Square Wave Quadrature Amplitude Modulation for Visible Light Communication Using Image Sensor

Alfarozi, Syukron Abu Ishaq; Pasupa, Kitsuchart; Hashizume, Hidetoshi; Woraratpanya, Kuntpong; Sugimoto, Masanori

doi:10.1109/access.2019.2928417

Cited by 8 publications

(27 citation statements)

References 21 publications

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“…According to the results of our SW-QAM scheme in [6], the theoretical encoding and decoding always perform well in a controllable situation. However, in practice, the existence of a large amount of noise and light interference becomes a serious problem in the decoding stage.…”

Section: A Neural Decodingmentioning

confidence: 82%

“…As described in [6], SW-QAM decoder requires essential complementary techniques such as LED localization, light interference elimination, and noise removal. However, these techniques may provide a sub-optimal performance because the performance of the entire system will depend on the performance of each particular method.…”

Section: Brief Reviewmentioning

confidence: 99%

“…Moreover, it is also powerful in estimating unknown parameters. Due to NN's capability in a variety of tasks, we can take the advantage of NN on light interference elimination, noise removal, and correct decoding in VLC with a camera receiver, especially when working with an SW-QAM modulation scheme [6]. The problem of using a camera as a receiver in VLC is no different from that in computer vision.…”

Section: A Neural Decodingmentioning

confidence: 99%

“…1, it can be seen that our proposed scheme uses a single neural decoder instead of multiple complementary methods, each of which overcomes a specific problem such as light interference elimination and LED localization. Inside our proposed scheme, the neural decoding does not require the PSF modeling to reduce the light interference among LEDs as the Wiener deconvolution method does, as described in [6]. Also, the position of the LED points and the image features are automatically detected in the training stage of the neural network.…”

Section: A Neural Decodingmentioning

confidence: 99%

“…In this paper, the great potential of CNN is also applied to visible light communication (VLC) research especially for the square wave quadrature amplitude modulation (SW-QAM) scheme [6]. In image-sensor-based VLC, an image sensor or a camera plays the role of a receiver that captures a sequence of LED images and then decodes the captured images back to a sequence of symbols as described in SW-QAM.…”

Section: Introductionmentioning

confidence: 99%

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Robust and Unified VLC Decoding System for Square Wave Quadrature Amplitude Modulation Using Deep Learning Approach

et al. 2019

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We have proposed a square wave quadrature amplitude modulation (SW-QAM) scheme for visible light communication (VLC) using an image sensor in our previous work. Here, we propose a robust and unified system by using a neural decoding method. This method offers essential SW-QAM decoding capabilities, such as LED localization, light interference elimination, and unknown parameter estimation, bundled into a single neural network model. This work makes use of a convolutional neural network (CNN) that has a capability in automatic learning of unknown parameters, especially when it deals with images as an input. The neural decoding method can provide good solutions for two difficult conditions that are not covered by our previous SW-QAM scheme: unfixed LED positions and multiple point spread functions (PSFs) of multiple LEDs. Responding to the above solutions, three recent CNN architectures-VGG, ResNet, and DenseNet-are modified to suit our scheme and other two small CNN architectures-VGG-like and MiniDenseNet-are proposed for low computing devices. Our experimental results show that the proposed neural decoding method performs better in terms of error rate than the theoretical decoding, an SW-QAM decoder with a Wiener filter, in different scenarios. Furthermore, we experiment on the problem of moving camera, i.e., the unfixed position of LED points. For this case, a spatial transformer network (STN) layer is added to the neural decoding method for solving the moving camera problem, and the method with the new layer achieves a remarkable result. INDEX TERMS Visible light communication, image sensor communication (ISC), SW-QAM, optical camera communication (OCC), neural decoding, convolutional neural network (CNN), deep learning.

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Section: A Neural Decodingmentioning

confidence: 82%

Section: Brief Reviewmentioning

confidence: 99%

Section: A Neural Decodingmentioning

confidence: 99%

Section: A Neural Decodingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust and Unified VLC Decoding System for Square Wave Quadrature Amplitude Modulation Using Deep Learning Approach

et al. 2019

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A multi-parameter tunable plasmon modulator

Lü

Zhao

et al. 2023

Sci Rep

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Multi-parameter control of light is a key functionality to modulate optical signals in photonic integrated circuits for various applications. However, the traditional optical modulators can only control one or two properties of light at the same time. Herein, we propose a hybrid structure which can modulate the amplitude, wavelength and phase of surface plasmon polaritons (SPPs) simultaneously to overcome these limitations. The numerical results show that when the Fermi level of graphene changes from 0.3 to 0.9 eV, the variation of optical transmission, wavelength and phase are 32.7 dB, 428 nm and 306°, respectively. The demonstrated structure triggers an approach for the realization of ultracompact modulation and has potential applications in the fields of optical switches, communications and photo-detection.

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Stochastic dynamics of stochastic delay Duffing oscillator and sensitivity analysis to different types of signals

Wang

Zhang

Yang

2023

Meas. Sci. Technol.

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In this paper, a stochastic delay diﬀerential system driven by the square wave signal is presented. The sensitivity of the system to diﬀerent types of signals is evaluated by the dynamic behaviors of the system. The stochastic dynamic behaviors of the system is analyzed theoretically, and the theoretical chaotic threshold under diﬀerent external excitation signals is deduced. The numerical simulation results show that the stochastic delay diﬀerential system is more sensitive to the square wave signals with the same frequency than the harmonic signal and the square wave signal with the diﬀerent frequency.

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Square Wave Quadrature Amplitude Modulation for Visible Light Communication Using Image Sensor

Cited by 8 publications

References 21 publications

Robust and Unified VLC Decoding System for Square Wave Quadrature Amplitude Modulation Using Deep Learning Approach

Robust and Unified VLC Decoding System for Square Wave Quadrature Amplitude Modulation Using Deep Learning Approach

A multi-parameter tunable plasmon modulator

Stochastic dynamics of stochastic delay Duffing oscillator and sensitivity analysis to different types of signals

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