Abstract
This paper proposes a novel method of training and applying a neural network to act as an adaptive decoder for a modulation scheme used in optical camera communication (OCC). We present a brief discussion on trending artificial intelligence applications, the contemporary ways of applying them in a wireless communication field, such as visible light communication (VLC), optical wireless communication (OWC) and OCC, and its potential contribution in the development of this research area. Furthermore, we proposed an OCC vehicular system architecture with artificial intelligence (AI) functionalities, where dimmable spatial 8-phase shift keying (DS8-PSK) is employed as one out of two modulation schemes to form a hybrid waveform. Further demonstration of simulating the blurring process on a transmitter image, as well as our proposed method of using a neural network as a decoder for DS8-PSK, is provided in detail. Finally, experimental results are given to prove the effectiveness and efficiency of the proposed method over an investigating channel condition.
Highlights
Nowadays, light-emitting diodes (LEDs) are widely used as common lighting sources because of their numerous advantages, such as excellent visibility, durability, and low power consumption.the ability to switch the light intensity fast [1,2] gives LEDs the abilities to transmit high-speed data, provided that the switching rate, or frequency, is higher than 200Hz for human eyes’safety [3]
optical camera communication (OCC) has a lower data rate compared to visible light communication (VLC) since it receives data via an image sensor [4,5], OCC is still preferable in applications where mobility is crucial because of the wider field of view (FoV) of a camera compared to a photodiode, for example, indoor localization using a personal smartphone [6,7] or vehicular OCC
We propose a new method of using deep learning and neural network (NN) to decode the high-rate OCC waveform (DS8-PSK): The model architecture and dataset preparation for training and performance testing
Summary
Light-emitting diodes (LEDs) are widely used as common lighting sources because of their numerous advantages, such as excellent visibility, durability, and low power consumption. Many studies have been carried out to demonstrate the feasibility of OWC/OCC technology in V2V/V2X systems (see, for example, [8,9,10]), and mostly, the performance is investigated with respect to Gaussian white noise with different signal-to-noise ratio (SNR) values Another type of distortion that can reduce the performance of a vehicular OWC/OCC system is blurred phenomenon, which generally occurs in any system related to camera and image processing. Deep learning has proved itself as an efficient tool to deal with various types of problems, including computer vision [14], speech recognition [15], autonomous vehicles [16], and many others Inspired by these developments, recently many efforts have been made to apply deep learning/AI technologies in communication field (including channel decoding) [17,18,19,20,21,22].
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