CSI-Based Indoor Localization
By Kaishun Wu, Jiang Xiao, Youwen Yi, Dihu Chen, Xiaonan Luo, Lionel Ming-shuan Ni. IEEE Transactions on Parallel and Distributed Systems, 2013
502 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/efa958769552c5c5717fdfcb85def4bbe0e2e581
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
In Ocean Engineering
Citations in the corpus
- Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead (2019, background): “loiting its fingerprint properties (frequency response, signal strength regarding the I/Q channel, etc.), which are then associated with a possible location in a pre-measured fingerprint database [26], [27]. To gain more detailed information concerning the target such as the human behavior, the receiv”
- WiFall: Device-free fall detection by wireless networks (2017, methodology): “After CSI has been leveraged for device-based indoor localization such as FILA [9], [29] and MODLoc [30], more efforts have been paid in device-free scenarios.”
- CSI-Based Fingerprinting for Indoor Localization: A Deep Learning Approach (2016, background): “cards (NICs), which can be used as fingerprints to improve the performance of indoor localization [7]–[11].”
- Wireless Sensing for Human Activity: A Survey (2020, background): “[84], [85] re-defined the indoor propagation model based on a modified free space path loss propagation model to capture the relationship between the effective CSI readings (i.”
- A Survey on Wireless Indoor Localization from the Device Perspective (2016, methodology): “Xiong and Jamieson [2012] leverage the MIMO techniques with multiple antennas in APs to enable fine-grained AOA-based indoor localization.”
- CSI Phase Fingerprinting for Indoor Localization With a Deep Learning Approach (2016, methodology): “In our experiments, a TP Link router serves as AP and the mobile device is a Dell laptop equipped with an IWL 5300 NIC.”
- Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons (2016, background): “Therefore, specialized infrastructures are still needed in current prototype systems [198].”
- DeepFi: Deep learning for indoor fingerprinting using channel state information (2015, background): “It is now possible to obtain channel state information (CSI) from some advanced WiFi network interface cards (NIC), which can be used as fingerprints to improve the performance of indoor localization [7], [8].”