@inproceedings{2d34b6ad2aa845da80d90abfbbcea8f5,
title = "Node Deployment under Position Uncertainty for Network Localization",
abstract = "Network localization performance depends on the network geometry and, therefore, node deployment methods are critical for high-accuracy localization. Optimal node deployment is challenging in practical problems due to various uncertainties present in the position knowledge of the deployed nodes. In this paper, we propose a node-deployment method for network localization that accounts for such uncertainties. We develop a framework for the optimal deployment of location-aware networks under bounded disturbances in the positions of the sensing nodes. More specifically, by considering bounded discrepancies in the network geometry, we characterize the optimal deployment according to the D-optimality criterion and assert its implications for the A-optimality and E-optimality criteria. Results show that the proposed optimization-based design achieves a significative improvement according to the D-optimality criterion.",
keywords = "Fisher information, network localization, node deployment, sensor network",
author = "Khojasteh, \{Mohammad Javad\} and Saucan, \{Augustin A.\} and Zhenyu Liu and Andrea Conti and Win, \{Moe Z.\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Communications, ICC 2022 ; Conference date: 16-05-2022 Through 20-05-2022",
year = "2022",
month = jan,
day = "1",
doi = "10.1109/ICC45855.2022.9839158",
language = "English",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "889--894",
booktitle = "ICC 2022 - IEEE International Conference on Communications",
}