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However, most Wi\u2010Fi\u2010based indoor localization systems have complex models and high localization delays, which limit the universality of these localization methods. To solve these problems, a depthwise separable convolution\u2010based passive indoor localization system (DSCP) is proposed. DSCP is a lightweight fingerprint\u2010based localization system that includes an offline training phase and an online localization phase. In the offline training phase, the indoor scenario is first divided into different areas to set training locations for collecting CSI. Then, the amplitude differences of these CSI subcarriers are extracted to construct location fingerprints, thereby training the convolutional neural network (CNN). In the online localization phase, CSI data are first collected at the test locations, and then, the location fingerprint is extracted and finally fed to the trained network to obtain the predicted location. The experimental results show that DSCP has a short training time and a low localization delay. DSCP achieves a high localization accuracy, above 97%, and a small median localization distance error of 0.69\u2009m in typical indoor scenarios.<\/jats:p>","DOI":"10.1155\/2021\/8821129","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T02:05:25Z","timestamp":1609812325000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["DSCP: Depthwise Separable Convolution\u2010Based Passive Indoor Localization Using CSI Fingerprint"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2657-1464","authenticated-orcid":false,"given":"Chong","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjing","family":"Xun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lijuan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoxiao","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,1,4]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2904347"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2911558"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2896482"},{"key":"e_1_2_10_4_2","doi-asserted-by":"crossref","unstructured":"LiuY. 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