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Journal Article
Pattern-Based Decoding for Wi-Fi Backscatter Communication of Passive Sensors
- Authors
- Hwanwoong Hwang, Jae-Han Lim, Ji-Hoon Yun, Byung Jang Jeong
- Issue Date
- 2019-03
- Citation
- Sensors, v.19, no.5, pp.1-18
- ISSN
- 1424-8220
- Publisher
- MDPI
- Language
- English
- Type
- Journal Article
- Project Code
- 18HF1100, Maximization of wireless communication efficiency based on compression sensing, non-power supply and super high-speed mobility, Lee Woo Yong
- Abstract
- 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 againstWi-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 ofWi-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.
- KSP Keywords
- Ambient RF, Backscatter Communication, Bit Error Rate(And BER), OFDM signal, Pattern-based, Power Consumption, RF signal, Sensing data, Threshold configuration, Ultralow power(ULP), WI-Fi
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
