@inproceedings{2c63531c4e4647e9999e3e3f820048f5,
title = "Channel-Aware Direct Localization Using One-Bit Quantized Measurements",
abstract = "To address the constraints of limited transmission bandwidth and power consumption in wireless sensor networks (WSNs), this paper proposes a direct localization method using one-bit quantized measurements. Specifically, the received signal is quantized into its one bit version at the local sensor before being transmitted to the fusion center (FC) for target localization. Recognizing the imperfections of the wireless channel between the sensors and the FC, a channel-aware position estimator using one-bit quantized measurements is proposed. Furthermore, the Cram{\'e}r-Rao lower bound (CRLB) of the proposed channel-aware estimator is also derived to theoretically assess the localization performance. Simulation results demonstrate that the proposed channel-aware position estimator approaches its theoretical performance bounds and is superior compared to that of the channel-unaware estimator.",
keywords = "Cram{\'e}r-Rao lower bound (CRLB), direct localization, maximum-likelihood estimation, quantization",
author = "Guoxin Zhang and Yunfei Liang and Wei Yi and Ngo, {Hien Quoc} and Michail Matthaiou and Varshney, {Pramod K.}",
note = "Publisher Copyright: {\textcopyright} 2024 European Signal Processing Conference, EUSIPCO. All rights reserved.; 32nd European Signal Processing Conference, EUSIPCO 2024 ; Conference date: 26-08-2024 Through 30-08-2024",
year = "2024",
language = "English (US)",
series = "European Signal Processing Conference",
publisher = "European Signal Processing Conference, EUSIPCO",
pages = "842--846",
booktitle = "32nd European Signal Processing Conference, EUSIPCO 2024 - Proceedings",
}