MIL: A mobile indoor localization scheme based on matrix completion

Cheng, Jie; Song, Zeqi; Ye, Qiang; Du, Hongwei

doi:10.1109/icc.2016.7510871

Cited by 11 publications

(4 citation statements)

References 13 publications

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“…Range-based localization methods have been extensively studied in past decades. In [12][13][14][15], the authors built optimization models utilizing physical distance to solve localization problems. Generally, range-based methods are mainly based on relative distance, which can be obtained through measuring methods like time-of-arrival (ToA), time difference of arrival (TDoA), or propagation model generated from RSSI value.…”

Section: Range-based Methodsmentioning

confidence: 99%

A hybrid outdoor localization scheme with high-position accuracy and low-power consumption

Zhang

et al. 2018

J Wireless Com Network

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As mobile devices, such as smart phones, become more and more popular, localization based on mobile devices has gained much attention in both the academia and industry. Although global positioning system (GPS) has been widely deployed in many fields, it has several disadvantages such as consuming too much power and requiring the line of sight to satellites. Cellular network-based localization is much more robust. However, this type of localization scheme cannot achieve enough accuracy for some localization-based services. With the existence of densely deployed WiFi access points, WiFi-based localization seems very promising in terms of positioning precision and power consumption. However, different than GPS and cellular network based localization, most of the existing WiFi-based localization schemes are supposed to be used in indoor environments. Note that indoor WiFi-based localization schemes cannot be simply ported to urban outdoor environments due to several factors such as weaker signal and more serious interference. In this paper, we present a hybrid outdoor localization scheme utilizing crowdsourced WiFi signal data and built-in sensors in smart phones, which can achieve high-positioning accuracy and low power consumption. Our experimental results show that the proposed hybrid localization scheme outperforms the widely-adopted GPSbased method in terms of both positioning accuracy and power consumption. In addition, the idea of crowdsourcing fingerprints is effective.

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Section: Range-based Methodsmentioning

confidence: 99%

A hybrid outdoor localization scheme with high-position accuracy and low-power consumption

Zhang

et al. 2018

J Wireless Com Network

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“…Moreover, how to cut the calibration workload is also directly related to the application of fingerprinting technology. Therefore, to upgrade the practicability of the proposals, many previous studies [5, 12–14, 26, 27] have begun to take into account the less calibration when building the FD. In [12], the authors proposed a sparse‐based recovery method to implement the completion of RSSI FD.…”

Section: Related Workmentioning

confidence: 99%

“…Kuo et al [26] used the spatial correlation of fingerprints to characterise the fingerprints with a small number of parameters. Both the authors of [5, 27] used the MC‐based approach to achieve the target of less calibration effort. However, due to the coarse‐grained nature of RSSI fingerprints, the positioning errors of both systems exceeded 2 m. Inspired by the achievements and shortcomings of the above work, our work will strive to seek the breakthroughs in FD construction and positioning performance.…”

Section: Related Workmentioning

confidence: 99%

Channel state information based efficient database construction for indoor localisation

Tian

Wang

2019

J. eng.

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“…The radio fingerprinting is a well known localization technique which is organized in two steps [7,8]. In the first step, a radio map is constructed and, in the second step, online measurement is compared to the radio map [9]. The communication signal can also be used to perform the trilateration [10][11][12] where the distances between the target and reference positions can be estimated by using the Received Signal Strength Indicator (RSSI) [13].…”

Section: Introductionmentioning

confidence: 99%

Beyond Stochastic Gradient Descent for Matrix Completion Based Indoor Localization

et al. 2019

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In this paper, we propose a high accuracy fingerprint-based localization scheme for the Internet of Things (IoT). The proposed scheme employs mathematical concepts based on sparse representation and matrix completion theories. Specifically, the proposed indoor localization scheme is formulated as a simple optimization problem which enables efficient and reliable algorithm implementations. Many approaches, like Nesterov accelerated gradient (Nesterov), Adaptative Moment Estimation (Adam), Adadelta, Root Mean Square Propagation (RMSProp) and Adaptative gradient (Adagrad), have been implemented and compared in terms of localization accuracy and complexity. Simulation results demonstrate that Adam outperforms all other algorithms in terms of localization accuracy and computational complexity.

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MIL: A mobile indoor localization scheme based on matrix completion

Cited by 11 publications

References 13 publications

A hybrid outdoor localization scheme with high-position accuracy and low-power consumption

A hybrid outdoor localization scheme with high-position accuracy and low-power consumption

Channel state information based efficient database construction for indoor localisation

Beyond Stochastic Gradient Descent for Matrix Completion Based Indoor Localization

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