{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:56:35Z","timestamp":1740149795120,"version":"3.37.3"},"reference-count":34,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T00:00:00Z","timestamp":1620345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["No. 61871232 and No.61771257"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Postgraduate Research & Practice Innovation Program of Jiangsu Province","award":["Grant No. SJCX19_0275 and No. KYCX20_0802"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"With the increasing demand of location-based services, neural network (NN)-based intelligent indoor localization has attracted great interest due to its high localization accuracy. However, deep NNs are usually affected by degradation and gradient vanishing. To fill this gap, we propose a novel indoor localization system, including denoising NN and residual network (ResNet), to predict the location of moving object by the channel state information (CSI). In the ResNet, to prevent overfitting, we replace all the residual blocks by the stochastic residual blocks. Specially, we explore the long-range stochastic shortcut connection (LRSSC) to solve the degradation problem and gradient vanishing. To obtain a large receptive field without losing information, we leverage the dilated convolution at the rear of the ResNet. Experimental results are presented to confirm that our system outperforms state-of-the-art methods in a representative indoor environment.<\/jats:p>","DOI":"10.3390\/e23050574","type":"journal-article","created":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T14:06:12Z","timestamp":1620396372000},"page":"574","source":"Crossref","is-referenced-by-count":4,"title":["An Indoor Localization System Using Residual Learning with Channel State Information"],"prefix":"10.3390","volume":"23","author":[{"given":"Chendong","family":"Xu","sequence":"first","affiliation":[{"name":"College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}]},{"given":"Weigang","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"},{"name":"National and Local Joint Engineering Laboratory of RF Integration and Micro-Assembly Technology, Nanjing 210023, China"}]},{"given":"Yunwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}]},{"given":"Jie","family":"Qin","sequence":"additional","affiliation":[{"name":"College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}]},{"given":"Shujuan","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}]},{"given":"Yun","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TMTT.2009.2035947","article-title":"Analysis and Performance of a Smart Antenna for 2.45-GHz Single-Anchor Indoor Positioning","volume":"58","author":"Cidronali","year":"2010","journal-title":"IEEE Trans. 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