Distributed Reconfigurable Intelligent Surfaces Assisted Indoor Positioning

Author:

Ma Teng1ORCID,Xiao Yue1ORCID,Lei Xia1ORCID,Xiong Wenhui1ORCID,Xiao Ming2ORCID

Affiliation:

1. National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China

2. Department of Information Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden

Funder

National Key Research and Development Program of China

FORMAS Project titled “Intelligent Energy Management in Smart Community with Distributed Machine Learning”

Swedish Research Council Project titled “Coding for Large-Scale Distributed Machine Learning”

STINT Project “Efficient and Secure Distributed Machine Learning with Gradient Descend”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Reference71 articles.

1. WiFi-based indoor positioning

2. Towards Ubiquitous Positioning by Leveraging Reconfigurable Intelligent Surface

3. Robust Indoor Positioning Provided by Real-Time RSSI Values in Unmodified WLAN Networks

4. Cramér–Rao lower bounds for positioning with large intelligent surfaces using quantized amplitude and phase;alegria;Proc 53rd Asilomar Conf Signals Syst Comput,2019

5. Locating the nodes: cooperative localization in wireless sensor networks

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