Search Results (79)

Compact mobile optical wireless communication (OWC) terminals are constrained not only by link budget but also by mobile-side size, weight, power consumption, and cost (SWaP-C). This paper proposes and models a remodulation-based bidirectional OWC transceiver module that integrates a fluorescent concentrator (FC) receiver and a modulating retroreflector (MRR) transmitter. The FC receives the downlink by absorbing a wavelength-dependent fraction of an interrogation beam, Stokes-shifting the absorbed light, and guiding the emission to an edge photodetector. The transmitted fraction of the same interrogation beam reaches the MRR and is remodulated for low-power uplink transmission without a mobile-side optical source. The central design variable is therefore not the optical power alone, but the pair consisting of the interrogation wavelength and the downlink modulation depth. A fully absorbed wavelength with high modulation depth is used for downlink-only operation, a pass-through wavelength with zero modulation depth is used for uplink-only operation, and an absorption-shoulder wavelength with intermediate modulation depth is used for simultaneous downlink and uplink remodulation. A spectral photon-transfer model, a direct-detection communication model, a self-interference model, and a weighted rate-optimization framework are developed. Simulation results show that the optimized wavelength shifts from the FC absorption peak in downlink-dominant operation to the FC pass-through window in uplink-dominant operation, while the optimal downlink modulation depth decreases to preserve uplink carrier margin. The proposed architecture is particularly well-suited for drones, robots, vehicles, and distributed sensors requiring robust optical downlink reception and low-SWaP-C uplink signaling. Full article

Optical wireless communication (OWC) has emerged as a complementary technology to conventional radio frequency (RF)-based communication systems, particularly in scenarios requiring low electromagnetic interference, enhanced security, and efficient spectrum utilization. Within various OWC approaches, optical camera communication (OCC) has attracted increasing attention due to its ability to utilize commercially available image sensors as receivers. This paper presents a 2D multiple-input–multiple-output (MIMO) OCC system based on light-emitting diode (LED) arrays for reliable communication in mobile environments. The proposed system employs on–off keying (OOK) modulation, which supports both rolling shutter and global shutter cameras. To improve decoding reliability under mobility conditions, a deep learning-based decoding model is introduced to enhance LED state detection compared with conventional zero-crossing approaches. In addition, a sequence number-based synchronization is implemented to compensate for frame rate variation and packet missing in a real-time environment. Besides that, by applying YOLOv13 for light source detection and tracking, we can achieve 98% accuracy at 3 m/s velocity. Experimental results show reliable communication performance at transmission distances of up to 22 m under various mobility conditions. Furthermore, the proposed system is validated through real-time environmental data transmission using temperature and humidity sensors with 20 links. The results indicate that the proposed scheme provides stable and reliable OCC performance for mobility Internet of Things (IoT) applications. Full article

This work proposes a fiber-tethered UAV-enabled adaptive aerial passive optical network (AA-PON) framework for rapid extension of optical access and backhaul in hard-to-reach or temporarily disrupted environments. The proposed architecture supports two distinct operating modes: (i) an aerial base station (ABS) mode for wide-area service extension and (ii) a ground-to-air-to-ground (G2A2G) mode for targeted high-speed optical bridging to ground terminal units. Unlike conventional UAV relay approaches, the proposed framework is developed as a network-level optical access/backhaul architecture based on tether-assisted aerial nodes and reconfigurable optical topology formation. In the ABS mode, representative Bus, Ring, and Star topologies are analyzed to evaluate serviceability, outage, deployment latency, and scalability as the number of UAV nodes increases. In the G2A2G mode, a stochastic-geometry-based analysis is used to characterize blockage-limited optical serviceability and infrastructure-density trade-offs. To complement the analytical study, a 2 Gb/s proof-of-concept FSO link between two fiber-tethered UAVs is demonstrated as an initial feasibility validation of the end-to-end optical link. The results show that the proposed AA-PON provides a flexible aerial optical networking framework that combines reconfigurable topology support with localized high-capacity optical access extension. Full article

The increasing demand for higher data rates in optical communication systems, especially within data centers and backbone networks, calls for the development of advanced modulation formats that can significantly enhance system performance. In this work, we introduce a novel modulation format based on the Kramers–Kronig relations, designed to improve upon traditional techniques such as Pulse Amplitude Modulation (PAM) and Carrier-less Amplitude Phase (CAP) modulation. The novel modulation format was rigorously validated through experimental investigations using an optical wireless communication (OWC) link. The results demonstrate a notable improvement in bit error rate (BER) performance and receiver sensitivity when compared to the conventional PAM-4 modulation scheme and CAP-16 modulation schemes. Moreover, the proposed scheme effectively reduces the complexity of digital filtering required by CAP while lowering the demands on the Digital-to-Analog Converter (DAC), making it a more practical solution for high-speed optical communication. This advancement facilitates higher data transmission rates, proving the Kramers–Kronig relations modulation format as a promising alternative to existing methods. Its potential for enhancing the efficiency and capacity of optical communication systems is evident. Future research will focus on optimizing the modulation parameters and exploring their application in more complex scenarios, such as high-speed underwater visible light communication systems, where advanced modulation formats are crucial for overcoming bandwidth limitations. Full article

The susceptibility of a Line-of-Sight (LOS) link in Optical Wireless Communication (OWC) to blockage is a major challenge affecting its deployment for next generation networks. Another challenge is the random orientation of the receiving device which also affects the amount of received optical power when the incidence angle is high. Reflecting Intelligent Surfaces (RIS) is a promising technology for using non-LOS (NLOS) communication. This work aims to study the effect of these LOS link impairments on Wavelength Division Multiplexing (WDM)-based resource allocation in OWC with and without the use of RIS elements and the effect on resilience. In this work, we adopt the state-of-the-art Orientation-based Random Way-Point (ORWP) model for mobility and random orientation of the User Equipment (UE) and calculate blockage geometrically assuming human objects since OWC links are not independent in contrast to RF-based communication. We propose multi-connectivity with physical path disjointness using multiple Angle Diversity Receiver (ADR) designs to evaluate the system performance using both a Mixed Integer Linear Program (MILP) and a low-complexity algorithm. Full article

With the rapid evolution of wireless networks, the need to explore novel technologies to meet the demands of future systems, particularly 6G, has become a significant challenge. One promising solution is integrating radio frequency (RF) and optical wireless communication (OWC) technologies to leverage their unique strengths. This paper introduces a novel model for integrating RF and OWC technologies within the framework of emerging 6G. The main objective of this approach is the dynamic technology selection (TS) and modulation scheme selection (MSS), which play a pivotal role in optimizing network efficiency and adapting to diverse 6G requirements. The proposed cross-layer architecture integrates the application layer, network layer based on a software-defined network (SDN), and physical layer consisting of a hybrid cell and software-defined radio with optical functionality (SDR-O). This approach facilitates real-time decision-making based on environmental factors and application requirements. Full article

This study explores the application of JAYA optimization algorithms to significantly enhance the performance of indoor optical wireless communication (OWC) systems. By strategically optimizing photo-signal parameters, the system was able to improve signal distribution and reception within a confined space using circular and randomly positioned diffuse spots. The primary objective was to maximize signal-to-noise ratio (SNR) and minimize delay spread (DS), two critical factors that affect transmission quality in OWC systems. Given the challenges posed by background noise and multipath dispersion, an effective optimization strategy was essential to ensure robust signal integrity at the receiver end. Key achievements of JAYA optimization include significant performance gains, such as a 29% improvement in SNR, enhancing signal clarity and reception, and a 23.3% reduction in delay spread, ensuring stable and efficient transmission. System stability also improved, with the standard deviation of SNR improving by up to 5%, leading to a more consistent performance, while the standard deviation of delay spread improved by up to 9.9%, minimizing variations across receivers. Resilience against environmental challenges: Optimization proved effective even in the presence of ambient light noise and complex multipath dispersion effects, reinforcing its adaptability in real-world applications. The findings of this study confirm that JAYA optimization algorithms offer a powerful solution for overcoming noise and dispersion issues in indoor OWC systems, leading to more reliable and high-quality optical wireless communications. These results underscore the importance of algorithmic precision in enhancing system performance, paving the way for further advancements in indoor optical networking technologies. Full article

Optical Wireless Communication (OWC) technologies are emerging as promising complements to radio-frequency systems, offering high bandwidth, spatial confinement, and license-free operation. Within this domain, Visible Light Communication (VLC) and Optical Camera Communication (OCC) represent two distinct paradigms with divergent performance and security profiles. While VLC leverages LED-photodiode links for high-speed data transfer, OCC exploits ubiquitous image sensors to decode modulated light patterns, enabling flexible but lower-rate communication. Despite their potential, both remain vulnerable to various attacks, including eavesdropping, jamming, spoofing, and privacy breaches. This work applies—and extends—the Risk Matrix (RM) methodology to systematically evaluate the security of VLC and OCC across reconnaissance, denial, and exploitation phases. Unlike prior literature, which treats VLC and OCC separately and under incompatible threat definitions, we introduce a unified, domain-specific risk framework that maps empirical channel behavior and attack feasibility into a common set of impact and likelihood indices. A normalized risk rank (NRR) is proposed to enable a direct, quantitative comparison of heterogeneous attacks and technologies under a shared reference scale. By quantifying risks for representative threats—including war driving, Denial of Service (DoS) attacks, preshared key cracking, and Evil Twin attacks—our analysis shows that neither VLC nor OCC is intrinsically more secure; rather, their vulnerabilities are context-dependent, shaped by physical constraints, receiver architectures, and deployment environments. VLC tends to concentrate confidentiality-driven exposure due to optical leakage paths, whereas OCC is more sensitive to availability-related degradation under adversarial load. Overall, the main contribution of this work is the first unified, standards-aligned, and empirically grounded risk-assessment framework capable of comparing VLC and OCC on a common security scale. The findings highlight the need for technology-aware security strategies in future OWC deployments and demonstrate how an adapted RM methodology can identify priority areas for mitigation, design, and resource allocation. Full article

The Faster-than-Nyquist (FTN) technology is widely used in optical wireless communication (OWC) systems to improve data rates and spectrum efficiency. However, it introduces inter-symbol interference (ISI), which can affect communication reliability. To address this issue, we propose a pre-equalization algorithm based on a deep neural network (DNN). The performance analysis primarily focuses on the bit-error-rate (BER) under a Gamma-Gamma atmospheric turbulence channel with varying acceleration factors. Simulation results show that our scheme effectively reduces the degradation in BER caused by ISI. Additionally, we observe an inverse relationship between the BER performance and the atmospheric refractive index constants as well as transmission distance, while a direct proportionality exists with respect to the filter roll-off factor and laser wavelength. Furthermore, comparing with conventional minimum mean square error (MMSE) and zero-forcing (ZF) algorithms highlights the superior performance of our proposal. Full article

The growing number of connected devices has strained traditional radio frequency wireless networks, driving interest in alternative technologies such as optical wireless communications (OWC). Among OWC solutions, optical camera communication (OCC) stands out as a cost-effective option because it leverages existing devices equipped with cameras, such as smartphones and security systems, without requiring specialized hardware. This paper proposes a novel deep learning-based detection and classification model designed to optimize the receiver’s performance in an OCC system utilizing color-shift keying (CSK) modulation. The receiver was experimentally validated using an $8\times 8$ LED matrix transmitter and a CMOS camera receiver, achieving reliable communication over distances ranging from 30 cm to 3 m under varying ambient conditions. The system employed CSK modulation to encode data into eight distinct color-based symbols transmitted at fixed frequencies. Captured image sequences of these transmissions were processed through a YOLOv8-based detection and classification framework, which achieved $98.4$% accuracy in symbol recognition. This high precision minimizes transmission errors, validating the robustness of the approach in real-world environments. The results highlight OCC’s potential for low-cost applications, where high-speed data transfer and long-range are unnecessary, such as Internet of Things connectivity and vehicle-to-vehicle communication. Future work will explore adaptive modulation and coding schemes as well as the integration of more advanced deep learning architectures to improve data rates and system scalability. Full article

In the realm of optical wireless communication (OWC), augmented spectral efficiency discrete multitone (ASE-DMT) has been widely recognized as a promising modulation due to its outstanding spectral efficiency and high power efficiency. However, ASE-DMT exhibits an inherently high peak-to-average power ratio (PAPR), which exacerbates error propagation and leads to a substantial transmission performance degradation in the successive interference cancellation (SIC) receiver of ASE-DMT. Therefore, a novel low-PAPR ASE-DMT scheme (LP-ASE-DMT) is proposed in the paper. Given the intricate multi-depth signal superposition of ASE-DMT, a progressive multi-level constellation extension algorithm is developed to effectively suppress the PAPR of the transmitted signal, while simultaneously achieving much lower computational complexity compared to conventional constellation extension schemes. Furthermore, a dedicated receiver architecture is designed for LP-ASE-DMT, in which a low-complexity modulo operation is employed to eliminate the impact of constellation extension without incurring significant additional receiver complexity. The effectiveness of the proposed LP-ASE-DMT scheme is validated through simulation, revealing a substantial mitigation of PAPR compared to its counterparts. This improvement notably strengthens the system’s robustness to nonlinear impairments. Consequently, LP-ASE-DMT enjoys superior performance across multiple metrics, including bit error rate (BER), power efficiency, and spectral efficiency. Full article

The time series prediction of visibility in terms of various meteorological variables, such as relative humidity, temperature, atmospheric pressure, and wind speed, is presented in this paper using Single-Variable Regression Analysis (SVRA), Artificial Neural Network (ANN), and Hybrid Adaptive Neuro-fuzzy Inference System (ANFIS) techniques for several sub-tropical locations. The initial method used for the prediction of visibility in this study was the SVRA, and the results were enhanced using the ANN and ANFIS techniques. Throughout the study, neural networks with various algorithms and functions were trained with different atmospheric parameters to establish a relationship function between inputs and visibility for all locations. The trained neural models were tested and validated by comparing actual and predicted data to enhance visibility prediction accuracy. Results were compared to assess the efficiency of the proposed systems, measuring the root mean square error (RMSE), coefficient of determination (R²), and mean bias error (MBE) to validate the models. The standard statistical technique, particularly SVRA, revealed that the strongest functional relationship was between visibility and RH, followed by WS, T, and P, in that order. However, to improve accuracy, this study utilized back propagation and hybrid learning algorithms for visibility prediction. Error analysis from the ANN technique showed increased prediction accuracy when all the atmospheric variables were considered together. After testing various neural network models, it was found that the ANFIS model provided the most accurate predicted results, with improvements of 31.59%, 32.70%, 30.53%, 28.95%, 31.82%, and 22.34% over the ANN for Durban, Cape Town, Mthatha, Bloemfontein, Johannesburg, and Mahikeng, respectively. The neuro-fuzzy model demonstrated better accuracy and efficiency by yielding the finest results with the lowest RMSE and highest R² for all cities involved compared to the ANN model and standard statistical techniques. However, the statistical performance analysis between measured and estimated visibility indicated that the ANN produced satisfactory results. The results will find applications in Optical Wireless Communication (OWC), flight operations, and climate change analysis. Full article

Vehicular visible light communication (VVLC) with ultralow electromagnetic interference has great potential to propel the growth of the Internet of Vehicles (IoV). However, ensuring quick response times and minimal delays in VVLC is a significant challenge brought on by fast-moving vehicles. In response to this problem, we propose a heuristic optical flow scheduling algorithm. First, the optical flow scheduling problem of VVLC is built as a multi-objective optimization model considering the makespan, delay, schedulable ratio, and bandwidth utilization with non-conflict constraints. Second, an improved artificial plant community (APC) algorithm with enhanced global and local search capabilities is proposed to achieve low-delay communication for time-sensitive optical flows. Finally, a series of benchmark experiments are conducted to show that the proposed algorithm can efficiently schedule optical flows with minimal delay. The cost of this algorithm is very low, and it is suitable for deployment on edge computing platforms such as vehicles. Full article

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). Full article