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Wi-Fi Backscatter System With Tag Sensors Using Multi-Antennas for Increased Data Rate and Reliability. | LitMetric

Wi-Fi Backscatter System With Tag Sensors Using Multi-Antennas for Increased Data Rate and Reliability.

Sensors (Basel)

Department of Information and Communication Engineering, Sejong University, Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea.

Published: February 2020

In this paper, we propose tag sensor using multi-antennas in a Wi-Fi backscatter system, which results in an improved data rate or reliability of the signal transmitted from a tag sensor to a reader. The existing power level modulation method, which is proposed to improve data rate in a Wi-Fi backscatter system, has low reliability due to the reduced distance between symbols. To address this problem, we propose a Wi-Fi backscatter system that obtains channel diversity by applying multiple antennas. Two backscatter methods are described for improving the data rate or reliability in the proposed system. In addition, we propose three low complexity demodulation methods to address the high computational complexity problem caused by multiple antennas: (1) SET (subcarrier energy-based threshold) method, (2) TCST (tag's channel state-based threshold) method, and (3) SED (similar Euclidean distance) method. In order to verify the performance of the proposed backscatter method and low complexity demodulation schemes, the 802.11 TGn (task group n) channel model was utilized in simulation. In this paper, the proposed tag sensor structure was compared with existing methods using only sub-channels with a large difference in received CSI (channel state information) values or adopting power-level modulation. The proposed scheme showed about 10 dB better bit error rate (BER) performance and throughput. Also, proposed low complexity demodulation schemes were similar in BER performance with a difference of up to 1 dB and the computational complexity was reduced by up to 60% compared to the existing Euclidean distance method.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085517PMC
http://dx.doi.org/10.3390/s20051314DOI Listing

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