performance. By adopting this precise QoE evaluation framework, FWA systems can make informed decisions, optimize resource allocation, and enhance overall user experience. |
doi_str_mv | 10.1109/CAMAD59638.2023.10478421 |
format | conference_proceeding |
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The calibration process ensures that the metric accurately represents the intricate interplay between user feedback and network performance. By adopting this precise QoE evaluation framework, FWA systems can make informed decisions, optimize resource allocation, and enhance overall user experience.</description><subject>fixed wireless access</subject><subject>Indexes</subject><subject>Key performance indicator</subject><subject>key performance indicators</subject><subject>network monitoring</subject><subject>Quality of experience</subject><subject>Real-time systems</subject><subject>Resource management</subject><subject>user analysis</subject><subject>User experience</subject><subject>Wireless communication</subject><issn>2378-4873</issn><isbn>9798350303490</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kMlOAkEURUsTEwnyBy7qBxpfDd31yl0HQYg4RYlLUsNrbIHCdBENf69GXd3k5OQsLmNcwFAIsBej-ra-Km2lcChBqqEAbVBLccQG1lhUJShQ2sIx60llsNBo1Ckb5PwGAEogorE99jROry6FNq34427M65wp5y2lPW8Tn7zUl3xOH9S51Y9xR_vPXbfmNw-zzF2KfJGp4xOi6F1Y8zq5zSG3-YydNG6TafC3fbaYjJ9H02J-fz0b1fOilaD3hQ9N2RiqhCm9hsoE74WJjcFoJYEIjYzWqYjfWINQLpJDV0WNAX3jfFB9dv7bbYlo-d61W9cdlv8_qC98lVKp</recordid><startdate>20231106</startdate><enddate>20231106</enddate><creator>Gokcesu, Hakan</creator><creator>Ercetin, Ozgur</creator><creator>Kalem, Gokhan</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20231106</creationdate><title>Enhancing QoE Assessment in FWA: Leveraging Network KPIs and User Feedback Analysis</title><author>Gokcesu, Hakan ; Ercetin, Ozgur ; Kalem, Gokhan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i204t-bcf5f7e6175b4067cbb17df78d92e01cf2d9a3d8bb14013adea8a6d48c8bfabc3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>fixed wireless access</topic><topic>Indexes</topic><topic>Key performance indicator</topic><topic>key performance indicators</topic><topic>network monitoring</topic><topic>Quality of experience</topic><topic>Real-time systems</topic><topic>Resource management</topic><topic>user analysis</topic><topic>User experience</topic><topic>Wireless communication</topic><toplevel>online_resources</toplevel><creatorcontrib>Gokcesu, Hakan</creatorcontrib><creatorcontrib>Ercetin, Ozgur</creatorcontrib><creatorcontrib>Kalem, Gokhan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore (Online service)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gokcesu, Hakan</au><au>Ercetin, Ozgur</au><au>Kalem, Gokhan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Enhancing QoE Assessment in FWA: Leveraging Network KPIs and User Feedback Analysis</atitle><btitle>2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)</btitle><stitle>CAMAD</stitle><date>2023-11-06</date><risdate>2023</risdate><spage>233</spage><epage>239</epage><pages>233-239</pages><eissn>2378-4873</eissn><eisbn>9798350303490</eisbn><abstract>Quality of Experience (QoE) evaluation plays a pivotal role in assessing user satisfaction, usability, performance and content quality across diverse services, applications and technologies. In the context of Fixed Wireless Access (FWA) systems, this research presents a novel and refined method for precise QoE evaluations tailored to FWA users. The cornerstone of our proposed approach lies in adjusting a fundamental metric known as the Customer Experience Index (CEI). This proprietary metric is commonly utilized by network operators. It enables the development of an innovative, low-complexity and highly efficient approach to construct QoE using many available metrics. To achieve greater accuracy and relevance, the proposed method integrates user feedback and, thus, allows the identification of deviations in service Key Performance Indicators (KPIs). By aligning the metrics with user perceptions, we enhance the method's ability to capture subtle nuances in user experience. The calibrated base metric (which is constructed from CEI) is a robust foundation that accommodates the identified deviations and yields more reliable QoE evaluations. 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identifier | EISSN: 2378-4873 |
ispartof | 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2023, p.233-239 |
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subjects | fixed wireless access Indexes Key performance indicator key performance indicators network monitoring Quality of experience Real-time systems Resource management user analysis User experience Wireless communication |
title | Enhancing QoE Assessment in FWA: Leveraging Network KPIs and User Feedback Analysis |
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