• Journal of electromagnetic engineering and science
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• v.16 no.4
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• pp.214-218
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• 2016

In this paper, we present an ambient light backscatter communication design that enables Internet of Things (IoT) devices to communicate through the backscattering ambient light emitted from lighting infrastructure or sunlight. The device can selectively modulate ambient light by switching a liquid crystal display (LCD) shutter located on its surface, so that a nearby smart device, which includes a photodiode or a camera, can demodulate this backscattered light information. To verify the practicality of the proposed concept, we design an IoT device equipped with a commercial LCD shutter and a microcontroller. Our device produces ambient light backscattered data at a speed of 100 bps, and these data are successfully decoded by a commercial photodiode module 10 cm away from the IoT device. We believe that our ambient light backscatter communication design is appropriate for implementation in various IoT applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.7-12
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• 2019

Ambient backscatter communication is limited to channel estimation technique through a pilot signal, which is a channel estimation method in current RF communication, due to transmission power efficiency. In a limited transmission power environment, the research of traditional ambient backscatter communication has been studied assuming that it is an ideal channel without signal distortions due to channel conditions. In this paper, we propose an expectation-maximization(EM) algorithm, one of the blind channel estimation techniques, as a channel estimation method in ambient backscatter communication system which is the state of channel following normal distribution. In the proposed system model, the simulations confirm that channel estimate through EM algorithm is approaching the lower bound of the mean square error compared with the Bayesian Cramer-Rao Boundary(BCRB) to check performance. It shows that the channel parameter can be estimated in the ambient backscatter communication system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.81-86
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• 2020

Ambient backscatter communication has a drawback in which the transmission power is limited because the data is transmitted using the ambient RF signal. In order to improve transmission efficiency between transceiver, a channel estimator capable of estimating channel state at a receiver is needed. In this paper, we consider the K-means algorithm to improve the performance of the channel estimator based on EM algorithm. The simulation uses MSE as a performance parameter to verify the performance of the proposed channel estimator. The initial value setting through K-means shows improved performance compared to the channel estimation method using the general EM algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1250-1264
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• 2017

This paper presents the architecture design, implement, experimental validation of a bistatic backscatter wireless communication system in Wi-Fi network. The operating principle is to communicate a tag's data by detecting the power level of the power modulated Wi-Fi packets to be reflected or absorbed by backscatter tag, in interconnecting with Wi-Fi device and Wi-Fi AP. This system is able to provide the identification and sensor data of tag on the internet connectivity without requiring extra device for reading data, because this uses an existing Wi-Fi AP infrastructure. The backscatter tag consists of Wi-Fi energy harvesting part and a backscatter transmitter/a power-detecting receiver part. This tag can operate by harvesting and generating energy from Wi-Fi signal power. Wi-Fi device decodes information of the tag data by recognizing the power level of the backscattered Wi-Fi packets. Wi-Fi device receives the backscattered Wi-Fi packets and generates the tag's data pattern in the time-series of channel state information (CSI) values. We believe that this system can be achieved wireless connectivity for ultra- low-power IoT and wearable device.