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Open Access

Optimal Data Transmission in Backscatter Communication for Passive Sensing Systems

Jumin ZhaoJi LiDengao Li( )Haizhu Yang
School of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China.
School of Big Data, Taiyuan University of Technology, Taiyuan 030600, China.
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Abstract

Computational Radio Frequency IDentification (CRFID) is a device that integrates passive sensing and computing applications, which is powered by electromagnetic waves and read by the off-the-shelf Ultra High Frequency Radio Frequency IDentification (UHF RFID) readers. Traditional RFID only identifies the ID of the tag, and CRFID is different from traditional RFID. CRFID needs to transmit a large amount of sensing and computing data in the mobile sensing scene. However, the current Electronic Product Code, Class-1 Generation-2 (EPC C1G2) protocol mainly aims at the transmission of multi-tag and minor data. When a large amount of data need to be fed back, a more reliable communication mechanism must be used to ensure the efficiency of data exchange. The main strategy of this paper is to adjust the data frame length of the CRFID response dynamically to improve the efficiency and reliability of CRFID backscattering communication according to energy acquisition and channel complexity. This is done by constructing a dynamic data frame length model and optimizing the command set of the interface protocol. Then, according to the actual situation of the uplink, a dynamic data validation method is designed, which reduces the data transmission delay and the probability of retransmitting, and improves the throughput. The simulation results show that the proposed scheme is superior to the existing methods. Under different energy harvesting and channel conditions, the dynamic data frame length and verification method can approach the theoretical optimum.

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Tsinghua Science and Technology
Pages 647-658

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Cite this article:
Zhao J, Li J, Li D, et al. Optimal Data Transmission in Backscatter Communication for Passive Sensing Systems. Tsinghua Science and Technology, 2020, 25(5): 647-658. https://doi.org/10.26599/TST.2019.9010037

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Received: 19 April 2019
Revised: 18 July 2019
Accepted: 23 July 2019
Published: 16 March 2020
© The author(s) 2020

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).