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Wirelessly Powered Crowd Sensing: Joint Power Transfer, Sensing, Compression, and Transmission

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Wirelessly Powered Crowd Sensing : Joint Power Transfer, Sensing, Compression, and Transmission. / Li, Xiaoyang; You, Changsheng; Andreev, Sergey; Gong, Yi; Huang, Kaibin.

In: IEEE Journal on Selected Areas in Communications, Vol. 37, No. 2, 02.2019, p. 391-406.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Li, X, You, C, Andreev, S, Gong, Y & Huang, K 2019, 'Wirelessly Powered Crowd Sensing: Joint Power Transfer, Sensing, Compression, and Transmission', IEEE Journal on Selected Areas in Communications, vol. 37, no. 2, pp. 391-406. https://doi.org/10.1109/JSAC.2018.2872379

APA

Li, X., You, C., Andreev, S., Gong, Y., & Huang, K. (2019). Wirelessly Powered Crowd Sensing: Joint Power Transfer, Sensing, Compression, and Transmission. IEEE Journal on Selected Areas in Communications, 37(2), 391-406. https://doi.org/10.1109/JSAC.2018.2872379

Vancouver

Li X, You C, Andreev S, Gong Y, Huang K. Wirelessly Powered Crowd Sensing: Joint Power Transfer, Sensing, Compression, and Transmission. IEEE Journal on Selected Areas in Communications. 2019 Feb;37(2):391-406. https://doi.org/10.1109/JSAC.2018.2872379

Author

Li, Xiaoyang ; You, Changsheng ; Andreev, Sergey ; Gong, Yi ; Huang, Kaibin. / Wirelessly Powered Crowd Sensing : Joint Power Transfer, Sensing, Compression, and Transmission. In: IEEE Journal on Selected Areas in Communications. 2019 ; Vol. 37, No. 2. pp. 391-406.

Bibtex - Download

@article{61f27fc6266143cbafaa2a6c5b20be70,
title = "Wirelessly Powered Crowd Sensing: Joint Power Transfer, Sensing, Compression, and Transmission",
abstract = "Leveraging massive numbers of sensors in user equipment as well as opportunistic human mobility, mobile crowd sensing (MCS) has emerged as a powerful paradigm, where prolonging battery life of constrained devices and motivating human involvement are two key design challenges. To address these, we envision a novel framework, named wirelessly powered crowd sensing (WPCS), which integrates MCS with wireless power transfer (WPT) for supplying the involved devices with extra energy and thus facilitating user incentivization. This paper considers a multiuser WPCS system where an access point (AP) transfers energy to multiple mobile sensors (MSs), each of which performing data sensing, compression, and transmission. Assuming lossless (data) compression, an optimization problem is formulated to simultaneously maximize data utility and minimize energy consumption at the operator side, by jointly controlling wireless-power allocation at the AP as well as sensing-data sizes, compression ratios, and sensor-transmission durations at the MSs. Given fixed compression ratios, the proposed optimal power allocation policy has the threshold-based structure with respect to a defined crowd-sensing priority function for each MS depending on both the operator configuration and the MS information. Further, for fixed sensing-data sizes, the optimal compression policy suggests that compression can reduce the total energy consumption at each MS only if the sensing-data size is sufficiently large. Our solution is also extended to the case of lossy compression, while extensive simulations are offered to confirm the efficiency of the contributed mechanisms.",
keywords = "Array signal processing, Energy consumption, lossless/lossy compression, Mobile crowd sensing, Optimization, resource allocation, Resource management, Sensor systems, wireless power transfer, Wireless sensor networks",
author = "Xiaoyang Li and Changsheng You and Sergey Andreev and Yi Gong and Kaibin Huang",
year = "2019",
month = "2",
doi = "10.1109/JSAC.2018.2872379",
language = "English",
volume = "37",
pages = "391--406",
journal = "IEEE Journal on Selected Areas in Communications",
issn = "0733-8716",
publisher = "Institute of Electrical and Electronics Engineers",
number = "2",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Wirelessly Powered Crowd Sensing

T2 - Joint Power Transfer, Sensing, Compression, and Transmission

AU - Li, Xiaoyang

AU - You, Changsheng

AU - Andreev, Sergey

AU - Gong, Yi

AU - Huang, Kaibin

PY - 2019/2

Y1 - 2019/2

N2 - Leveraging massive numbers of sensors in user equipment as well as opportunistic human mobility, mobile crowd sensing (MCS) has emerged as a powerful paradigm, where prolonging battery life of constrained devices and motivating human involvement are two key design challenges. To address these, we envision a novel framework, named wirelessly powered crowd sensing (WPCS), which integrates MCS with wireless power transfer (WPT) for supplying the involved devices with extra energy and thus facilitating user incentivization. This paper considers a multiuser WPCS system where an access point (AP) transfers energy to multiple mobile sensors (MSs), each of which performing data sensing, compression, and transmission. Assuming lossless (data) compression, an optimization problem is formulated to simultaneously maximize data utility and minimize energy consumption at the operator side, by jointly controlling wireless-power allocation at the AP as well as sensing-data sizes, compression ratios, and sensor-transmission durations at the MSs. Given fixed compression ratios, the proposed optimal power allocation policy has the threshold-based structure with respect to a defined crowd-sensing priority function for each MS depending on both the operator configuration and the MS information. Further, for fixed sensing-data sizes, the optimal compression policy suggests that compression can reduce the total energy consumption at each MS only if the sensing-data size is sufficiently large. Our solution is also extended to the case of lossy compression, while extensive simulations are offered to confirm the efficiency of the contributed mechanisms.

AB - Leveraging massive numbers of sensors in user equipment as well as opportunistic human mobility, mobile crowd sensing (MCS) has emerged as a powerful paradigm, where prolonging battery life of constrained devices and motivating human involvement are two key design challenges. To address these, we envision a novel framework, named wirelessly powered crowd sensing (WPCS), which integrates MCS with wireless power transfer (WPT) for supplying the involved devices with extra energy and thus facilitating user incentivization. This paper considers a multiuser WPCS system where an access point (AP) transfers energy to multiple mobile sensors (MSs), each of which performing data sensing, compression, and transmission. Assuming lossless (data) compression, an optimization problem is formulated to simultaneously maximize data utility and minimize energy consumption at the operator side, by jointly controlling wireless-power allocation at the AP as well as sensing-data sizes, compression ratios, and sensor-transmission durations at the MSs. Given fixed compression ratios, the proposed optimal power allocation policy has the threshold-based structure with respect to a defined crowd-sensing priority function for each MS depending on both the operator configuration and the MS information. Further, for fixed sensing-data sizes, the optimal compression policy suggests that compression can reduce the total energy consumption at each MS only if the sensing-data size is sufficiently large. Our solution is also extended to the case of lossy compression, while extensive simulations are offered to confirm the efficiency of the contributed mechanisms.

KW - Array signal processing

KW - Energy consumption

KW - lossless/lossy compression

KW - Mobile crowd sensing

KW - Optimization

KW - resource allocation

KW - Resource management

KW - Sensor systems

KW - wireless power transfer

KW - Wireless sensor networks

U2 - 10.1109/JSAC.2018.2872379

DO - 10.1109/JSAC.2018.2872379

M3 - Article

VL - 37

SP - 391

EP - 406

JO - IEEE Journal on Selected Areas in Communications

JF - IEEE Journal on Selected Areas in Communications

SN - 0733-8716

IS - 2

ER -