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A Deep Learning based Approach for Indoor Localization A short review for “ CSI-based fingerprinting for indoor localization : A deep learning approach ”
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ge, Xiaohu Wang, Xiaoming Gao, Limian Mao, Song-Yen Pandey, Soma |
| Copyright Year | 2018 |
| Abstract | Location is important information for many mobile applications, for example, navigation and tracking. Since most mobile users are indoors, indoor localization is of great interest. Accurate indoor localization can enable traditional and new applications such as navigation in a stadium or exhibition hall, locationbased advertisement, access control to wireless networks or information based on location, and even faster beamforming/beam tracking in 5G mmWave networks. Although having been studied for decades, there is still a great need for accurate and robust solutions for complex indoor environments. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.eng.auburn.edu/~szm0001/papers/mmtc_review_Dec-2018_DeepFi.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |