Acoustic ranging and communication via microphone channel

Liu, Kaikai; Liu, Xinxin; Li, Xin

doi:10.1109/glocom.2012.6503128

Cited by 12 publications

(10 citation statements)

References 12 publications

(11 reference statements)

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“…Realize relative ranging on a smartphone is crucial for Coloc scheme. Using acoustic time-of-arrival (TOA) based ranging has been demonstrated to have better accuracy than received-signal-strength (RSS) based ranging using WiFi/GSM/Bluetooth signals [9], [14]- [16].…”

Section: Preliminary a Relative Rangingmentioning

confidence: 99%

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Improving GPS Service via Social Collaboration

Liu

Huang

Wang

et al. 2013

2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems

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The popularity of GPS-enabled smartphones enables a wide variety of new location-based or location-aware services and applications. However, the GPS module in a smartphone produces inaccurate position estimates and incurs high energy consumption, which inhibits the wide use of locationaware applications. To address this, we propose a socialaided cooperative location optimization (Coloc) scheme, which is capable of improving positioning accuracy and achieving low energy consumption. Specifically, our scheme enhances positioning accuracy by fusing the GPS positions of multiple colocated smartphones in a social network, or by neighborhoodbased weighted least-squares estimation when relative distances between smartphones are available. The energy efficiency is achieved by sharing location information among co-located users and lower the update rate of the GPS module without sacrificing the accuracy. To validate our proposed approach, we conduct experiments in stationary and moving scenarios. Experimental results show that our proposed cooperative localization scheme can achieve sufficient performance gains in both indoor and outdoor environments.

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Section: Preliminary a Relative Rangingmentioning

confidence: 99%

“…Based on our prior work [9], [16], we perform 2-PAM modulation for the acoustic signal and combine ranging and information bit transmission at the same time. With the information bits directly available in the ranging signal, we could identify the smartphone after signal demodulation.…”

Section: Preliminary a Relative Rangingmentioning

confidence: 99%

Improving GPS Service via Social Collaboration

Liu

Huang

Wang

et al. 2013

2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems

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“…The TOA estimation threshold η toa can be dynamically adapted to balance the false alarm and miss detection probability. Based on our previous work [20], we can write the TOA detection probability as…”

Section: Symbol Detection and Toa Estimationmentioning

confidence: 99%

“…From the measurement signal perspective, smartphone-based indoor localization could be summarized into following categories: RSS-based ranging using propagation attenuation of radio (WiFi, Cellular, and Bluetooth) [23], [24], fingerprintingbased matching using surround sound [2], [25] or radio profiles [5], [26], [26], [27], and TOA-based ranging [11], [12], [15], [20], [28], [29]. Different applications may have different requirements on the complexity, cost and resolution.…”

Section: Related Workmentioning

confidence: 99%

Guoguo: Enabling Fine-Grained Smartphone Localization via Acoustic Anchors

Liu

2016

IEEE Trans. on Mobile Comput.

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Modern smartphones and location-based services and apps are poised to transform our daily life. However, current smartphone-based localization solutions are limited mainly to outdoor, mostly missing practical, robust and accurate indoor location solutions. Despite significant efforts on indoor localization in both academia and industry in the past two decades, highly accurate and practical smartphone-based indoor localization remains an open problem. To enable indoor location-based services (ILBS), e.g., step-by-step navigation for the Blind and visually impaired, there are several stringent requirements: highly accurate (foot-level); no additional hardware components or extensions on users' smartphones; scalable to massive concurrent users. Current GPS, Radio RSS (e.g. WiFi, Bluetooth, ZigBee), or Fingerprinting based solutions can only achieve meter-level or room-level accuracy. In this paper, we propose a practical and accurate solution that fills the long-lasting gap of smartphonebased fine-grained indoor localization. Specifically, we design and implement an indoor localization ecosystem Guoguo. Guoguo consists of an anchor network with a coordination protocol to transmit modulated localization beacons using high-band acoustic signals, a realtime processing app in a smartphone, and a backend server for indoor contexts and location-based services. We further propose approaches to improve its coverage, accuracy, and location update rate with low-power consumption. Our prototype shows centimeter-level localization accuracy in several typical indoor environments. Such precise indoor localization is expected to have high impact in the future ILBS and our daily activities.

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“…To overcome the blindness of random movement, literature [5] enables mobile Sink to move forward at uniform speed along the fixed rail, and collect data from the encountered sensor nodes, thus the static nodes can predict the arrival time of mobile Sink node, efficiently switch between waking and sleeping status, thus saving energy consumption. Some researchers start from that perspective of shortening mobile path and reducing data delay [6,7], turn the traditional TSP problem into TSPN length, thereby reducing data delay. Literature [8] proposed PBS scheduling algorithm based on partition to regulate Sink's movement, in order to ensure that the sensor node buffer in each partition area does not overflow.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Data Gathering Protocol for Mobile Wireless Sensor Networks

Yue¹,

Li²,

Qin³

et al. 2017

dtcse

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Data gathering is a hot research issue of mobile wireless sensor networks. In order to ensure maximum data gathering, minimize the total energy consumption and optimize network reliability, from Sink dynamic selection of movement path to the life cycle of the entire sensor network. Through the study found that the problem is NP-hard. We then propose a mobile wireless sensor network data gathering strategy based on ant colony algorithm. Before Sink carries out the next round of data gathering, ant colony algorithm is used to estimate and selectively optimize the next hop destination according to the current network environment parameters and moving strategy. Simulation results show that compared with other data gathering methods, the proposed algorithm can produce balanced network energy, reduce the total energy consumption, improve network efficiency and reliability, prolong network lifetime.

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Acoustic ranging and communication via microphone channel

Cited by 12 publications

References 12 publications

Improving GPS Service via Social Collaboration

Improving GPS Service via Social Collaboration

Guoguo: Enabling Fine-Grained Smartphone Localization via Acoustic Anchors

An Efficient Data Gathering Protocol for Mobile Wireless Sensor Networks

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