Underwater Visible Light Communication Research Articles

Performance analysis of rectangular quadrature amplitude modulation for multiple-input multiple-output dual-hop cooperative underwater visible light communication system

Performance analysis of rectangular quadrature amplitude modulation for multiple-input multiple-output dual-hop cooperative underwater visible light communication system

Optimization of underwater visible light communication transmission using multilevel regression modelling

This paper proposes the 32-Channel Dense wavelength Division Multiplexing (DWDM) system for Underwater Visible Light Communication (UVLC). The proposed DWDM-UVLC system performs the transmission of visible light data under different underwater ocean environmental conditions such as Pure sea, Clear ocean, and Coastal ocean water and ocean pollution such as oil spills, microplastics. The data transmission through visible light in underwater ocean environment is a challenging task due to attenuation in ocean water, which causes variations in water column parameters such as temperature, Ph, salinity, and chemical oil spill contents in water such as water with oil spills, and microplastics. The proposed dense wavelength Division Multiplexing (DWDM) system for Underwater Visible Light Communication (UVLC) is optimized using Bayesian optimized Multiple Regression Learning (BO-MRL) method. The BO-MRL based DWDM for UVLC mitigates the attenuation problems in data transmission, which is in the range of approximately 350m. The proposed DWDM-UVLC system is evaluated through the Performance metrics such as Q-factor, Minimal BER and proper spectral eye characteristics. The proposed BO-MRL based DWDM consists of non-return-to-zero (NRZ) modulation, which performs better in 320 Gbps, transmission in the range of 200m and 350m, and achieves the maximum Q-factor of 19.2364 with a minimal BER of 9.16489 e−083.

Modulation format recognition in a UVLC system based on an ultra-lightweight model with communication-informed knowledge distillation

Modulation format recognition (MFR) is a key technology for adaptive optical systems, but it faces significant challenges in underwater visible light communication (UVLC) due to the complex channel environment. Recent advances in deep learning have enabled remarkable achievements in image recognition, owing to the powerful feature extraction of neural networks (NN). However, the high computational complexity of NN limits their practicality in UVLC systems. This paper proposes a communication-informed knowledge distillation (CIKD) method that achieves high-precision and low-latency MFR with an ultra-lightweight student model. The student model consists of only one linear dense layer under a communication-informed auxiliary system and is trained under the guidance of a high-complexity and high-precision teacher model. The MFR task involves eight modulation formats: PAM4, QPSK, 8QAM-CIR, 8QAM-DIA, 16QAM, 16APSK, 32QAM, and 32APSK. Experimental results show that the student model based on CIKD can achieve comparable accuracy to the teacher model. After knowledge transfer, the prediction accuracy of the student model can be increased by up to 87%. Besides, it is worth noting that CIKD’s inference accuracy can reach up to 100%. Moreover, the parameters constituting the student model in CIKD correspond to merely 18% of the parameters found in the teacher model, which facilitates the hardware deployment and online data processing of MFR algorithms in UVLC systems.

Underwater Visible Light Communication for Scuba Divers Health Monitoring System

Diving has become a common way of performing research in the underwater living world. One of the major problems with diving is the health issues faced by the divers during diving and there comes the need for monitoring diver’s health. This paper mainly focuses on the health monitoring systems for divers by transferring the data using Li-Fi (Light Fidelity). This system senses different health specifications like heartbeat, body temperature and body position. The monitored health specifications are recorded as a database in a memory chip for further analysis. To reduce the power consumption, the system transfers the data to the nearby divers and ships only during the abnormal health issue. The uniqueness of this system lies in its combination of advanced technologies for diver safety, communication, and submarine surveillance. This is crucial for ensuring their safety, especially in challenging underwater environments. This is perhaps one of the most unique aspects. Li-Fi, which uses light to transmit data, is a breakthrough for underwater communication. This system provides real-time data on the diver's condition and an immediate way to request assistance in case of an emergency. By incorporating temperature and gyro monitoring, the system collects valuable data on diver conditions and movements. This data could be analyzed for research or used to improve safety protocols in the future.

AquaKey

Underwater Visible Light Communication (UVLC) is promising due to its relatively strong penetration capability in water and large frequency bandwidth. Visible Light Communication (VLC) is also considered a safer wireless communication paradigm as light signals can be constrained within the area of interest with obstacles such as walls, reducing the chance of potential attack. However, this intuitional security assumption is not true anymore in underwater environment. Recent research shows that the eavesdropping risk of UVLC is more severe than we thought, attributed to the divergence and scattering effects of light beams in water. In this paper, we harness the dynamic nature of underwater environments as a true random resource to extract symmetric keys for UVLC. Specifically, the proposed AquaKey system incorporates instantaneous bidirectional channel probing, computation of relative channel characteristics, and an environment-adaptive quantization algorithm. The above design addresses unique challenges caused by the dynamic underwater environment, including self-interference, high-frequency disturbance, and mismatch, ensuring the practicality and applicability of AquaKey. Additionally, AquaKey has negligible impact on communication and has no effect on the illumination function. Through extensive real-world experiments, we show that AquaKey can achieve reliable key extraction with cheap hardware, generating a 512-bit key in just 0.5-1 seconds.

Neural-network-based end-to-end learning for adaptive optimization of two-dimensional signal generation in UVLC systems.

Visible light communication (VLC) benefits from the underwater blue-green window and holds immense potential for underwater wireless communication. In order to address the limitations of various equipment and harsh channel conditions in the underwater visible light communication (UVLC) system, the researchers proposed to use the method of autoencoder (AE) to tap the potential of the system. However, traditional AE schemes involve replacing the transmitting and receiving components of a communication system with a large multilayer perceptron (MLP) network, and they have significant drawbacks due to their reliance on a single network structure. In this paper, a novel 2D adaptive optimization autoencoder (2D-AOAE) framework is proposed to realize adaptive modulation and demodulation of two-dimensional signals. By implementing this scheme, we experimentally achieved a transmission rate of 2.85 Gbps over a 1.2-meter underwater VLC link. Compared to the traditional 32QAM UVLC system, the 2D-AOAE scheme demonstrated a 15.4% data rate increase. Moreover, the 2D-AOAE scheme exhibited a remarkable 73% improvement when compared to the UVLC system utilizing the traditional AE scheme. This significant enhancement highlights the superior performance and capabilities of the 2D-AOAE scheme in terms of transmission rate.

0.5-bit/s/Hz fine-grained adaptive OFDM modulation for bandlimited underwater VLC.

In this paper, we propose and demonstrate a 0.5-bit/s/Hz fine-grained adaptive orthogonal frequency division multiplexing (OFDM) modulation scheme for bandlimited underwater visible light communication (UVLC) systems. Particularly, integer spectral efficiency is obtained by conventional OFDM with quadrature amplitude modulation (QAM) constellations, while fractional spectral efficiency is obtained by two newly proposed dual-frame OFDM designs. More specifically, OFDM with dual-frame binary phase-shift keying (DF-BPSK) is designed to achieve a spectral efficiency of 0.5 bit/s/Hz, while OFDM with dual-frame dual-mode index modulation (DF-DMIM) is designed to realize the spectral efficiencies of 0.5+n bits/s/Hz with n being a positive integer (i.e., n = 1, 2, …). The feasibility and superiority of the proposed 0.5-bit/s/Hz fine-grained adaptive OFDM modulation scheme in bandlimited UVLC systems are successfully verified by simulations and proof-of-concept experiments. Experimental results demonstrate that a significant achievable rate gain of 18.6 Mbps can be achieved by the proposed 0.5-bit/s/Hz fine-grained adaptive OFDM modulation in comparison to the traditional 1-bit/s/Hz granularity adaptive OFDM scheme, which corresponds to a rate improvement of 22.1%.

Transceiver performance enhanced green micro-LED based on pre-layer structure enable multifunctional applications in underwater visible light communication.

Transceiver performance enhanced green micro-LED based on pre-layer structure enable multifunctional applications in underwater visible light communication.

Channel estimation-based time-frequency neural network for post-equalization in underwater visible light communication

Channel estimation-based time-frequency neural network for post-equalization in underwater visible light communication

Performance analysis of convolutional codes in dynamic underwater visible light communication systems

Performance analysis of convolutional codes in dynamic underwater visible light communication systems

Hybrid Space Division Multiple Access and Quasi-Orthogonal Multiple Access for Multi-User Underwater Visible Light Communication

Hybrid Space Division Multiple Access and Quasi-Orthogonal Multiple Access for Multi-User Underwater Visible Light Communication

An Optimal Adaptive Constellation Design Utilizing an Autoencoder-Based Geometric Shaping Model Framework

Since visible-light communication (VLC) has become an increasingly promising candidate for 6G, the field of underwater visible-light communication (UVLC) has also garnered significant attention. However, the impairments introduced by practical systems and the time-varying underwater channels always limit the performance of underwater visible-light communication. In this paper, we propose and experimentally demonstrate an autoencoder-based geometric shaping model (AEGSM) framework to jointly optimize quadrature amplitude modulation (QAM) signals at the symbol-wise and bit-wise levels for underwater visible-light communication. Unlike traditional geometric shaping (GS) methods, which only give theoretically optimal shaping solutions, our framework can always obtain the globally optimal shaping scheme for a specific channel condition or different application scenarios. In our AEGSM framework, an autoencoder is used to find the optimal shaping scheme at the symbol-wise level and a revised pairwise optimization (RPO) algorithm is applied to achieve bit-wise optimization. In a real UVLC system, 2.05 Gbps transmission is achieved under the hard decision–forward error correction (HD-FEC) threshold of 3.8 × 10−3 by employing the autoencoder-based 8QAM (AE-8QAM) optimized by the AEGSM, which is 103 Mbps faster than the Norm-8QAM. The AE-8QAM also shows its resistance to nonlinearity and enables the UVLC system to operate within a larger dynamic range of driving voltages. The results substantiate the potential and practicality of the proposed AEGSM framework in the realm of underwater visible-light communication.

Adaptive Fuzzy Logic Deep-Learning Equalizer for Mitigating Linear and Nonlinear Distortions in Underwater Visible Light Communication Systems

Underwater visible light communication (UVLC) has recently come to light as a viable wireless carrier for signal transmission in risky, uncharted, and delicate aquatic environments like seas. Despite the potential of UVLC as a green, clean, and safe alternative to conventional communication methods, it is challenged by significant signal attenuation and turbulent channel conditions compared to long-distance terrestrial communication. To address linear and nonlinear impairments in UVLC systems, this paper presents an adaptive fuzzy logic deep-learning equalizer (AFL-DLE) for 64 Quadrature Amplitude Modulation-Component minimal Amplitude Phase shift (QAM-CAP)-modulated UVLC systems. The proposed AFL-DLE is dependent on complex-valued neural networks and constellation partitioning schemes and utilizes the Enhanced Chaotic Sparrow Search Optimization Algorithm (ECSSOA) to improve overall system performance. Experimental outcomes demonstrate that the suggested equalizer achieves significant reductions in bit error rate (55%), distortion rate (45%), computational complexity (48%), and computation cost (75%) while maintaining a high transmission rate (99%). This approach enables the development of high-speed UVLC systems capable of processing data online, thereby advancing state-of-the-art underwater communication.

SIMO-Underwater Visible Light Communication (UVLC) system

The advent of visible light communication (VLC) towards 5G and beyond (5GB) networks opened new doors to unveil the mysteries of unguided mediums such as ocean. The varying physicochemical properties of water introduces the underwater optical turbulence (UOT). The UOT of UVLC link is modelled as unified Gamma-Gamma (GG) distribution fading under moderate-to-strong turbulence channel conditions as well as the misalignment of transceivers following exponential fading are included and studied. This study also contains the effect of UOT which is characterized by multiple water layers within the Monte Carlo simulation framework. The end-to-end (E2E) performances of a Single-Input and Multi-Output (SIMO) underwater VLC (UVLC) system is in consideration of Intensity-Modulation/Direct-Detection (IM/DD) technique which is obtained to fulfill the current communication requirements in hostile aqueous channels. More specifically, the probability distribution function (PDF) and cumulative distribution function (CDF) are derived to obtain the E2E performance metrics of the SIMO-UVLC system in terms of Meijer-G function. Consequently, novel closed-form expressions for average bit-error-rate (ABER) and outage probability of the system are formulated. Finally, the numerical and simulation results are obtained based on the experimental data in mixed water layers of the oceanic environments, and analytically verified through the Monte Carlo simulation approach in harsh channel conditions.

Modulation format recognition in a UVLC system based on reservoir computing with coordinate transformation and folding algorithm.

Modulation format recognition (MFR) is one of the key technologies in adaptive optical systems and widely used in both commercial and civil applications. With the rapid development of deep learning, MFR algorithm based on neural networks (NN) has achieved impressive success. Due to the high complexity of underwater channels, to gain better performance of MFR tasks in underwater visible light communication (UVLC), the NN tend to be designed with a complex structure, which is costly in computation and hinders fast allocation and real-time processing. In this paper, we propose a lightweight and efficient method based on reservoir computing (RC), whose trainable parameters are only 0.3% of common NN-based methods. To improve the performance of RC in MFR tasks, we propose powerful feature extraction algorithms including coordinate transformation and folding algorithm. The proposed RC-based methods are implemented for six modulation formats, including OOK, 4QAM, 8QAM-DIA, 8QAM-CIR, 16APSK, and 16QAM. The experimental results show that our RC-based methods take only a few seconds for training process and under different pin voltages of LED, the accuracy for almost all exceeds 90%, and the highest is close to 100%. Analysis on how to design a well-performed RC to strike a balance between accuracy and time cost is also investigated, providing a useful guide for RC implementations in MFR.

Enhancing underwater VLC with spatial division transmission and pairwise coding.

In this paper, we propose and evaluate two spatial division transmission (SDT) schemes, including spatial division diversity (SDD) and spatial division multiplexing (SDM), for underwater visible light communication (UVLC) systems. Moreover, three pairwise coding (PWC) schemes, including two one-dimensional PWC (1D-PWC) schemes, i.e., subcarrier PWC (SC-PWC) and spatial channel PWC (SCH-PWC), and one two-dimensional PWC (2D-PWC) scheme are further applied for signal-to-noise ratio (SNR) imbalance mitigation in the UVLC systems using SDD and SDM with orthogonal frequency division multiplexing (OFDM) modulation. The feasibility and superiority of applying SDD and SDM with various PWC schemes in a practical bandlimited two-channel OFDM-based UVLC system have been verified through both numerical simulations and hardware experiments. The obtained results show that the performance of SDD and SDM schemes are largely determined by both the overall SNR imbalance and the system spectral efficiency. Moreover, the experimental results demonstrate the robustness of SDM with 2D-PWC against bubble turbulence. Specifically, SDM with 2D-PWC can obtain bit error rates (BERs) under the 7% forward error correction (FEC) coding limit of 3.8 × 10-3 with a probability higher than 96% for a signal bandwidth of 70 MHz and a spectral efficiency of 8 bits/s/Hz, achieving an overall data rate of 560 Mbits/s.

Precoder Design to Improve Performance of Multi-User OQAM DCO-FBMC Underwater Visible Light Communication

Precoder Design to Improve Performance of Multi-User OQAM DCO-FBMC Underwater Visible Light Communication

Physical prior inspired ensemble learning enables effective channel estimation of underwater visible light communication.

Deep neural networks have been applied to estimate the optical channel in communication systems. However, the underwater visible light channel is highly complex, making it challenging for a single network to accurately capture all its features. This paper presents a novel approach to underwater visible light channel estimation using a physical prior inspired network based on ensemble learning. A three-subnetwork architecture was developed to estimate the linear distortion from inter-symbol interference (ISI), quadratic distortion from signal-to-signal beat interference (SSBI), and higher-order distortion from the optoelectronic device. The superiority of the Ensemble estimator is demonstrated from both the time and frequency domains. In terms of mean square error performance, the Ensemble estimator outperforms the LMS estimator by 6.8 dB and the single network estimators by 15.4 dB. In terms of spectrum mismatch, the Ensemble estimator has the lowest average channel response error, which is 0.32 dB, compared to 0.81 dB for LMS estimator, 0.97 dB for the Linear estimator, and 0.76 dB for the ReLU estimator. Additionally, the Ensemble estimator was able to learn the V-shaped Vpp-BER curves of the channel, a task not achievable by single network estimators. Therefore, the proposed Ensemble estimator is a valuable tool for underwater visible light channel estimation, with potential applications in post-equalization, pre-equalization, and end-to-end communication.

On Performance Analysis of Cooperative Horizontal and Vertical Underwater VLC Systems with Best Relay Selection

In this paper, we consider cooperative horizontal and vertical underwater visible light communication (UWVLC) systems employing best relay selection. In the vertical UWVLC system, the source is placed at the sea surface and the destination is placed at a depth of 60 m. The link between the source and the destination is modeled as concatenated layers considering inhomogeneous environmental conditions. The underwater parameters change with depth, causing a variable refractive index, which leads to non-uniform optical turbulence. The horizontal communication link is analyzed for two different levels of turbulence at 10 m and 50 m depths. Turbulence is modeled using a log-normal distribution, whose statistical parameters depend on the temperature and salinity at different depths. We have also taken into account the path losses caused by absorption and scattering, and carried out a comprehensive performance comparison between the horizontal and the vertical UWVLC systems. Insights show that compared to horizontal links, vertical links need an extra relay in order to achieve the same level of matching performance. Moreover, it is shown that the horizontal system’s outage performance improves with depth.

Effect of Sea Waves on Vertical Underwater Visible Light Communication Links

Underwater visible light communication (VLC) has been proposed to deal with emerging high bandwidth underwater applications. Initial research works on underwater VLC are based on the assumption that both transmitter and receiver are submerged, creating a horizontal link. In most of the vertical communication links, one of the transceiver nodes takes the form of a buoy and requires taking into the effect of the sea surface, which is inherently unsteady due to wind and waves. In this article, we consider a vertical underwater VLC link where the transmitter is in the form of a buoy at the sea surface, and the receiver is a submerged node at a certain depth. We assume sinusoidal waves and consider the fact that the buoy will fluctuate and oscillate, during drifting up and down, around its vertical axis. This effectively results in a 3-D displacement at the suspended transmitter. Building upon these assumptions of practical relevance, we propose an aggregate channel model, which includes a random path loss due to periodic changes of the transmission distance and a fading term induced by pointing errors with periodic changes of relative movement. Based on the proposed statistical model, we derive closed-form expressions for the exact and asymptotic bit error ratio and investigate the achievable diversity orders. We further present numerical results to confirm the analytical findings.