Amirul Islam

Current Status and Performance Analysis of Optical Camera Communication Technologies for 5G Networks

This paper investigates optical camera communication (OCC) technologies, targeting new spectrum, multiple-input-multiple-output diversity, transmission access, and novel architectures with augmented reality user experience for the extended 5G wireless network. It provides the current OCC research status and trend pertaining to these technologies, especially an inside view on the revision of IEEE 802.15.7-2011 known as the IEEE 802.15.7m (TG7m) Optical Wireless Communication Task Group. Such standardization activities have a major impact on the development of OCC technologies. In addition, it provides a detailed review of the related literature. Herein, OCC technologies are classified into five categories to elucidate their operations and technical characteristics. Furthermore, a concise performance analysis, numerical simulations, and some comparison of the results obtained for associated systems are presented, and the future directions of research and development are discussed.

Survey of Promising Technologies for 5G Networks

As an enhancement of cellular networks, the future-generation 5G network can be considered an ultra-high-speed technology. The proposed 5G network might include all types of advanced dominant technologies to provide remarkable services. Consequently, new architectures and service management schemes for different applications of the emerging technologies need to be recommended to solve issues related to data traffic capacity, high data rate, and reliability for ensuring QoS. Cloud computing, Internet of things (IoT), and software-defined networking (SDN) have become some of the core technologies for the 5G network. Cloud-based services provide flexible and efficient solutions for information and communications technology by reducing the cost of investing in and managing information technology infrastructure. In terms of functionality, SDN is a promising architecture that decouples control planes and data planes to support programmability, adaptability, and flexibility in ever-changing network architectures. However, IoT combines cloud computing and SDN to achieve greater productivity for evolving technologies in 5G by facilitating interaction between the physical and human world. The major objective of this study provides a lawless vision on comprehensive works related to enabling technologies for the next generation of mobile systems and networks, mainly focusing on 5G mobile communications.

High temporal-spatial resolution optical wireless communication technique using image sensor

Optical wireless communication (OWC) has recently been considered as one of the efficient and supportive technologies in automotive applications that drive attraction both in R&D and in their practical applications. Exchanging information about the relative directional position of each vehicle together with front and rear-facing direction is significant for fast, accurate and reliable communication. Radio Frequency (RF) (causing extensive interference) or expensive laser (Laser) that is also harmful to the human body are the currently available technology for vehicular communication purposes. Some existing technologies are also using visible light (i.e. LEDs) communications (VLC). But these technologies have the limitation of fast object detection and multiple objects detection as well as maintaining communication simultaneously. However, ensuring high temporal and spatial detection resolution has become one of the challenging tasks for OWC. This paper proposes an image sensor based OWC technique to ensure high temporal and spatial resolution based on VLC system. We proposed an algorithm to support multiple objects detection and communication principal in temporal and spatial condition. We have simulated different scenarios related to spatial and temporal condition using Matlab simulation. The results reveal that our proposed method ensure high temporal and spatial resolution criteria. After all, it also provides secure and fast communication at critical and multiple objects condition efficiently without deploying any tracking method.

Region-of-Interest Signaling Vehicular System Using Optical Camera Communications

This technical paper introduces an optical camera communication system for vehicles. The purpose of the communication system incorporated into car (using existing light-emitting diode (LED) lights and ordinary cameras) is to add region-of-interest signaling functionality for cars via either their headlights or taillights. A low-data-rate but reliable link via the optical channel is the objective. In particular, the communication system, contributes a spatial modulation approach called spatial-2-phase-shift keying (S2-PSK) that uses a pair of optical light sources on a car (either a pair of rear-LEDs or a pair of front-LEDs) as a transmitter. A typical camera (i.e., less than 30 frames/s), either a global shutter or a rolling shutter, can be used to receive light-modulated data. As a remarkable physical layer (PHY) operating mode among image sensor communication PHY modes recently contributed to IEEE 802.15.7r1 (TG7r1), the communication system, along with technical details on the S2-PSK communication protocol, is described in this paper. In addition, in order to deal with the noisy optical channel and the low-performance challenge of a camera receiver, we have suggested a rate-1/2 line coding and an intelligent decoding approach in our intended vehicular communication scenario. Finally, numerical analyses on the performance of our system and experiment results are addressed.

Performance analysis of smart digital signage system based on software-defined IoT and invisible image sensor communication:

Everything in the world is being connected, and things are becoming interactive. The future of the interactive world depends on the future Internet of Things (IoT). Software-defined networking (SDN) technology, a new paradigm in the networking area, can be useful in creating an IoT because it can handle interactivity by controlling physical devices, transmission of data among them, and data acquisition. However, digital signage can be one of the promising technologies in this era of technology that is progressing toward the interactive world, connecting users to the IoT network through device-to-device communication technology. This article illustrates a novel prototype that is mainly focused on a smart digital signage system comprised of software-defined IoT (SD-IoT) and invisible image sensor communication technology. We have proposed an SDN scheme with a view to initiating its flexibility and compatibility for an IoT network-based smart digital signage system. The idea of invisible communication can make the users of the technology trendier to it, and the usage of unused resources such as images and videos can be ensured. In addition, this communication has paved the way for interactivity between the user and digital signage, where the digital signage and the camera of a smartphone can be operated as a transmitter and a receiver, respectively. The proposed scheme might be applicable to real-world applications because SDN has the flexibility to adapt with the alteration of network status without any hardware modifications while displays and smartphones are available everywhere. A performance analysis of this system showed the advantages of an SD-IoT network over an Internet protocol-based IoT network considering a queuing analysis for a dynamic link allocation process in the case of user access to the IoT network.

A Novel Indoor Mobile Localization System Based on Optical Camera Communication

Localizing smartphones in indoor environments offers excellent opportunities for e-commence. In this paper, we propose a localization technique for smartphones in indoor environments. This technique can calculate the coordinates of a smartphone using existing illumination infrastructure with light-emitting diodes (LEDs). The system can locate smartphones without further modification of the existing LED light infrastructure. Smartphones do not have fixed position and they may move frequently anywhere in an environment. Our algorithm uses multiple (i.e., more than two) LED lights simultaneously. The smartphone gets the LED-IDs from the LED lights that are within the field of view (FOV) of the smartphone’s camera. These LED-IDs contain the coordinate information (e.g., - and -coordinate) of the LED lights. Concurrently, the pixel area on the image sensor (IS) of projected image changes with the relative motion between the smartphone and each LED light which allows the algorithm to calculate the distance from the smartphone to that LED. At the end of this paper, we present simulated results for predicting the next possible location of the smartphone using Kalman filter to minimize the time delay for coordinate calculation. These simulated results demonstrate that the position resolution can be maintained within 10 cm.

Simplified photogrammetry using optical camera communication for indoor positioning

In this paper, we describe the positioning technique for camera based smartphone in an indoor environment. The camera of smartphone detects multiple light-emitting diode (LED) lights whose are located on the rooftop. LED light sends its coordinates (x, y) information to the camera whose are fixed and parallel to the world coordinate. We calculate the distance from each LED to the camera using photogrammetry. Later, a lighting server calculates the accurate position information and using extended Kalman filter algorithm it corrects position estimation error of the smartphone.

Adaptive spatial-temporal resolution optical vehicular communication system using image sensor

In this article, we introduce an image sensor–based optical vehicular communication system for performing vehicular condition resolution adaptively in the spatial domain and the temporal domain. To validate the proposed system, a dual camera–based approach is presented here, where a vision camera is used to detect multiple vehicles of interest (i.e. spatial condition), a communication link is set up, and then, a high-speed camera adapts its resolution to ensure fast processing and high-rate data communication (i.e. temporal condition). We suggest an adaptive algorithm that supports the detection of and communication multiple vehicles simultaneously in spatial-temporal condition. Moreover, we propose a combination of scale-invariant feature transform and iterative closest point for detection and classification of multiple vehicles. To prove the feasibility of our proposed scheme, we present simulation results.

Interference mitigation technique for Time-of-Flight (ToF) camera

Time-of-Flight (ToF) camera has become an attractive source of applications in location-based services, autonomous navigation, object localization for robotic manipulation, ego-motion estimation, etc. Besides, these services demand centimeter level accuracy to provide the required services. Though ToF cameras can provide high accuracy in location-based services with high frame rates (approx. 30 fps), they are facing some problems like multipath interference (MPI), internal scattering, motion blur, etc. The interferences inherent to ToF camera can influence the measurements by several centimeters. In this paper, we formulate a model to mitigate MPI and light scattering problems through a combination of scale-invariant feature transform (SIFT) and iterative closest point (ICP). We use SIFT algorithm for image features extraction and ICP for error correction during estimation. Finally, we present simulation results to prove the scalability and flexibility of our proposed algorithm for both MPI and light scattering mitigation.

Convolutional neural networkscheme–based optical camera communication system for intelligent Internet of vehicles:

The evolution of the Internet of vehicles and growing use of mobile devices has created a demand for new wireless communication technologies. Optical camera communication, which uses light-emitting diodes as transmitters and cameras as receivers, has emerged as a promising alternative. Since light-emitting diodes and cameras are already exploring in traffic lights, vehicles, and public lightings, optical camera communication has the potential to intelligently handle transport systems. Although other technologies have been proposed or developed in both academia and industry, they are not yet mature enough to uphold the huge requirements of the Internet of vehicles. This study introduces a new intelligent Internet of vehicles system based on optical camera communication combined with convolutional neural networks. Optical camera communication is a promising candidate for maintaining interference-free and more robust communication, for supporting the Internet of vehicles. Convolutional neural network is introduced for precise detection and recognition of light-emitting diode patterns at long distances and in bad weather conditions. We propose an algorithm to detect the interested light-emitting diode signals (i.e. regions-of-interest), measure the distance using a stereo-vision technique to find out the desired targets, and simulate our proposed scheme using a MATLAB Toolbox. Thus, our system will provide great advantages for next-generation transportation systems.