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However, massive signal attenuation, complex response to building structures, and frequent non-availability of the Line-Of-Sight path make D-band picocell deployment challenging. To address this challenge, we propose a deep learning-based tool, that allows a network deployer to quickly scan the environment from a few random locations and predict Signal Reflection Profiles everywhere, which is essential to determine the optimal locations for picocell deployment.<\/jats:p>","DOI":"10.1145\/3595244.3595266","type":"journal-article","created":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T10:27:14Z","timestamp":1682591234000},"page":"62-64","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Towards Deep Learning Augmented Robust D-Band Millimeter-Wave Picocell Deployment"],"prefix":"10.1145","volume":"50","author":[{"given":"Hem","family":"Regmi","sequence":"first","affiliation":[{"name":"University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanjib","family":"Sur","sequence":"additional","affiliation":[{"name":"University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,4,27]]},"reference":[{"volume-title":"A Global Initiative, \"The Mobile Broadband Standard: Release 18","year":"2022","unstructured":"3GPP : A Global Initiative, \"The Mobile Broadband Standard: Release 18 ,\" 2022 . 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