Quasi-Optimal Subcarrier Selection Dedicated for Localization With Multicarrier-Based Signals

Wang, Donglin; Fattouche, M.; Ghannouchi, Fadhel M.; Zhan, Xingqun

doi:10.1109/jsyst.2018.2864794

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…In [30], a subcarrier power allocation scheme for OFDM-based localization is developed in which subcarrier power allocation at the anchor nodes is optimized to reduce positioning errors. In [31], orthogonal multicarrierbased proving signal designs for base station (BS)-based or mobile station (MS)-based localization are presented where non-overlapping subcarrier allocation is necessary for MS based localization to differentiate signals from different BSs. In [32], a RSSI based positioning scheme is proposed in which RSSI of a selected reference subcarrier is exploited for trilaterationbased positioning.…”

Section: Related Workmentioning

confidence: 99%

Device-Free WLAN Based Indoor Localization Scheme With Spatially Concatenated CSI and Distributed Antennas

Muta

Keisuke

Noguchi

et al. 2023

IEEE Trans. Veh. Technol.

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Various machine learning (ML) based localization schemes using channel state information (CSI) in wireless local area networks (WLANs) have been investigated recently. Adopting a proper feature selection technique is important to achieve further improvement in detection accuracy. As described herein, we propose a device-free indoor localization scheme using a lightweight ML model with compressed spatially concatenated CSI in WLAN systems with distributed antennas. In this scheme, feedback beam-forming weights (BFWs) are collected at a CSI capture terminal. Then, current and past BFWs are concatenated as accurate feature data to characterize the object behavior. Additionally, we propose the use of a frequency-domain sampling scheme for a low-complexity real-time target position detection with a small number of datasets. Using ray-trace based simulation analysis and experimentally obtained results from an indoor environment, we demonstrate that the proposed scheme using the concatenated CSI is effective not only for achieving more accurate real-time detection, but also for reducing the necessary complexity for both off-line training and on-line classification compared with other reference schemes.

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Section: Related Workmentioning

confidence: 99%

Device-Free WLAN Based Indoor Localization Scheme With Spatially Concatenated CSI and Distributed Antennas

Muta

Keisuke

Noguchi

et al. 2023

IEEE Trans. Veh. Technol.

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“…But the signal power to locate the channel has higher requirements. Many positioning algorithms are based on ranging information, such as the least squares algorithm [20] and the chan algorithm [21]. Wang [22] proves the bound of position estimation in 3-D localization is closely associated with the bound of range estimation.…”

Section: Introductionmentioning

confidence: 99%

Multi-Frequency-Ranging Positioning Algorithm for 5G OFDM Communication Systems

Zhang

et al. 2023

Chinese J. Elect.

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The accurate determination of vehicle location is of great research significance, considering challenges such as the multipath environment and the absence of Global Navigation Satellite System (GNSS) signals. In this particular environment, vehicles equipped with 5G wireless communication devices can enhance their positioning accuracy by exchanging information with infrastructure (vehicle-to-infrastructure, V2I). Therefore, in this paper, we propose a multifrequency ranging method and positioning algorithm specifically designed for 5G orthogonal frequency division multiplexing (OFDM) communication systems. Our approach involves selecting specific subcarriers within the OFDM communication system for transmitting ranging frames and capturing delay observations. Importantly, this selection does not affect the functionality of other subcarriers used for regular communication. By utilizing dedicated subcarriers for ranging and positioning, we achieve accurate vehicle location without significantly impacting communication capacity. We outline the method for selecting ranging subcarriers and describe the format of the ranging frame carried by these subcarriers. To evaluate the effectiveness of our system, we prove the Cramér-Rao lower bound of this ranging positioning system. The obtained ranging positioning accuracy meets the requirements for vehicle location applications. In our experimental simulations, we compare the performance of our system with other positioning methods, demonstrating its superiority. Additionally, we provide theoretical proofs and simulations that establish the relationship between ranging accuracy and channel parameters in a multipath environment. The simulation results indicate that, under the conditions of a 5 GHz frequency and a high signal-to-noise ratio, our system achieves a positioning accuracy of approximately 5 cm.

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HILLS: Hierarchical Indoor Localization for Large-Scale Architectural Complex

Wang¹

2018

2018 IEEE International Conference on Data Mining Workshops (ICDMW)

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Quasi-Optimal Subcarrier Selection Dedicated for Localization With Multicarrier-Based Signals

Cited by 4 publications

References 25 publications

Device-Free WLAN Based Indoor Localization Scheme With Spatially Concatenated CSI and Distributed Antennas

Device-Free WLAN Based Indoor Localization Scheme With Spatially Concatenated CSI and Distributed Antennas

Multi-Frequency-Ranging Positioning Algorithm for 5G OFDM Communication Systems

HILLS: Hierarchical Indoor Localization for Large-Scale Architectural Complex

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