The evolving explosion in high data rate services and applications will soon require the use of untapped, abundant unregulated spectrum of the visible light for communications to adequately meet the demands of the fifth-generation (5G) mobile technologies. Radio-frequency (RF) networks are proving to be too scarce to cover the escalation in data rate services. Visible light communication (VLC) has emerged as a great potential solution, either in replacement of, or a complement to, existing RF networks, to support the projected traffic demands. Despite the prolific advantages of VLC networks, VLC faces many challenges that must be resolved in the near future to achieve full standardization and to be integrated to future wireless systems. Here, we review the emerging research in the field of VLC networks and lay out the challenges, technological solutions, and future work predictions. Specifically, we first review the VLC channel capacity derivation and discuss the performance metrics and the associated variables. The optimization of VLC networks are also discussed, including resources and power allocation techniques, user-to-access point (AP) association and APs-to-clustered-users-association, APs coordination techniques, non-orthogonal multiple access (NOMA) VLC networks, simultaneous energy harvesting and information transmission using the visible light, and the security issues in VLC networks. Finally, we propose several open research problems to optimize the various VLC networks by maximizing either the sum rate, fairness, energy efficiency, secrecy rate, or harvested energy.
Some review articles focused on specific aspects of VLC such as VLC channel modeling methods @cite_47 , noise optical sources and noise mitigation mechanisms @cite_57 , VLC-based positioning techniques for indoor and outdoor applications @cite_18 , and the pertinent issues associated with the outdoor usage of VLC in vehicular communication @cite_177 . They generally identified emerging challenges and proposed future research directions.
@cite_57 @cite_177 @cite_47 @cite_18
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In the context of an increasing interest toward reducing the number of traffic accidents and of associated victims, communication-based vehicle safety applications have emerged as one of the best solutions to enhance road safety. In this area, visible light communications (VLC) have a great potential for applications due to their relatively simple design for basic functioning, efficiency, and large geographical distribution. This paper addresses the issues related to the VLC usage in vehicular communication applications, being the first extensive survey dedicated to this topic. Although VLC has been the focus of an intensive research during the last few years, the technology is still in its infancy and requires continuous efforts to overcome the current challenges, especially in outdoor applications, such as the automotive communications. This paper is aimed at providing an overview of several research directions that could transform VLC into a reliable component of the transportation infrastructure. The main challenges are identified and the status of the accomplishments in each direction is presented, helping one to understand what has been done, where the technology stands and what is still missing. The challenges for VLC usage in vehicle applications addressed by this survey are: 1) increasing the robustness to noise; 2) increasing the communication range; 3) enhancing mobility; 4) performing distance measurements and visible light positioning; 5) increasing data rate; 6) developing parallel VLC; and 7) developing heterogeneous dedicated short range communications and VLC networks. Addressing and solving these challenges lead to the perspective of fully demonstrating the high potential of VLC, and therefore, to enable the VLC usage in road safety applications. This paper also proposes several future research directions for the automotive VLC applications and offers a brief review on the associated standardization activities. As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems. Visible light communication VLC is a newly emerging technology, which integrates communications and lighting purposes, and has become a very active research topic in the areas of wireless communications. It is expected to become an important part of the next generation wireless communications because of its unique features in using unlicensed spectrum, support of high data rate, and its resistance to electromagnetic interferences. In this survey paper, we begin with a review on the basis of photometry, which is used to establish channel models of VLC systems. Then, we will continue to address various issues on the fundamental characteristic features of VLC systems, the impact of indoor environments on system performance, and the analysis and discussions of five different types of typical VLC channel models and other related parameters in VLC channel models. Finally, in terms of the future works, we will show the possible follow-up research focuses and directions as an effort to identify some new research topics on VLCs. Copyright © 2016 John Wiley & Sons, Ltd. This paper presents a deep-learning (DL) based approach to the design of multi-colored visible light communication (VLC) systems where RGB light-emitting diode (LED) lamps accomplish multi-dimensional color modulation under color and illuminance requirements. It is aimed to identify a pair of multi-color modulation transmitter and receiver leading to efficient symbol recovery performance. To this end, an autoencoder (AE), an unsupervised deep learning technique, is adopted to train the end-to-end symbol recovery process that includes the VLC transceiver pair and a channel layer characterizing the optical channel along with additional LED intensity control features. As a result, the VLC transmitter and receiver are jointly designed and optimized. Intensive numerical results demonstrate that the learned VLC system outperforms existing techniques in terms of the average symbol error probability. This framework sheds light on the viability of DL techniques in the optical communication system design. Visible light communication (VLC) systems have typically operated at data rates below 20 Gbps and operation at this data rate was shown to be feasible by using laser diodes (LDs), beam steering, imaging receivers and delay adaptation techniques. However, an increase in the computational cost is incurred. In this paper, we introduce fast computer generated holograms (FCGHs) to speed up the adaptation process. The new, fast and efficient fully adaptive VLC system can improve the receiver signal to noise ratio (SNR) and reduce the required time to estimate the position of the VLC receiver. In addition, an imaging receiver and a delay adaptation technique are used to reduce the effect of inter symbol interference (ISI) and multipath dispersion. Significant enhancements in the SNR, with VLC channel bandwidths of more than 36 GHz are obtained resulting in a compact impulse response and a VLC system that is able to achieve higher data rates (25 Gbps) with full mobility in the considered indoor environment. This paper develops a deep learning framework for the design of on-off keying (OOK) based binary signaling transceiver in dimmable visible light communication (VLC) systems. The dimming support for the OOK optical signal is achieved by adjusting the number of ones in a binary codeword, which boils down to a combinatorial design problem for the codebook of a constant weight code (CWC) over signal-dependent noise channels. To tackle this challenge, we employ an autoencoder (AE) approach to learn a neural network of the encoder-decoder pair that reconstructs the output identical to an input. In addition, optical channel layers and binarization techniques are introduced to reflect the physical and discrete nature of the OOK-based VLC systems. The VLC transceiver is designed and optimized via the end-to-end training procedure for the AE. Numerical results verify that the proposed transceiver performs better than baseline CWC schemes. In order to counteract the explosive escalation of wireless tele-traffic, the communication spectrum has been gradually expanded from the conventional radio frequency (RF) band to the optical wireless (OW) domain. By integrating the classic RF band relying on diverse radio techniques and optical bands, the next-generation heterogeneous networks (HetNets) are expected to offer a potential solution for supporting the ever-increasing wireless tele-traffic. Owing to its abundant unlicensed spectral resources, visible light communications (VLC) combined with advanced illumination constitute a competent candidate for complementing the existing RF networks. Although the advantages of VLC are multi-fold, some challenges arise when incorporating VLC into the classic RF HetNet environments, which may require new system architectures. The user-centric (UC) design principle for VLC environments constitutes a novel and competitive design paradigm for the super dense multi-tier cell combinations of HetNets. The UC concept may be expected to become one of the disruptive techniques to be used in the forthcoming fifth-generation era. This paper provides a comprehensive survey of visible-light-aided OW systems with special emphasis on the design and optimization of VLC networks, where the radically new UC design philosophy is reviewed. Finally, design guidelines are provided for VLC systems. Detailing a systems approach, Optical Wireless Communications: System and Channel Modelling with MATLAB, is a self-contained volume that concisely and comprehensively covers the theory and technology of optical wireless communications systems (OWC) in a way that is suitable for undergraduate and graduate-level students, as well as researchers and professional engineers. Incorporating MATLAB throughout, the authors highlight past and current research activities to illustrate optical sources, transmitters, detectors, receivers, and other devices used in optical wireless communications. They also discuss both indoor and outdoor environments, discussing how different factorsincluding various channel modelsaffect system performance and mitigation techniques. In addition, this book broadly covers crucial aspects of OWC systems: Fundamental principles of OWC Devices and systems Modulation techniques and schemes (including polarization shift keying) Channel models and system performance analysis Emerging visible light communications Terrestrial free space optics communication Use of infrared in indoor OWC One entire chapter explores the emerging field of visible light communications, and others describe techniques for using theoretical analysis and simulation to mitigate channel impact on system performance. Additional topics include wavelet denoising, artificial neural networks, and spatial diversity. Content also covers different challenges encountered in OWC, as well as outlining possible solutions and current research trends. A major attraction of the book is the presentation of MATLAB simulations and codes, which enable readers to execute extensive simulations and better understand OWC in general. Wireless vehicle-to-vehicle (V2V) and vehicle-toinfrastructure (V2I) communication holds great promise for significantly reducing the human and financial costs of vehicle collisions. A common characteristic of this communication is the broadcast of a device's core state information at regular intervals (e.g., vehicle speed and location or traffic signal state and timing). Unless controlled, the aggregate of these broadcasts will congest the channel under dense traffic scenarios, reducing the effectiveness of collision avoidance applications that use transmitted information. Active congestion control using distributed techniques is a topic of great interest for establishing the scalability of this technology. This paper defines a new adaptive congestion control algorithm that can be applied to the message rate of devices in this vehicular environment. While other published approaches rely on binary control, the LInear MEssage Rate Integrated Control (LIMERIC) algorithm takes advantage of full-precision control inputs that are available on the wireless channel. The result is provable convergence to fair and efficient channel utilization in the deterministic environment, under simple criteria for setting adaptive parameters. This “perfect” convergence avoids the limit cycle behavior that is inherent to binary control. We also discuss several practical aspects associated with implementing LIMERIC, including guidelines for the choice of system parameters to obtain desired utilization outcomes, a gain saturation technique that maintains robust convergence under all conditions, convergence with asynchronous updates, and using channel load to determine the aggregate message rate that is observable at a receiver. This paper also extends the convergence analysis for two important cases, i.e., measurement noise in the input signal and delay in the update process. This paper illustrates key analytical results using MATLAB numerical results and employs standard NS-2 simulations to demonstrate the performance of LIMERIC in several high-density scenarios. Over the past decade, visible light communication (VLC) systems have typically operated between 50 Mbps and 3.4 Gbps. In this paper, we propose and evaluate mobile VLC systems that operate at 10 Gbps. The enhancements in channel bandwidth and data rate are achieved by the introduction of laser diodes (LDs), angle diversity receivers (ADR), imaging receivers, relay nodes, and delay adaptation techniques. We propose three mobile VLC systems: an ADR relay assisted LD-VLC, an imaging relay assisted LD-VLC (IMGR-LD), and select-the-best imaging relay assisted LD-VLC. The ADR and imaging receiver are proposed for the VLC system to mitigate the intersymbol interference, maximize the signal-to-noise ratio (SNR), and reduce the impact of multipath dispersion due to mobility. The combination of IMGR-LD with a delay adaptation technique adds a degree of freedom to the link design, which results in a VLC system that has the ability to provide high data rates under mobility. The proposed IMGR-LD system achieves significant improvements in the SNR over other systems in the worst case scenario in the considered real indoor environment. Recently, millimeter-wave (mmWave) bands have been postulated as a means to accommodate the foreseen extreme bandwidth demands in vehicular communications, which result from the dissemination of sensory data to nearby vehicles for enhanced environmental awareness and improved safety level. However, the literature is particularly scarce in regards to principled resource allocation schemes that deal with the challenging radio conditions posed by the high mobility of vehicular scenarios. In this paper, we propose a novel framework that blends together matching theory and swarm intelligence to dynamically and efficiently pair vehicles and optimize both transmission and reception beamwidths. This is done by jointly considering channel state information and queue state information when establishing vehicle-to-vehicle (V2V) links. To validate the proposed framework, simulation results are presented and discussed, where the throughput performance as well as the latency reliability tradeoffs of the proposed approach are assessed and compared with several baseline approaches recently proposed in the literature. The results obtained in this paper show performance gains of 25 in reliability and delay for ultra-dense vehicular scenarios with 50 more active V2V links than the baselines. These results shed light on the operational limits and practical feasibility of mmWave bands, as a viable radio access solution for future high-rate V2V communications. Due to severe inter-cell interference (ICI), the signal-to- interference-and-noise ratio (SINR) suffers from very significant fluctuation in indoor multi-cell visible light communication (VLC) systems, which greatly limits the overall system performance. In this paper, we propose and evaluate a generalized angle diversity receiver (ADR) structure to reduce SINR fluctuation in indoor multi-cell VLC systems. The generalized ADR consists of one top detector and multiple inclined side detectors. In an indoor multi-cell VLC system using the generalized ADR, the inclination angle of the side detectors is optimized in order to minimize the SINR fluctuation over the receiving plane, where the impact of receiver random rotation is considered. An optimized ADR with different numbers of detectors is analyzed with different LED layouts and diversity combining techniques in a typical indoor environment. Analytical results show that the SINR fluctuation is gradually reduced when more detectors are equipped in the optimized ADR. In an indoor two-cell VLC system, much more significant SINR fluctuation reduction is achieved by using select-best combining (SBC). However, nearly the same SINR fluctuations are obtained in an indoor four-cell VLC system when using SBC and maximal-ratio combining (MRC). By applying the optimized ADR, up to 15.9 and 32.4-dB SINR fluctuation reductions can be achieved in comparison to a conventional single-element receiver (SER) in indoor two-cell and four-cell VLC systems, respectively. Vehicle Safety Communications (VSC) is advancing rapidly towards product development and field testing. While a number of possible solutions have been proposed, the question remains open as how such a system will address the issue of scalability in its actual deployment. This paper presents a design methodology for congestion control in VSC as well as the description and evaluation of a resulting rate adaption oriented protocol named PULSAR. We start with a list of design principles reflecting the state of the art that define why and how vehicles should behave while responding to channel congestion in order to ensure fairness and support the needs of safety applications. From these principles, we derive protocol building blocks required to fulfill the defined objectives. Then, the actual protocol is described and assessed in detail, including a discussion on the intricate features of channel load assessment, rate adaptation and information sharing. A comparison with other state-of-the-art protocols shows that “details matter” with respect to the temporal and spatial dimensions of the protocol outcome. In this letter, a new dimming control system with polar codes is proposed for visible light communication (VLC). The polar codes are concatenated with run-length limited codes and compensation symbols that can be used in VLC dimming control; moreover, puncturing is used to shorten the code length and improve coding efficiency. To compare the proposed system with the referenced systems, non-systematic and systematic polar codes are also considered. The simulation results show that our proposed system provides better performance than referenced systems, which use low-density parity-check codes or Reed–Solomon codes for dimming control. There has been a paradigm shifting trend towards feature-less methods due to their elegant formulation, accuracy and ever increasing computational power. In this work, we present a direct edge alignment approach for 6-DOF tracking. We argue that photo-consistency based methods are plagued by a much smaller convergence basin and are extremely sensitive to noise, changing illumination and fast motion. We propose to use the Distance Transform in the energy formulation which can significantly extend the influence of the edges for tracking. We address the problem of non-differentiability of our cost function and of the previous methods by use of a sub-gradient method. Through extensive experiments we show that the proposed method gives comparable performance to the previous method under nominal conditions and is able to run at 30 Hz in single threaded mode. In addition, under large motion we demonstrate our method outperforms previous methods using the same runtime configuration for our method. This paper presents an indoor relocalization system using a dual-stream convolutional neural network (CNN) with both color images and depth images as the network inputs. Aiming at the pose regression problem, a deep neural network architecture for RGB-D images is introduced, a training method by stages for the dual-stream CNN is presented, different depth image encoding methods are discussed, and a novel encoding method is proposed. By introducing the range information into the network through a dual-stream architecture, we not only improved the relocalization accuracy by about 20 compared with the state-of-the-art deep learning method for pose regression, but also greatly enhanced the system robustness in challenging scenes such as large-scale, dynamic, fast movement, and night-time environments. To the best of our knowledge, this is the first work to solve the indoor relocalization problems based on deep CNNs with RGB-D camera. The method is first evaluated on the Microsoft 7-Scenes data set to show its advantage in accuracy compared with other CNNs. Large-scale indoor relocalization is further presented using our method. The experimental results show that 0.3 m in position and 4° in orientation accuracy could be obtained. Finally, this method is evaluated on challenging indoor data sets collected from motion capture system. The results show that the relocalization performance is hardly affected by dynamic objects, motion blur, or night-time environments. Note to Practitioners —This paper was motivated by the limitations of the existing indoor relocalization technology that is significant for mobile robot navigation. Using this technology, robots can infer where they are in a previously visited place. Previous visual localization methods can hardly be put into wide application for the reason that they have strict requirements for the environments. When faced with challenging scenes such as large-scale environments, dynamic objects, motion blur caused by fast movement, night-time environments, or other appearance changed scenes, most existing methods tend to fail. This paper introduces deep learning into the indoor relocalization problem and uses dual-stream CNN (depth stream and color stream) to realize 6-DOF pose regression in an end-to-end manner. The localization error is about 0.3 m and 4° in a large-scale indoor environments. And what is more important, the proposed system does not lose efficiency in some challenging scenes. The proposed encoding method of depth images can also be adopted in other deep neural networks with RGB-D cameras as the sensor. Multiple-input multiple-output (MIMO) systems using multiple light emitting diode (LED) sources and photodiode (PD) detectors are attractive for visible light communication (VLC) as they offer a capacity gain proportional to the number of parallel single-input single-output (SISO) channels. MIMO VLC systems exploit the high signal-to-noise ratio (SNR) of a SISO channel offered due to typical illumination requirements to overcome the capacity constraints due to limited modulation bandwidth of LEDs. In this work, a modified singular value decomposition VLC (SVD-VLC) MIMO system is proposed. This system maximizes the data rate while maintaining the target illumination and allowing the channel matrix to vary in order to support mobility in a practical indoor VLC deployment. The upper bound on capacity of the proposed SVD-VLC MIMO system is calculated assuming an imaging receiver. The relationship between the proposed system performance and system parameters total power constraint, lens aperture and random receiver locations are described. Indoor Positioning based on WiFi has received extensive focus from research communities, owing its promises of ubiquitous positioning indoors for a variety of applications. The majority of the existing research on WiFi positioning centers around the improvement of positioning accuracy. However, to this end there is missing a unanimous evaluation methodology appropriately reflecting criteria relevant in real-world use. Assessing and advancing the state-of-the-art is often hindered by incomparable evaluation settings, and in many cases a missing rigor in describing evaluation methodology, metrics, and data collection, which is often decoupled from realistic use scenarios and their diversity. This leads to major challenges—and often disappointments—when implementing positioning methods in the hope of the promised accuracies. We believe that this holds especially in large real world environments, as only few extensive experimental evaluations have been reported in such environments. This paper presents a comparative evaluation of several indoor positioning techniques set at a large university hospital spanning 160, 000m2—an environment where several location- and context-aware logistic applications are in daily use. The positioning methods utilize measurements of signal strengths using existing WiFi infrastructure, which eases deployment and maintenance. We identify meaningful key metrics which describe different aspects of the methods' performance. Using these metrics, we furthermore report on experiences with implementing and utilizing indoor positioning solutions in a highly diverse environment, in which building types and materials, as well as building use differ across the complex. Correspondingly, the evaluation data we use is gathered at different building complex parts, days, and daytimes, and both at static locations as well as traveling within the building complex. Our results illustrate and quantify the challenges and breakdowns in transferring performance results from a small controlled setting, such as a small office environment, to a large dynamic building complex. In this letter, we propose a new decoding algorithm based on a soft run-length limited (RLL) decoding in visible light communication (VLC) with on-off keying modulation and Reed-Solomon codes. Conventional RLL codes are used for dimming adjustments in VLC; however, in our receiver model, the proposed RLL decoder produces one or multiple candidates with greater probabilities to enhance the throughput in the VLC system. We also propose a selection method based on a cyclic redundancy check among multiple candidates. A significant advantage of our proposed method is that it leads to performance enhancement without any change in the transmitter in VLC systems. Simulation results show that the bit error rate of our proposed method is better than that of RLL hard decoding. Direct radio-based vehicle-to-vehicle communication can help prevent accidents by providing accurate and up-to-date local status and hazard information to the driver. In this paper, we assume that two types of messages are used for traffic safety-related communication: 1) Periodic messages (ldquobeaconsrdquo) that are sent by all vehicles to inform their neighbors about their current status (i.e., position) and 2) event-driven messages that are sent whenever a hazard has been detected. In IEEE 802.11 distributed-coordination-function-based vehicular networks, interferences and packet collisions can lead to the failure of the reception of safety-critical information, in particular when the beaconing load leads to an almost-saturated channel, as it could easily happen in many critical vehicular traffic conditions. In this paper, we demonstrate the importance of transmit power control to avoid saturated channel conditions and ensure the best use of the channel for safety-related purposes. We propose a distributed transmit power control method based on a strict fairness criterion, i.e., distributed fair power adjustment for vehicular environments (D-FPAV), to control the load of periodic messages on the channel. The benefits are twofold: 1) The bandwidth is made available for higher priority data like dissemination of warnings, and 2) beacons from different vehicles are treated with ldquoequal rights,rdquo and therefore, the best possible reception under the available bandwidth constraints is ensured. We formally prove the fairness of the proposed approach. Then, we make use of the ns-2 simulator that was significantly enhanced by realistic highway mobility patterns, improved radio propagation, receiver models, and the IEEE 802.11p specifications to show the beneficial impact of D-FPAV for safety-related communications. We finally put forward a method, i.e., emergency message dissemination for vehicular environments (EMDV), for fast and effective multihop information dissemination of event-driven messages and show that EMDV benefits of the beaconing load control provided by D-FPAV with respect to both probability of reception and latency.