Next Article in Journal
Spatiotemporal Rule of Heat Transfer on a Soil/Finned Tube Interface
Next Article in Special Issue
An Energy-Efficient Slotted Sense Multiple Access Broadcast Protocol for Reliable Command Delivery in Dynamic Wireless Sensor Networks
Previous Article in Journal
Experimental Configuration to Determine the Nonlinear Parameter β in PMMA and CFRP with the Finite Amplitude Method
Previous Article in Special Issue
Eavesdropping and Jamming Selection Policy for Suspicious UAVs Based on Low Power Consumption over Fading Channels
Open AccessArticle

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

1
Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea
2
Department of Software, Kwangwoon University, Seoul 01897, Korea
3
Electronics and Telecommunications Research Institute, Daejeon 34129, Korea
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(5), 1157; https://doi.org/10.3390/s19051157
Received: 7 February 2019 / Revised: 28 February 2019 / Accepted: 4 March 2019 / Published: 7 March 2019
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. View Full-Text
Keywords: ambient backscatter communication; sensor network; ultralow power communication; sensor tag; IoT ambient backscatter communication; sensor network; ultralow power communication; sensor tag; IoT
Show Figures

Figure 1

MDPI and ACS Style

Hwang, H.; Lim, J.-H.; Yun, J.-H.; Jeong, B.J. Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors. Sensors 2019, 19, 1157. https://doi.org/10.3390/s19051157

AMA Style

Hwang H, Lim J-H, Yun J-H, Jeong BJ. Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors. Sensors. 2019; 19(5):1157. https://doi.org/10.3390/s19051157

Chicago/Turabian Style

Hwang, Hwanwoong; Lim, Jae-Han; Yun, Ji-Hoon; Jeong, Byung J. 2019. "Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors" Sensors 19, no. 5: 1157. https://doi.org/10.3390/s19051157

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop