Transfer Learning–Based Artificial Neural Networks Post-Equalizers for Underwater Visible Light Communication

In this letter, we jointly consider the problems of blind channel estimation (BCE), channel equalization and data detection in underwater visible light communication (UVLC) systems. Specifically, we propose to solve them with a model-driven deep learning (DL) approach. Inspired by the module-based signal processing methodology and communication theory, we devise a new blind receiver architecture called blind detection network (BDNet), which consists of three modules corresponding to BCE, channel equalization, and symbol demapping, respectively. Different from existing BCE schemes, the BDNet does not directly estimate the channel itself, but instead estimates the inverse channel regardless of the scalar ambiguity issue by learning the latent channel features from the received signal only. The UVLC channel effects can then be partially compensated by the zero-forcing equalization module of BDNet. Finally, the symbol demapping module recovers the transmitted symbols with the aid of the learned decision thresholds. Simulation results show the competitive bit error rate performance of BDNet in comparison to conventional pilot-aided schemes.

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.

Ongoing advances in the research and development of visible light communication (VLC) systems has opened up many opportunities for using the concept of light based communication in underwater medium. Water presents a favourable medium for communication of optical wavelengths, particularly in the blue-violet regions of the visible spectrum and parts of ultraviolet wavelength. Prior work in designing underwater VLC systems and exploration of underwater optical wireless channels have largely been limited to theoretical propositions. Experimentation work in this space have not studied the impact of water quality factors on communication, and there exists no clear database of underwater VLC channel studies. Prior work have also largely focused only on horizontal configurations, where the transmitter and receiver are at the same depth underwater. To bridge this gap between existing work and advancement of underwater VLC systems, this paper presents the development of an empirical model for underwater VLC across the vertical configuration and across different water quality factors such as turbidity, salinity and temperature.

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.

This paper demonstrates a multi-hop underwater visible light communication (VLC) system using light emitting diodes (LEDs). It is demonstrated that using a multi-hop technique, the overall underwater VLC distance can be increased significantly without adding significant complexity to the physical layer. The performance of the multi-hop system is compared to a single-hop technique utilizing three types of water in the laboratory environment, namely sea, canal, and tap water. The obtained results validate that a multi-hop technique can be a viable solution to overcome the problem of limited underwater communication range.

Underwater optical wireless communication (UWOC) is an interesting area need to be explored. In recent years, underwater visible light communication (UVLC) is expected to act as an alternative candidate in next-generation underwater wireless optical communications for the Internet of Underwater Things. The challenge is that the absorption, scattering, diffraction effect and turbulence of water medium, which can bring large attenuation and nonlinearity penalty. Therefore, it needs to apply lots of advanced modulation formats which including orthogonal frequency division multiplexing (OFDM), discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-S OFDM) and carrier-less amplitude and phase modulation (CAP) in UVLC system. What's more, advanced digital signal processing algorithm such as pre/post equalization, nonlinear compensation and other algorithms based on artificial intelligence are needed. In this paper, we introduce three advanced modulation formats including DFT-S OFDM, OFDM and CAP employing probabilistic shaping for high-speed LED based underwater visible light communication.

To satisfy the demands of high data rate underwater applications such as image and real-time video transmission, underwater visible light communication (UVLC) has emerged as an alternative to acoustic signaling. One of the major impairments in UVLC systems is turbulence-induced fading as a result of temporal variations in temperature and salinity. Furthermore, unlike the horizontal links modeled with fixed turbulence strength, vertical links experience varying turbulence strength based on the depth-dependent temperature and salinity profiles. In this paper, we consider a multiple-input multiple-output (MIMO) UVLC link over a vertical turbulence channel which is modeled as the concatenation of multiple non-mixing layers. Under the assumption of cascaded log-normal channel model, we derive the outage probability of vertical MIMO UVLC links and quantify the diversity gain in terms of the number of transmitter/receivers.

Modulation classification (MC) has become a widely used technology, which is of great value in both commercial and civil applications. It actually completes the classification task of modulation signal through various means. In recent years, modulation format recognition based on deep learning (DL) has achieved great success. However, in practical application, the computational cost and model complexity have become the biggest obstacles of the traditional MC based on DL. To solve this problem, we propose complementary folding algorithm (CFA). This is an algorithm based on classical modulation classification (CMC), which folds and splices the features of the input neural network (NN), so that these features have both large-scale and small-scale dual branch receptive fields. The research results prove that under the same network structure and data quantity, both the correctness rate and the convergence speed of CFA are significantly improved in the communication experiment based on underwater visible light communication (UVLC). It is also worth mentioning that because of the particularity and complexity of the channel, UVLC system can be divided into different regions. In any region, CFA performs better than CMC, so we can prove that this algorithm also has excellent robustness.

In this paper, we study different modulation techniques for visible light communication (VLC), taking illumination constraints into account. Two modulation schemes are compared, namely pulse amplitude modulation (PAM) and carrierless amplitude and phase (CAP) modulation, through both simulations and experimental measurements. The data link under study is based on low-cost components comprising a white light-emitting diode (LED) and a silicon PIN photodiode. Moreover, the proposed VLC system complies with illumination standards and limits the brightness level to that of a typical office room. The impact of the roll-off factor parameter, which is directly related to the total occupied bandwidth, and the maximum achievable throughput for PAM and CAP are studied. Moreover, adaptive postdistortion based on a Volterra series expansion is implemented to mitigate the effects of LED nonlinearity in practice. We also demonstrate that 8-PAM can outperform 64-CAP and discrete multitone (DMT) when the LED nonlinearity is adequately compensated.

We have proposed a frequency reshaping and compensation scheme for FTN (Faster-Than-Nyquist) CAP (Carrierless Amplitude and Phase modulation) signal based on machine learning for the first time in this paper. The cascaded post equalizer consists of 2 stages. The first stage digital signal processing (DSP) is a Deep Neural Network (DNN), then LMS post-equalization is conducted as the second stage offline DSP. Through this method, we successfully demonstrated a data rate of 1.12Gbit/s FTN CAP 9QAM modulation over 1meter free space transmission with bit error rate (BER) below 7% FEC threshold of 3.8×10-3. Compared to the traditional FTN CAP modulation without DNN, the proposed method would increase the data rate by approximately 100 Mbps, leading to an improvement of system capacity of 9.8%. The experimental results clearly validate the proposed cascaded two stage DNN-LMS (C2S DNNLMS) can be a promising solution for future high speed VLC system.

We propose an underwater visible light communication (VLC) system for use in drones. The transmitter modulates a message using phase-shift keying (PSK) and emits the signal as LED fast-blinking light. The receiver captures this pattern with a CMOS image sensor using a rolling-shutter effect, and demodulates PSK. In existing VLC systems, rolling-shutter effect is used to transmit baseband signals; this system transmits a passband signal tolerant of low-frequency optical interference noise. System performance was evaluated in test-tank experiments. Findings suggested that the VLC system with PSK outperformed that using on-off keying when noise frequency did not exceed carrier frequency.

ABSTRACTThis research endeavors to investigate the end‐to‐end performance metrics of a submerged AUV within the Single‐Input‐Multi‐Output underwater visible‐light communication (UVLC) system operating in moderate‐to‐strong turbulence channel conditions while accounting for pointing errors. In this study, the closed‐form expressions of analytical work are derived by using the probability density function and cumulative density function with a specific focus on Gamma‐Gamma distribution channel. The analytical framework is used to gain insight into the performance of developed UVLC system within the mixed waters. To validate the accuracy of the analytical approach under the Monte Carlo simulation methodology is used to improve the quality of service. The designed system aims to improve the reliability, practical applicability, and efficiency of the UVLC system, which is the paramount importance in emerging communication technologies.

In this letter we experimentally verify a real-time implementation of the ‘better-than-Nyquist’ pulse shape in carrier-less amplitude and phase (CAP) modulation in the context of a visible light communications system. We use two National Instruments universal software radio peripherals (USRPs) as a transmitter and receiver working independently. Previously reported experimental work on pulse shaping in CAP is also verified in real time, showing lower error vector magnitudes (EVM) can be obtained at shorter filter lengths using the better-than-Nyquist pulses in place of the conventionally used square-root raised cosine as the basis function of the signal. We show that a real time EVM penalty is an additional 3% EVM in the worst case and is a result of synchronisation offset at the receiver.

Carrierless amplitude and phase (CAP) is a bandwidth efficient modulation and line coding scheme that has been accepted by various standardization bodies as the means to accomplish the task of high speed data transfer over voice grade unshielded twisted pair copper cable in digital subscriber line (DSL) applications. This paper considers the design of finite length digital filters for CAP receivers. It is shown that, with an appropriate design strategy, it is possible to obtain good performance from short length FIR filters.

In this paper, we consider underwater visible light communication (UVLC) system with M parallel relaying paths where each path has N decode-and-forward (DF) relays. One path (not necessarily the best one) out of M paths is selected for transmission. Such a multi-hop system is especially useful since some relay nodes might break down or malfunction and hence single path might not be sufficient. Furthermore, selection of the best path is not always possible due to several reasons such as the effect of noise on the estimation of the best path and feedback error. Under the assumption of lognormal (LN) turbulence channels, we derive a closed-form expression for the outage probability of UVLC system where the $m^{\mathrm{th}}$ best path is selected for transmission. We then use our derived closed-form outage probability for investigating the so-called incremental diversity order (IDO).