Existing wavefront sensorless (WFS-less) adaptive optics (AO) generally require a search algorithm that takes lots of iterations and measurements to get optimal results. So the latency is a serious problem in the current WFS-less AO system, especially in applications to free-space optics communication. To solve this issue, we propose a deep neural network (DNN)–based aberration correction method. The DNN model can detect the wavefront distortion directly from the intensity images, thereby avoiding time-consuming iterative processes. Since the tip-and-tilt mode of Zernike coefficients are considered, the tip-tilt correction system is not necessarily required in the proposed method. From our simulation results, the proposed method can effectively reduce the computation time and has an impressive improvement of root mean square (RMS) in different turbulence conditions.

In this paper, a novel turbo-coded 16-ary orbital angular momentum - shift keying-free space optical (OAM-SK-FSO) communication system combining a convolutional neural network (CNN) based adaptive demodulator under strong atmospheric turbulence is proposed for the first time. The feasibility of the scheme is verified by transmitting a 256-grayscale two-dimensional digital image. The bit error ratio (BER) performance of the system is investigated and the effect of different factors such as turbulence strength, propagation distance, code rate, length of random interleaver and length of bit interleaver is also taken into account. An advanced encoder/decoder structure and mapping scheme are applied to diminish the influence of CNN misclassification and reduce the BER effectively. With the optimal encoder/decoder structure and CNN model settings, the BER varies from 0 to $4.89\times {10}^{-4}$ when the propagation distance increases from 200m to 1000m for a given turbulence strength ${\text{C}}_n^2$ equals $5\times {10}^{-14}{m}^{-2/3}$. For a determined propagation distance equals 400m, the BER ranges from 0 to $4.01\times {10}^{-4}$ when ${\text{C}}_n^2$increases from $1\times {10}^{-15}{m}^{-2/3}$ to $4\times {10}^{-13}{m}^{-2/3}$. Our numerical simulations demonstrate that the proposed system can provide better BER performance under strong atmospheric turbulence and conditions when the classification ability of CNN is limited.

Orbital angular momentum (OAM) has the potential to dramatically enhance the amount of information in the Internet of Underwater Things (IoUT) system. Nevertheless, underwater-turbulence-induced scintillation will destroy the orthogonality of OAM modes, hence degrading the performance of the system. In this article, a random-amplitude-mask-based adaptive optics (AOs) technique is proposed for the sake of mitigating the turbulence effects in the OAM-based underwater wireless optical communication (UWOC) system. Combined with phase retrieval algorithms, the magnitudes of linear measurements obtained from the distorted OAM beams modulated with a series of random amplitude masks and focused by a lens are employed for the phase estimation. Furthermore, we present a comprehensive performance comparison against state-of-the-art phaseless wave-front sensing techniques. Moreover, the mixture exponential-generalized gamma (EGG) distribution is applied for characterizing the probability density function (PDF) of reference-channel irradiance of OAM beams coupled into a single-mode fiber (SMF). In the end, the performance metrics, such as the outage probability, the average bit-error-rate (BER), and the ergodic capacity are analyzed with the aid of PDF for both single-input-single-output (SISO) and multiinput-multioutput (MIMO) systems. In a nutshell, this article provides new insights for the applications of AO in the OAM-based UWOC system, which can serve as a candidate for supporting IoUT devices.

Stochastic nonlinear impairment is the primary factor that limits the transmission performance of high-speed orbital angular momentum (OAM) mode-division multiplexing (MDM) optical fiber communication systems. This Letter presents a low-complexity adaptive-network-based fuzzy inference system (LANFIS) nonlinear equalizer for OAM-MDM intensity-modulation direct-detection (IM/DD) transmission with three OAM modes and 15 wavelength division multiplex (WDM) channels. The LANFIS equalizer could adjust the probability distribution functions (PDFs) of the distorted pulse amplitude modulation (PAM) symbols to fit the statistical characteristics of the WDM–OAM-MDM transmission channel. Therefore, although the transmission symbols in the WDM–OAM-MDM system are subjected to a stochastic nonlinear impairment, the proposed LANFIS equalizer can effectively compensate the distorted signals. The proposed equalizer outperforms the Volterra equalizer with improvements in receiver sensitivity of 2, 1.5, and 1.3 dB for three OAM modes at a wavelength of 1550.12 nm, respectively. It also outperforms a CNN equalizer, with improvements in receiver sensitivity of 1, 0.5, and 0.3 dB, respectively. Moreover, complexity reductions of 67%, 74%, and 99.9% are achieved for the LANFIS equalizer compared with the Volterra, CNN, and ANFIS equalizers, respectively. The proposed equalizer has high performance and low complexity, making it a promising candidate for a high-speed WDM–OAM-MDM system.

The frozen-wave-based longitudinal orbital angular momentum multiplexing (LOAMM) system developed in [ IEEE Photonics J. 10, 7900416 (2018)10.1109/JPHOT.2017.2778238 ] has the potential to overcome the crosstalk effects induced by turbulence. In this paper, we propose a defocus measurement aided adaptive optics (DMA-AO) technique for turbulence compensation in a LOAMM underwater wireless optical communication (UWOC) system to investigate the enhancement of physical layer security. Relying on a phase retrieval algorithm and probe beam, three amplitude-only measurements obtained from different back focus planes can realize phase reconstruction of distorted OAM beams. Moreover, the so-called mixture generalized gamma-Johnson S _B (GJSB) distribution is proposed to characterize the probability density function (PDF) of reference-channel irradiance of OAM. The GJSB allows for obtaining closed-form and analytically tractable expression for the probability of strictly positive secrecy capacity (SPSC) in a single input single output (SISO) system. Furthermore, the average secrecy capacity (ASC) and probability of SPSC for a multiple input multiple output (MIMO) system are investigated. Compared to the traditional OAM multiplexing system based on Laguerre-Gaussian (LG) beams, the LOAMM system with a probe beam assisted DMA-AO technique has potential advantages for improving the security performance in UWOC.

The underwater turbulence channel is modelled and a unified statistical distribution is applied for characterizing orbital angular momentum (OAM) propagation in underwater wireless optical communication (UWOC) systems. Based on Monte-Carlo simulations, the effects of turbulences are characterized by the multiple phase screens model considering both the coherence width and scintillation index. The phase screen samples are processed by the randomized spectral sampling discrete Fourier transform (DFT) technique. To validate the propagated field distribution, both the phase structure function and optical transfer function are derived and evaluated with the aid of ensemble-averaged results. The Generalized Gamma Distribution (GGD) enriched by an additional independent parameter is applied for modelling the probability density function (PDF) of both the reference-channels, fluctuating irradiance as well as the intermodal crosstalk irradiance between different OAM modes. Furthermore, based on the PDF, the performance metrics of both single input multiple output (SISO) and multiple input multiple output (MIMO) systems are analyzed, based on the average capacity, the bit-error rate and the outage probability.