Complementary Color Barcode-Based Optical Camera Communications

In order to increase the data rate of the optical camera communication (OCC) system, the 8-composite-amplitude-shift-keying modulation (8CASK) OCC system is used in this work. However, if the static decision thresholds are employed to demodulate multi-level ASK signal, uneven illumination of LED lamps and LED light-emitting instability lead to the fluctuation of the gray range in the picture and degrade the bit-error-rate (BER) performance. In this work, we propose and demonstrate a demodulation scheme, using the uneven illumination compensation algorithm, the pixel matrix threshold overall update algorithm and the secondary decision algorithm, to mitigate the impact of illumination unevenness and LED light-emitting instability. The BER performance is evaluated and compared with other demodulation schemes. The experimental results demonstrate that the communication rate of our proposed scheme can reach 9kbit/s at a distance of 250 cm where the illumination is 135lux, and the BER is 8.01 × 10−5.

Data rate and communication distance are two important criteria for measuring the performance of optical camera communication (OCC) systems. Intensive researches have been made to find possible solutions to improve these two performance indicators. However, most existing literature either provides solutions which closely related to the experimental parameters of their own designed OCC systems or provides models which are suitable for visible light communication (VLC) and cannot be directly used in OCC. Motivated by this, we propose a simplified system model for OCC in this paper. By jointly applying Lambertian model for the transmitter light-emitting diode (LED), channel direct current (DC) gain for free space channel, and mathematical descriptions for the imaging process of the camera receiver, the proposed model provides the relationship between the optical transmission power and the final pixel values on the image sensor. We specifically explore the parameters of the transmission distance and the exposure time based on the proposed model. Simulation results qualitatively and quantitatively explore the influences of these two parameters on the final pixel values. Our proposed model can provide guidance for the design of a generalized OCC system as well as the selection of demodulating threshold, thus it can help to realize a highperformance OCC system.

To enable a higher transmission rate in optical camera communication (OCC) systems, severe inter-symbol interference (ISI) occurs owing to the reduction of the number of pixel-row-per-bit (PPB). Therefore, those pixels representing data bit 0 or 1 may have same gray scale values, significantly deteriorating the bit decision when using the conventional thresholding scheme. In this Letter, a simple yet efficient scheme, referred to as nearest neighbor bit assisted decision (NNBAD) scheme, is proposed and experimentally demonstrated for signal decision in OCC systems. NNBAD leverages the nearest neighbor bit to jointly assist bit decision for pixels with severe ISI. Experimental results show that, for OCC systems with on-off keying (OOK) modulation, those pixels with severe ISI cannot be distinguished by the conventional thresholding scheme. Yet, the NNBAD scheme exhibits strong robustness against ISI, remarkably improving the bit error rate (BER) performance. The proposed scheme can achieve a throughput of 8.2 kbps with OOK modulation under an illuminance of 600 lx.

Optical camera communication (OCC) shows promise for optical wireless communication (OWC) in vehicular networks. However, vehicle mobility-induced angular distortions hinder system throughput by degrading non-isotropic vehicular OCC channel gain. Few of the prior works have ever made a comprehensive analysis of their impact, especially based on the pixel value which reflects the camera imaging features. To address this knowledge gap, a pixel value-described vehicular OCC system model accounting for transmitter imaging location and intensity from the geometry and radiometry aspects is presented in this paper with common types of the offset and rotation angles included. We integrate a MATLAB-based simulated vehicular OCC system with an experimentally designed testbed for validation and performance analysis. For a single-time snapshot, we investigate the impacts of common angular distortion types in vehicular OCC systems on maximum pixel value, imaging location, and communication-related metrics. Furthermore, we statistically analyze their influences by considering two driving scenarios with respective angular distributions. The angular distortion characterization from this work is expected to lay a stepping stone to addressing mobility in vehicular OCC systems.

As mobile payments become increasingly popular, the security of the transaction process should be taken more seriously. Many mobile phones are equipped with complementary metal-oxide-semiconductor (CMOS) cameras, which can be used as visible light communication (VLC) receivers. An optical camera communication (OCC) system is a special VLC system that uses an optical camera as a receiver. OCC offers acceptable security, but challenges remain. In this paper, we propose an OCC system that uses an optical camera with a rolling shutter as a receiver and a light-emitting diode (LED) panel light as a transmitter. The feature of an LED panel light serving as a surface light source reduces the possibility of overexposure and avoids the blooming effect of the camera. The rolling shutter effect of the CMOS camera is used to increase the data rate, which is numerically much higher than the frame rate. Finally, the results of a symbol error rate (SER) test show that the VLC system exhibits error-free performance. The data rate is approximately 4.2kb/s, while the net data rate is approximately 2.46kb/s due to the redundancy of the 3-9 code bar code and the redundant cycle. This data rate is sufficient for mobile payments, which require only 60bits of data at a time.

In this work, we propose a multiple inputs multiple outputs (MIMO) non-line-of-sight (NLOS) optical camera communication (OCC) system with multi-level pulse width modulation (MPWM) and difference-based pulse width recognition (DBPWR) schemes. The MPWM signals transmitted over a NLOS link are recovered using the DBPWR algorithm. Compared with the conventional threshold-based demodulation scheme, the proposed DBPWR scheme has lower complexity, higher reliability, and improved sampling frequency offset tolerance. A total data rate of 3.6 kb/s is experimentally demonstrated for more than 2 m NLOS link using the proposed MIMO OCC system, which is sufficient in many Internet of things applications.

This paper presents a method for performing traffic light detection using computer vision. Reliable traffic light detection and classification is crucial for automated driving in urban environments. By using big data and artificial intelligence, a complex dataset belonging to an urban area in China is preprocessed to determine the level of vehicular congestion, and then different machine learning algorithms are applied to a dataset of traffic light images in order to validate them in the urban environment to be studied, this process is explained step by step. The models obtained in this work can be applied in optical camera communication (OCC) systems, and also in intelligent transportation systems (ITS), using tracking channels for visible light communication (VLC). The two optical channels, VLC and OCC, are simulated in terms of the quality of information received in order to apply the previously generated datasets. In this work, a traffic light feature dataset has been generated from images and two traffic light classification models present in images and video frames have been generated from their features, obtaining a maximum accuracy of 94.52 %.

Nowadays, the coherent optical communication system plays an important role in communication field because of large capability and bandwidth. A coherent optical communication, based on high-order modulation and digital signal processing technologies, consists of optical transmitters, optical fiber lines, optical amplifiers and optical receivers. In the high-speed coherent optical communication system, the phase noise from the transmitter laser and the local oscillator laser can significantly degrade the performance of the signal transmission and detection, especially for the systems using high-order modulation format, such as m-ary phase shift keying (mPSK) and m-ary quadrature amplitude modulation (m-QAM). Therefore, investigations on laser phase noise compensation algorithm based on digital signal processing technologies has become more and more significant. In this work, a multi-ring carrier phase recovery algorithm is developed for compensating the laser phase noise in optical fiber communication systems using high-order modulation formats. Degradations on the performance of communication systems due to the laser phase noise have been investigated. The system performance using the proposed algorithm and the conventional Viterbi-Viterbi algorithm were also evaluated in 9-channel and 15- channel, 32-Gbaud, Nyquist-spaced QPSK, 16-QAM, 64-QAM and 256-QAM coherent transmission systems with considering the impact of the laser phase noise. It is found that the phase noise leads to stricter constraints on the linewidths of transmitter-side and receiver-side lasers, and it can greatly degrade the achievable information rates in communication systems. Besides, compared to the conventional Viterbi-Viterbi algorithm, which is usually applied in the QPSK system, our proposed algorithm can also well mitigate the laser phase noise in 16-QAM, 64-QAM and 256-QAM optical communication systems.
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Nowadays, underwater activities are becoming more and more important. As the number of underwater sensing devices grows rapidly, the amount of bandwidth needed also increases very quickly. Apart from underwater communication, direct communication across the water–air interface is also highly desirable. Air-to-water wireless transmission is crucial for sending control information or instructions from unmanned aerial vehicles (UAVs) or ground stations above the sea surface to autonomous underwater vehicles (AUVs). On the other hand, water-to-air wireless transmission is also required to transmit real-time information from AUVs or underwater sensor nodes to UAVs above the water surface. Previously, we successfully demonstrated a water-to-air optical camera-based OWC system, which is also known as optical camera communication (OCC). However, the reverse transmission (i.e., air-to-water) using OCC has not been analyzed. It is worth noting that in the water-to-air OCC system, since the camera is located in the air, the image of the light source is magnified due to diffraction. Hence, the pixel-per-symbol (PPS) decoding of the OCC pattern is easier. In the proposed air-to-water OCC system reported here, since the camera is located in the water, the image of the light source in the air will be diminished in size due to diffraction. Hence, the PPS decoding of the OCC pattern becomes more difficult. In this work, we propose and experimentally demonstrate a wide field-of-view (FOV) air-to-water OCC system using CUDA Deep-Neural-Network Long-Short-Term-Memory (CuDNNLSTM). Due to water turbulence and air turbulence affecting the AUV and UAV, a precise line-of-sight (LOS) between the AUV and the UAV is difficult to achieve. OCC can provide wide FOV without the need for precise optical alignment. Results revealed that the proposed air-to-water OCC system can support a transmission rate of 7.2 kbit/s through a still water surface, and 6.6 kbit/s through a wavy water surface; this satisfies the hard-decision forward error correction (HD-FEC) bit-error-rate (BER).

Guest Editorial

光纤通信已经成为目前通信网络发展的主流方向。但是随着光纤通信系统向着超远距离、超大容量、超高速率的方向发展，光纤色散已经成为其巨大的阻碍。如何有效地控制光通信系统中产生的色散，使光信号在大容量、高速率、长距离传输中无误码地到达接收端，已经成为人们迫切需要解决的问题。对光通信系统中的色散进行监测并进行动态补偿的研究，使得超大容量、超长距离、超高速率的光纤通信系统成为可能，有助于最终实现全光智能自动交换网络。在众多测量光纤色散的方法中，调制相移法具有结构简单，可靠性强等优点。本文中，我们对使用调制相移法测量光纤色散进行了研究和仿真，讨论了在不同光纤长度和不同调制频率下，影响调制相移法测量结果精度的因素。通过适当地选取调制频率，我们可以使用调制相移法测得不同光纤长度下色散的精确值。另外在本文中，我们通过仿真验证了调制相移法可以测量具有任意色散–波长曲线的光纤。因此在实际应用中，调制相移法是可以应用于高精度光纤色散的测量。 Optical fiber communication is the mainstream of communication development at present. However, with the development of optical fiber communication system which trending towards ultra-long length, ultra-large capacity and ultra-high speed, fiber dispersion turned to be a great obstacle. How to control the dispersion created in the optical communication system effectively while force optical signal to reach the receiving end in high-capacity, high-rate and error-free long-distance transmission has increasingly become a research focus of optical fiber communication systems. It is a great significance to research about monitor and dynamic compensate dispersion in the optical communication systems, so that the ultra-large capacity, ultra-long length and ultra-high speed optical fiber communication systems would not be impossible, all-optical intelligent network with automatic switching functions would come true. Among the varieties of methods to measure fiber dispersion, the phase-modulation shift method is the unique one, which has the advantages of simple structure, high reliability. In this paper, we make a research and simulate to use the phase-modulation shift method, meanwhile we also discuss about the factors which affect the accuracy of the results in the different fiber lengths and modulation frequencies. By the means that selecting appropriate modulation frequency, we can use modulation phase shift method to measure the exact value of dispersion comes out from different lengths of fiber. Moreover, this paper also proves that the phase-modulation shift method is able to measure the optical fiber with arbitrary dispersion-wavelength curve, which is already verified by our simulation. Therefore, the phase-modulation shift method is well to be applied to take practice in the high-precision fiber dispersion measurement.

In this work, a new Time Difference of Arrival (TDoA) scheme for distance measurement based on Optical Camera Communication (OCC) systems is proposed. It relies on the use of optical pulses instead of radio-frequency signals as the time reference triggers, and the introduction of a rolling shutter camera, whose characteristics allows substituting the timer modules used in conventional TDoA techniques by image processing of the illuminated area in the picture. This processing on the camera’s images provides time measurements and implies and specific analysis, which is presented in this work. The system performance and properties, such as resolution and range, mainly depends on the camera characteristics, such as the frames capture rate and the image quality. This new technique is suitable to be implemented in smartphones or other Commercial Off-The-Shelf (COTS) devices equipped with a camera and speakers.

The efficient and accurate evaluation of the transmission performance of high-capacity optical communication systems has always attracted significant research attentions. The enhanced Gaussian noise (EGN) model is considered as an excellent solution to predict the system performance taking into account linear and nonlinear transmission impairments. Since the conventional form of the EGN model is complicated and intractable for a fast computation, the closed-form simplification has been regarded as a direction to significantly reduce the computational complexity. However, the accuracy of such a closed-form EGN model becomes a main concern in the application of ultra-wideband optical communication systems. In this work, we have investigated the accuracy of the closed-form EGN model for ultra-wideband optical fiber communication systems, where the performance of the system using electronic dispersion compensation, multi-channel nonlinearity compensation and full-field nonlinearity compensation has been evaluated in terms of symbol rate, number of channels and signal power. Our work will provide an insight on the application of the EGN model in next-generation ultra-wideband long-haul optical fiber communication networks.

Deep neural networks (DNNs) have been applied to recover signals in optical communication systems and have shown competence of mitigating linear and nonlinear distortions. However, as the data throughput increases, the heavy computational cost of DNNs impedes them from rapid and power-efficient processing. In this paper, we propose an optical communication signal recovery technology based on a photonic convolutional processor, which is realized by dispersion delay unit and wavelength division multiplexing. Based on the photonic convolutional processor, we implement an optoelectronic convolutional neural network (OECNN) for signal post-equalization and experimentally demonstrate on 16QAM and 32QAM of an optical wireless communication system. With system parameters optimization, we verify that the OECNN can achieve accurate signal recovery where the bit error ratio (BER) is below the 7% forward error correction threshold of 3.8×10-3 at 2Gbps. With adding the OECNN-based nonlinear compensation, compared with only linear compensation, we improve the quality (Q) factor by 3.35 dB at 16QAM and 3.30 dB at 32QAM, which is comparable to that of an electronic neural network. This work proves that the photonic implementation of DNN is promising to provide a fast and power-efficient solution for optical communication signal processing.

In this paper, an optical camera communication system utilizing the under-sampled phase shift ON-OFF keying modulation is proposed to support non-flickering visible light communication. This system sends three types of light symbols through light emitting diode (LED) lamps, which are recorded by a camera. By employing a dual LED lamp with a designated mapping and framing method, the data rate can reach up to 3 times of the camera's frame rate. The experiment results show that the proposed camera communication system can achieve 150 bps error-free communications for a range up to 12 m.