Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors

Ambient backscatter communication enables passive sensors to convey sensing data on ambient RF signals in the air at ultralow power consumption. To extract data bits from such signals, threshold-based decoding has generally been considered, but suffers against Wi-Fi signals due to severe fluctuation...

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Main Authors: Hwanwoong Hwang, Jae-Han Lim, Ji-Hoon Yun, Byung Jang Jeong
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Sensors
Subjects:
IoT
Online Access:http://www.mdpi.com/1424-8220/19/5/1157
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spelling doaj-413d47bfb0404a29a87148b13cb3b3f42020-11-25T00:05:02ZengMDPI AGSensors1424-82202019-03-01195115710.3390/s19051157s19051157Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive SensorsHwanwoong Hwang0Jae-Han Lim1Ji-Hoon Yun2Byung Jang Jeong3Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, KoreaDepartment of Software, Kwangwoon University, Seoul 01897, KoreaDepartment of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, KoreaElectronics and Telecommunications Research Institute, Daejeon 34129, KoreaAmbient backscatter communication enables passive sensors to convey sensing data on ambient RF signals in the air at ultralow power consumption. To extract data bits from such signals, threshold-based decoding has generally been considered, but suffers against Wi-Fi signals due to severe fluctuation of OFDM signals. In this paper, we propose a pattern-matching-based decoding algorithm for Wi-Fi backscatter communications. The key idea is the identification of unique patterns of signal samples that arise from the inevitable smoothing of Wi-Fi signals to filter out noisy fluctuation. We provide the mathematical basis of obtaining the pattern of smoothed signal samples as the slope of a line expressed in a closed-form equation. Then, the new decoding algorithm was designed to identify the pattern of received signal samples as a slope rather than classifying their amplitude levels. Thus, it is more robust against signal fluctuation and does not need tricky threshold configuration. Moreover, for even higher reliability, the pattern was identified for a pair of adjacent bits, and the algorithm decodes a bit pair at a time rather than a single bit. We demonstrate via testbed experiments that the proposed algorithm significantly outperforms conventional threshold-based decoding variants in terms of bit error rate for various distances and data rates.http://www.mdpi.com/1424-8220/19/5/1157ambient backscatter communicationsensor networkultralow power communicationsensor tagIoT
collection DOAJ
language English
format Article
sources DOAJ
author Hwanwoong Hwang
Jae-Han Lim
Ji-Hoon Yun
Byung Jang Jeong
spellingShingle Hwanwoong Hwang
Jae-Han Lim
Ji-Hoon Yun
Byung Jang Jeong
Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors
Sensors
ambient backscatter communication
sensor network
ultralow power communication
sensor tag
IoT
author_facet Hwanwoong Hwang
Jae-Han Lim
Ji-Hoon Yun
Byung Jang Jeong
author_sort Hwanwoong Hwang
title Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors
title_short Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors
title_full Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors
title_fullStr Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors
title_full_unstemmed Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors
title_sort pattern-based decoding for wi-fi backscatter communication of passive sensors
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2019-03-01
description Ambient backscatter communication enables passive sensors to convey sensing data on ambient RF signals in the air at ultralow power consumption. To extract data bits from such signals, threshold-based decoding has generally been considered, but suffers against Wi-Fi signals due to severe fluctuation of OFDM signals. In this paper, we propose a pattern-matching-based decoding algorithm for Wi-Fi backscatter communications. The key idea is the identification of unique patterns of signal samples that arise from the inevitable smoothing of Wi-Fi signals to filter out noisy fluctuation. We provide the mathematical basis of obtaining the pattern of smoothed signal samples as the slope of a line expressed in a closed-form equation. Then, the new decoding algorithm was designed to identify the pattern of received signal samples as a slope rather than classifying their amplitude levels. Thus, it is more robust against signal fluctuation and does not need tricky threshold configuration. Moreover, for even higher reliability, the pattern was identified for a pair of adjacent bits, and the algorithm decodes a bit pair at a time rather than a single bit. We demonstrate via testbed experiments that the proposed algorithm significantly outperforms conventional threshold-based decoding variants in terms of bit error rate for various distances and data rates.
topic ambient backscatter communication
sensor network
ultralow power communication
sensor tag
IoT
url http://www.mdpi.com/1424-8220/19/5/1157
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AT jihoonyun patternbaseddecodingforwifibackscattercommunicationofpassivesensors
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