A Survey on Wireless Indoor Localization from the Device Perspective

By Jiang Xiao, Zimu Zhou, Youwen Yi, Lionel Ming-shuan Ni. ACM Computing Surveys, 2016

357 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/d4ca490730df2fc88455cb2a24b4a589ddc3f45d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Paul Patras
2. Gang Zhou
3. Hamed Haddadi
4. Yongsen Ma
5. Chaoyun Zhang
6. Shuangquan Wang
7. Erik G. Larsson
8. Meysam Sadeghi

In Electrical and Electronic Engineering

1. Paul Patras
2. Gang Zhou
3. Hamed Haddadi
4. Yongsen Ma
5. Chaoyun Zhang
6. Shuangquan Wang
7. Erik G. Larsson
8. Meysam Sadeghi

In Ocean Engineering

1. Paul Patras
2. Hamed Haddadi
3. Chaoyun Zhang

Citations in the corpus

• WiFi Sensing with Channel State Information (2019, background): “[122] device-free and device-based indoor localization models, basic principles, and data fusion techniques”
• Deep Learning in Mobile and Wireless Networking: A Survey (2018, background): “84]. As a result, research on user localization is evolving rapidly and numerous techniques are emerging [485].In general, user localization methods can be categorized as device-based and device-free [486]. We illustrate the two different paradigms in Fig. 14. Specifically, in the first category speci”