Search Results (9)

Underwater wireless communications face significant challenges due to high attenuation, turbulence, and water turbidity. Traditional methods like acoustic and radio frequency (RF) communication suffer from low data rates (<100 kbps), high latency (>1 s), and limited transmission distances (<10 km).Visible Light Communication (VLC) emerges as a promising alternative, offering high-speed data transmission (up to 5 Gbps), low latency (<1 ms), and immunity to electromagnetic interference. This paper provides an in-depth review of underwater VLC, covering fundamental principles, environmental factors (scattering, absorption), and dynamic water properties. We analyze modulation techniques, including adaptive and hybrid schemes (QAM-OFDM achieving 4.92 Gbps over 1.5 m), and demonstrate their superiority over conventional methods. Practical applications—underwater exploration, autonomous vehicle control, and environmental monitoring—are discussed alongside security challenges. Key findings highlight UVLC’s ability to overcome traditional limitations, with experimental results showing 500 Mbps over 150 m using PAM4 modulation. Future research directions include integrating quantum communication and Reconfigurable Intelligent Surfaces (RISs) to further enhance performance, with simulations projecting 40% improved spectral efficiency in turbulent conditions. Full article

Approximately 75% of the Earth’s surface is covered by water, and 78% of the global animal kingdom resides in marine environments. Furthermore, algae and microalgae in marine ecosystems contribute up to 75% of the planet’s oxygen supply, underscoring the critical need for conservation efforts. This review systematically evaluates the impact of underwater communication systems on aquatic ecosystems, focusing on both wired and wireless technologies. It highlights the applications of these systems in Internet of Underwater Things (IoUT), Underwater Wireless Sensor Networks (UWSNs), remote sensing, bathymetry, and tsunami warning systems, as well as their role in reducing the ecological footprint of human activities in aquatic environments. The main contributions of this work include: a benchmark of various underwater communication systems, comparing their advantages and limitations; an in-depth analysis of the adverse effects of anthropogenic emissions associated with communication systems on marine life; and a discussion of the potential for underwater communication technologies, such as remote sensing and passive monitoring, to aid in the preservation of biodiversity and the protection of fragile ecosystems. Full article

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. Full article

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. Full article

Underwater visible light communication (UVLC) based on LEDs has become a competitive candidate, which is able to provide high data rates, low latency and low cost for next-generation wireless communication technologies. However, it is still challenging to achieve high-speed communication because of bottleneck problems such as bandwidth limitation and linear and nonlinear distortions. Traditional Deep-learning Neural Network (DNN)-based waveform-to-symbol converter is verified to be an effective method to alleviate them, but impractical due to high complexity. To achieve a better tradeoff between communication performance and computation complexity, a cascaded receiver consisting of a DNN-based waveform-to-symbol converter and modified Neural Network (NN)-based decision-directed least mean square (DD-LMS) is then innovatively proposed. With fewer taps and nodes than the traditional converter, the front-stage converter could mitigate the majority of Inter-Symbol Interference (ISI) and signal nonlinear distortions. Then modified NN-based DD-LMS is cascaded to improve communication performance by reducing phase offset, making received constellation points more concentrated and closer to standard constellation points. Compared with the traditional converter, the cascaded receiver could achieve 89.6% of signal Vpp dynamic range with 12.4% of complexity in the 64APSK UVLC system. Moreover, the ratio of signal Vpp dynamic range and total trainable parameters is 1.24 × 10⁻¹ mV, while that of the traditional converter is 1.95 × 10⁻² mV. The cascaded receiver used in 64APSK UVLC systems is experimentally verified to achieve enhanced performance, thus as a promising scheme for future high-speed underwater VLC. Full article

Post-equalization using neural network (NN) is a promising technique that models and offsets the nonlinear distortion in visible light communication (VLC) channels, which is recognized as an essential component in the incoming 6G era. NN post-equalizer is good at modeling complex channel effects without previously knowing the law of physics during the transmission. However, the trained NN might be weak in generalization, and thus consumes considerable computation in retraining new models for different channel conditions. In this paper, we studied transfer learning strategy, growing DNN models from a well-trained ‘stem model’ instead of exhaustively training multiple models from randomly initialized states. It extracts the main feature of the channel first whose signal power balances the signal-to-noise ratio and the nonlinearity, and later focuses on the detailed difference in other channel conditions. Compared with the exhaustive training strategy, stem-originated DNN models achieve 64% of the working range with five times the training efficiency at most or more than 95% of the working range with 150% higher efficiency. This finding is beneficial to improving the feasibility of DNN application in real-world UVLC systems. Full article

Nowadays, underwater visible light communication (UVLC) has become one of the key technologies for high-speed underwater wireless communication. Because of the limited modulation bandwidth and nonlinearity of the optoelectronic devices in the UVLC system, the combination of inter-symbol interference and nonlinear impairment will inevitably degrade the transmission performance. Advanced digital signal processing methods including equalization and decoding are required. In the past few years, Support vector machine (SVM) has been widely investigated in quadrature amplitude modulation (QAM) for soft decision in the decoding process. However, previous works only consider 2-dimensional (2-D) separate symbol, ignoring the correlation between consecutive symbols. In this paper, we propose to use SVM for soft decision with a 4-dimensional (4-D) constellation by concatenating two consecutive symbols. To deal with the increasing computational complexity in the SVM training phase, bit-based binary SVM multi-class strategy and an edge-detection-based data pre-processing method are employed. In this paper, we demonstrate a carrierless amplitude and phase (CAP) 16-QAM UVLC system. Experimental results indicate that the performance is greatly improved when using consecutive-symbol-expanded 4-D constellation with SVM for soft decision. Full article

Recently, underwater visible light communication (UVLC) has become a potential wireless carrier candidate in the acrimonious mingled ocean straits. The combined strait of the North and Baltic ocean is a harsh and strongly turbid aqueous zone that contributes signal fading at a large scale. Due to this, we are proposing a UVLC system within the Baltic–North ocean mingled water under strong turbulence channel conditions. In this study, the Gamma–Gamma distribution is used to model UVLC link under an OOK modulation scheme. Subsequently, the reason for the unavailability of the latest North–Baltic oceanographic data within this bayou, we investigate the BER and outage probability performance of the proposed system within the mingled strait for the whole year during 1996s. Throughout, this work, the performance is obtained individually in both of the oceans and then compared with the heterogeneous state. It is noteworthy that the analytical work has been considered of the following distinct physio-chemical properties and the data provided for each ocean. Additionally, the simulation results are verified the analytical work of the proposed system model. Full article

In this paper, low-density parity-check (LDPC)-coded carrierless amplitude and phase (CAP) modulation with spatial diversity is proposed to mitigate turbulence-induced fading in an underwater visible-light communication (UVLC) channel. Generalized-gamma (GG) distribution was used to model the fading, as this model is valid for weak- and strong-turbulence regimes. On the basis of the characteristic function (CHF) of GG random variables, we derived an approximated bit-error rate (BER) for the CAP modulation scheme with spatial diversity and equal-gain combining (EGC). Furthermore, we simulated the performance of the CAP system with diversity and LDPC for various turbulence conditions and validated the analysis. Obtained results showed that the combination of LDPC and spatial diversity is effective in mitigating turbulence-induced fading, especially when turbulence strength is strong. Full article