{"id":774,"date":"2022-04-27T14:37:43","date_gmt":"2022-04-27T14:37:43","guid":{"rendered":"https:\/\/carleton.ca\/ericsson\/?p=774"},"modified":"2025-04-14T11:29:40","modified_gmt":"2025-04-14T15:29:40","slug":"ericsson-fellow-ben-earle-is-exploring-ml-to-reconstruct-5g-channels","status":"publish","type":"post","link":"https:\/\/carleton.ca\/ericsson\/2022\/ericsson-fellow-ben-earle-is-exploring-ml-to-reconstruct-5g-channels\/","title":{"rendered":"Ericsson Fellow Ben Earle is Exploring ML to Reconstruct 5G Channels"},"content":{"rendered":"\n
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\n Ericsson Fellow Ben Earle is Exploring ML to Reconstruct 5G Channels\n <\/h1>\n \n \n <\/header>\n\n <\/div>\n\n <\/div>\n\n <\/div>\n<\/section>\n\n\n\n\n\n

By Ellen Tsaprailis
Photos by Lindsay Ralph <\/em><\/p>\n\n\n\n

Ben Earle<\/a> is trying to find the ideal mathematical representation using Machine Learning to reconstruct channels to better transmit 5G signals.<\/p>\n\n\n\n

Machine Learning (ML) is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.<\/p>\n\n\n\n

With mass adoption of 5G on cellphones for example, Earle explains that multiple users will bring interference between them and if there is a good understanding of the channel and how to direct the 5G signal so the interference doesn\u2019t happen, then transmission of data could happen twice as fast as what people currently experience on networks today.<\/p>\n\n\n\n

\u201cWith every iteration of wireless protocols, they are trying to push things forward,\u201d says Earle. \u201cThe user equipment and the base station have an internal representation of the channel they are communicating over and how quickly they can transmit data. The more antennas we can use and the finer-grained we can make the beams, the more users can talk at the same time with the same resources because ultimately, you have a limited number of resources to communicate with.<\/p>\n\n\n

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\u201cUltimately, it is important to improve these channels so that we can meet the goals set by the 5G pillars and support the expected high data rates.\u201d<\/p><\/blockquote>\n<\/div>\n\n\n

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Ben Earle is an Ericsson Fellow and PhD student in Applied Science<\/figcaption><\/figure>\n\n\n\n

Earle is one of six graduate students who are <\/a>Ericsson Fellows<\/a> at Carleton University\u2014a unique, talent-building program born out of the Ericsson-Carleton University Partnership for Research and Leadership in Wireless Networks<\/a>.<\/p>\n\n\n\n

Instead of working as a teaching assistant during their graduate studies, Earle and the other fellows are being supported to fully focus on their pioneering wireless communications research and get input from both their academic supervisors and Ericsson professionals.<\/p>\n\n\n\n

In 2019, Earle earned his Bachelor of Engineering in Computer Systems from Carleton and while in his fourth year, he decided to take graduate courses instead of electives as part of the accelerated pathway program. <\/p>\n\n\n\n

Finding his graduate courses more interesting than expected, Earle decided to enrol in Carleton\u2019s master\u2019s program in electrical and computer engineering and began to conduct research with Systems and Computer Engineering<\/a> Professor Gabriel Wainer<\/a>.<\/p>\n\n\n\n

As Wainer and Earle collaborated, Earle decided to take another accelerated pathway by skipping his master\u2019s and going straight into a PhD instead that he is currently pursuing. Along with his PhD studies in applied science, he became an Ericsson Fellow two years ago.<\/p>\n\n\n\n

The Ericsson Fellowship provided Earle the opportunity to research ML in a practical application that ties in with his PhD studies.<\/p>\n\n\n\n

\u201cSupervising Ben is a delight,\u201d says Wainer. \u201cEven during the difficult times of the pandemic, Ben has been proactive, hardworking and showed academic excellence. Ben\u2019s collaboration between Carleton University and Ericsson Canada has given him the opportunity to work on a project that combines two areas he is interested in. He proposed new ideas to deploy ML and Deep Learning algorithms in a challenging task in 5G systems, i.e., channel estimation in massive-MIMO system. Throughout this collaboration between Carleton and Ericsson, Ben gets to work on an innovative project where he is constantly learning about state-of-the-art research, building a solid experience to solve challenging tasks in 5G systems.\u201d<\/p>\n\n\n\n

From the Ericsson Ottawa office, Team Leader and Developer Xingliang Li has worked with Earle during his fellowship as has Manager of Network System Verification Guoqiang Xue. Last July, Earle published a paper titled, Prediction of 5G New Radio Wireless Channel Path Gains and Delays Using Machine Learning and CSI Feedback<\/em> along with Li, Xue, Wainer and Carleton Systems and Computer Engineering Adjunct Research Professor Ala\u2019a Al-Habashna<\/a>. The paper was published in IEEEXplore<\/em><\/a>.<\/p>\n\n\n\n

\u201cBen is showing his expertise in Machine Learning and an eager-to-learn attitude in wireless communications from Ericsson partners. With his comprehensive literature review and his paper as the result of the first step of the research, I believe that the project is in good progress and Ben has found a good way forward to achieve our objectives,\u201d says Li, who Earle meets with regularly to provide updates and keep him focused on industry relevant research.<\/p>\n\n\n\n

\u201cFrom the company perspective to direct this research from the Ericsson side, we are making most of our efforts in communicating with the Carleton side to guide this research based on our application context and practical requirements. That is important to guarantee the collaboration will be productive for Ericsson. I think this project is on the right track.\u201d<\/p>\n\n\n\n

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Ben Earle<\/figcaption><\/figure>\n\n\n\n

For Earle, the Ericsson Fellowship has helped him keep his research practical and relevant in the niche area of channel reconstruction.<\/p>\n\n\n

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\u201cI probably wouldn’t have been doing wireless research if it wasn’t for this partnership. I am thrilled about doing it and it’s certainly a good field if I want to try and get a job in Ottawa. Giving me industry contacts is certainly priceless,\u201d says Earle. \u201cHopefully I\u2019ll be able to turn this experience into a job at Ericsson when I finish my PhD.\u201d<\/p><\/blockquote>\n<\/div>\n\n\n

Ericsson Fellowship<\/strong><\/a>
In this prestigious fellowship program<\/a>, Carleton graduate students conduct hands-on research alongside Ericsson experts in state-of-the-art facilities, ensuring students build skills that are in high demand in today’s telecommunications industry.<\/p>\n\n\n\n

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<\/p>\n","protected":false},"excerpt":{"rendered":"

By Ellen Tsaprailis Photos by Lindsay Ralph Ben Earle is trying to find the ideal mathematical representation using Machine Learning to reconstruct channels to better transmit 5G signals. Machine Learning (ML) is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can […]<\/p>\n","protected":false},"author":2,"featured_media":775,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[32],"tags":[],"class_list":["post-774","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"acf":{"cu_post_thumbnail":false},"_links":{"self":[{"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/posts\/774","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/comments?post=774"}],"version-history":[{"count":5,"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/posts\/774\/revisions"}],"predecessor-version":[{"id":789,"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/posts\/774\/revisions\/789"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/media\/775"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/media?parent=774"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/categories?post=774"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/carleton.ca\/ericsson\/wp-json\/wp\/v2\/tags?post=774"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}