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Smartphone camera-based device-to-device communication using neural network-assisted high-density modulation

机译:使用神经网络辅助的高密度调制的基于智能手机相机的设备到设备通信

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摘要

Device-to-device (D2D) communication has become one of the focuses for future wireless communications in conjunction with rapidly growing smartphone technologies. Smartphone camera-based D2D communication is presented as a favorable solution to supporting indoor D2D communications. As a smartphone has both camera and display, two smartphones can communicate over a relatively short range distance indoors in the form of smartphone display (transmitter) and smartphone camera (receiver) link. The smartphone camera-based wireless communication called optical camera communication (OCC), however, suffers from low data rate that is at most a hundred kilobits per second. To ameliorate this, we propose a high-density modulation that is more efficient in achieving an Mbps rate for smartphone camera-based D2D systems, by exploiting two-dimensional data transmission capability in OCC. Neural network is also implemented to improve the performance of the proposed system. To verify the proposed system, simulations and experiments were performed. It is demonstrated that a 2.66 Mbps rate of the proposed system is achieved with an acceptable bit error rate.
机译:设备到设备(D2D)通信已成为与快速增长的智能手机技术结合使用的未来无线通信的重点之一。提出了基于智能手机相机的D2D通信,作为支持室内D2D通信的理想解决方案。由于智能手机同时具有摄像头和显示器,因此两个智能手机可以在室内相对较短的距离范围内以智能手机显示屏(发送器)和智能手机摄像头(接收器)链接的形式进行通信。但是,基于智能手机相机的无线通信称为光学相机通信(OCC),其数据速率低至每秒100 kb。为了改善这一点,我们提出了一种高密度调制,通过利用OCC中的二维数据传输功能,可以更有效地实现基于智能手机相机的D2D系统的Mbps速率。还实现了神经网络以改善所提出系统的性能。为了验证所提出的系统,进行了仿真和实验。证明了以可接受的误码率实现了所提出系统的2.66 Mbps速率。

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