Data precoding and energy transmission for parameter estimation in MIMO wireless powered sensor networks

Naveen K.D. Venkategowda, Hoon Lee, Inkyu Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we study parameter estimation in multiple-input multiple-output (MIMO) wireless powered sensor networks (WPSN). The sensor nodes are powered exclusively by harvesting the radio frequency signals transmitted from the energy access points. We propose a joint design of the sensor data precoders and energy covariance matrices to minimize the mean square error (MSE) of the parameter estimate. This design also incorporates optimal allocation of the harvested power for data acquisition and data transmission. We employ a zero-forcing precoding based estimation framework and the alternating minimization technique to compute the precoders, power allocation, and energy covariance matrices. Simulation results demonstrate that the proposed method achieves a superior estimation performance in comparison to the conventional energy transfer techniques for estimation in WPSNs.

Original languageEnglish
Title of host publication2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
Volume2017-September
ISBN (Electronic)9781509059355
DOIs
Publication statusPublished - 2018 Feb 8
Event86th IEEE Vehicular Technology Conference, VTC Fall 2017 - Toronto, Canada
Duration: 2017 Sep 242017 Sep 27

Other

Other86th IEEE Vehicular Technology Conference, VTC Fall 2017
CountryCanada
CityToronto
Period17/9/2417/9/27

Fingerprint

Precoding
Multiple-input multiple-output (MIMO)
Parameter estimation
Sensor networks
Parameter Estimation
Wireless Sensor Networks
Covariance matrix
Energy
Sensor
Zero-forcing
Power Allocation
Harvesting
Optimal Allocation
Energy Transfer
Data Transmission
Data Acquisition
Sensor nodes
Mean square error
Energy transfer
Data communication systems

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Venkategowda, N. K. D., Lee, H., & Lee, I. (2018). Data precoding and energy transmission for parameter estimation in MIMO wireless powered sensor networks. In 2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings (Vol. 2017-September, pp. 1-5). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCFall.2017.8288111

Data precoding and energy transmission for parameter estimation in MIMO wireless powered sensor networks. / Venkategowda, Naveen K.D.; Lee, Hoon; Lee, Inkyu.

2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings. Vol. 2017-September Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-5.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Venkategowda, NKD, Lee, H & Lee, I 2018, Data precoding and energy transmission for parameter estimation in MIMO wireless powered sensor networks. in 2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings. vol. 2017-September, Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 86th IEEE Vehicular Technology Conference, VTC Fall 2017, Toronto, Canada, 17/9/24. https://doi.org/10.1109/VTCFall.2017.8288111
Venkategowda NKD, Lee H, Lee I. Data precoding and energy transmission for parameter estimation in MIMO wireless powered sensor networks. In 2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings. Vol. 2017-September. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-5 https://doi.org/10.1109/VTCFall.2017.8288111
Venkategowda, Naveen K.D. ; Lee, Hoon ; Lee, Inkyu. / Data precoding and energy transmission for parameter estimation in MIMO wireless powered sensor networks. 2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings. Vol. 2017-September Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-5
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