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

Sensors

卷:19

Hwanwoong Hwang¹  Ji-Hoon Yun¹  Jae-Han Lim²  ByungJang Jeong³ 

[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;

关键词: ambient backscatter communication;    sensor network;    ultralow power communication;    sensor tag;    IoT;   

DOI  :  10.3390/s19051157

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown