{"id":406,"date":"2021-03-19T08:16:24","date_gmt":"2021-03-19T08:16:24","guid":{"rendered":"https:\/\/vinuni.edu.vn\/research\/?p=406"},"modified":"2022-09-05T08:17:43","modified_gmt":"2022-09-05T08:17:43","slug":"applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems","status":"publish","type":"post","link":"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/","title":{"rendered":"Applying Machine Learning to mitigate RF impairments in wireless communications systems"},"content":{"rendered":"<p>Abstract<\/p>\n<p>In traditional wireless communications systems, multiple complex digital signal processing blocks are designed to combat the imperfect radio frequency front-end components. However, due to Part-to-part, Voltage, and Temperature variation, an algorithm working well on one device may not work well on the others. Also, it is not efficient as each block needs to regularly run calibration and compensation at different time slots; hence, the system performance is significantly reduced. In this project, it is proposed to utilize machine learning to learn and compensate for RF front-end impairments in wireless communications systems. The results of this project can be used to improve various end-to-end wireless communication systems such as 5G\/6G, IoT systems, device to device, self-driving car, etc.<\/p>\n<p>Author: Nguyen Viet Tu<\/p>\n<p>Read more about the author\u2019s publications\u00a0<a href=\"https:\/\/vinuni.edu.vn\/people\/nguyen-viet-tu\/\">here<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Abstract In traditional wireless communications systems, multiple complex digital signal processing blocks are designed to combat the imperfect radio frequency front-end components. However, due to Part-to-part, Voltage, and Temperature variation, an algorithm working well on one device may not work well on the others. Also, it is not efficient as each block needs to regularly [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":407,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[37],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.6.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Applying Machine Learning to mitigate RF impairments in wireless communications systems - Vinuni Research Website<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Applying Machine Learning to mitigate RF impairments in wireless communications systems - Vinuni Research Website\" \/>\n<meta property=\"og:description\" content=\"Abstract In traditional wireless communications systems, multiple complex digital signal processing blocks are designed to combat the imperfect radio frequency front-end components. However, due to Part-to-part, Voltage, and Temperature variation, an algorithm working well on one device may not work well on the others. Also, it is not efficient as each block needs to regularly [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/\" \/>\n<meta property=\"og:site_name\" content=\"Vinuni Research Website\" \/>\n<meta property=\"article:published_time\" content=\"2021-03-19T08:16:24+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-09-05T08:17:43+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/vinuni.edu.vn\/research\/wp-content\/uploads\/2022\/09\/Prof.-Tu-1-e1616128979270-660x410-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"660\" \/>\n\t<meta property=\"og:image:height\" content=\"410\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"phuong.ntn\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"phuong.ntn\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/\",\"url\":\"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/\",\"name\":\"Applying Machine Learning to mitigate RF impairments in wireless communications systems - Vinuni Research Website\",\"isPartOf\":{\"@id\":\"https:\/\/vinuni.edu.vn\/research\/#website\"},\"datePublished\":\"2021-03-19T08:16:24+00:00\",\"dateModified\":\"2022-09-05T08:17:43+00:00\",\"author\":{\"@id\":\"https:\/\/vinuni.edu.vn\/research\/#\/schema\/person\/d19200a9f0488a2d6374d8641ee8c085\"},\"breadcrumb\":{\"@id\":\"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Applying Machine Learning to mitigate RF impairments in wireless communications systems\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/vinuni.edu.vn\/research\/#website\",\"url\":\"https:\/\/vinuni.edu.vn\/research\/\",\"name\":\"Vinuni Research Website\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/vinuni.edu.vn\/research\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/vinuni.edu.vn\/research\/#\/schema\/person\/d19200a9f0488a2d6374d8641ee8c085\",\"name\":\"phuong.ntn\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/vinuni.edu.vn\/research\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/678312306781d0830679d2c1a8a112f1?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/678312306781d0830679d2c1a8a112f1?s=96&d=mm&r=g\",\"caption\":\"phuong.ntn\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Applying Machine Learning to mitigate RF impairments in wireless communications systems - Vinuni Research Website","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/vinuni.edu.vn\/research\/applying-machine-learning-to-mitigate-rf-impairments-in-wireless-communications-systems\/","og_locale":"en_US","og_type":"article","og_title":"Applying Machine Learning to mitigate RF impairments in wireless communications systems - Vinuni Research Website","og_description":"Abstract In traditional wireless communications systems, multiple complex digital signal processing blocks are designed to combat the imperfect radio frequency front-end components. 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