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Among the problems that prevent free-space optical communication systems from becoming a truly mainstream technology is beam wander, which is especially important for structured light beams since beam misalignment introduces additional crosstalk at the receiver. The paper suggests a recurrent neural network-based (RNN) solution to predict beam wander in free space optics (FSO). The approach uses past beam center of mass positions to predict future movement, significantly outperforming various prediction types. The proposed approach is demonstrated using under-sampled experimental data over a 260 m link as a worst-case and over-sampled simulated data as a best-case scenario. In addition to conventional Gaussian beams, Hermite- and Laguerre-Gaussian beam wander is also investigated. With a 20 to 40% improvement in error over naive and linear predictions, while predicting multiple samples ahead in typical situations and overall matching or outperforming considered predictions across all studied scenarios, this method could help mitigate turbulence-induced fading and has potential applications in intelligent re-transmits, quality of service, optimized error correction, maximum likelihood-type algorithms, and predictive adaptive optics.
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The development of multiple autonomous underwater vehicles (AUVs) has revolutionized the traditional reliance on a single, costly AUV for conducting underwater surveys. This shift has garnered increasing interest among marine researchers. Communication between AUV fleets is an urgent concern due to the data rate limitation of underwater acoustic communication. Laser-based underwater wireless optical communication (UWOC) is a potential solution once the link-establishing requirement between AUVs can be met. Due to the limited coverage area of the laser beam, the previous pointing, acquisition, and tracking (PAT) method is to quickly adjust the beam direction and search for the target according to the set scanning path. In response to these challenges, we propose a scalable laser-based link establishment method that combines the maneuvering of the AUV, the acoustic positioning, and the control of the optical system. Our proposed approach has consistently outperformed the existing PAT method in simulated environments, effectively establishing laser links. Importantly, we have successfully implemented our approach in machine experiments, confirming its practical applicability.
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We present a fast and efficient simulation method of structured light free space optics (FSO) channel effects from propagation through a turbulent atmosphere. In a system that makes use of multiple higher order modes (structured light), turbulence causes crosstalk between modes. This crosstalk can be described by a channel matrix, which usually requires a complete physical simulation or an experiment. Current simulation techniques based on the phase-screen approximation method are very computationally intensive and are limited by the accuracy of the underlying models. In this work, we propose to circumvent these limitations by using a data-driven approach for the decomposition matrix simulation with a conditional generative adversarial network (CGAN) synthetic simulator.
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Monitoring climate change can be accomplished by deploying Internet of Things (IoT) sensor devices to collect data on various climate variables. Providing continuous power or replacing batteries for these devices is not always available, particularly in difficult-access locations and harsh environments. Here, we propose a design for a self-powered weather station that can harvest energy, decode information using solar cells, and is controlled by a programmable system-on-chip. A series of experimental demonstrations have shown the versatility of the proposed design to operate autonomously.
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We designed and tested a distributed acoustic sensing (DAS) that co-exists with optical communication over a two-mode fiber (TMF). In particular, we excited both linearly polarized (LP) modes, LP01 and LP11a, using a photonic lantern for simultaneous information signal transmission while collecting the backscattered Rayleigh light at the near end of the fiber to detect vibrations from a predetermined source. While transmitting data using on-off keying (OOK) or orthogonal frequency-division multiplexing (OFDM) modulation schemes, the optical fiber DAS offers high signal-to-noise ratio (SNR) values that are always larger than the minimum acceptable 2 dB SNR. In addition, as a proof-of-concept experiment, we report parallel sensing and OFDM transmission achieving a data rate of up to 4.2 Gb/s with a bit error rate (BER) of 3.2 × 10-3.
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Extending the field-of-view (FoV) of underwater wireless optical communication (UWOC) receivers can significantly ease the need for active positioning and tracking mechanisms. Two bundle of scintillating fibers emitting at 430- and 488-nm were used to detect two independent signals from ultraviolet and visible laser sources. A zero-forcing approach to minimize inter-channel crosstalk was further implemented. A net aggregated UWOC data rate of 1 Gb/s was achieved using two wavelengths and a non-return-to-zero on-off keying scheme.
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Photodetectors used in wireless applications suffer from a trade-off between their response speeds and their active areas, which limits the received signal-to-noise ratio (SNR). Conventional light-focusing elements used to improve the SNR narrow the field of view (FOV). Herein, we demonstrate a versatile imaging light-focusing element featuring a wide FOV and high optical gain using fused fiber-optic tapers. To verify the practicality of the proposed design, we demonstrated and tested a wide-FOV optical detector for optical wireless communication that can be used for wavelengths ranging from the visible-light band to the near infrared. The proposed detector offers improvements over luminescent wide-FOV detectors, including higher efficiency, a broader modulation bandwidth, and indefinite stability.
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The unique orthogonal shapes of structured light beams have attracted researchers to use as information carriers. Structured light-based free space optical communication is subject to atmospheric propagation effects such as rain, fog, and rain, which complicate the mode demultiplexing process using conventional technology. In this context, we experimentally investigate the detection of Laguerre Gaussian and Hermite Gaussian beams under dust storm conditions using machine learning algorithms. Different algorithms are employed to detect various structured light encoding schemes including the use of a convolutional neural network (CNN), support vector machine, and k-nearest neighbor. We report an identification accuracy of 99% under a visibility level of 9 m. The CNN approach is further used to estimate the visibility range of a dusty communication channel.
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Underwater wireless optical communication (UWOC) can offer reliable and secure connectivity for enabling future internet-of-underwater-things (IoUT), owing to its unlicensed spectrum and high transmission speed. However, a critical bottleneck lies in the strict requirement of pointing, acquisition, and tracking (PAT), for effective recovery of modulated optical signals at the receiver end. A large-area, high bandwidth, and wide-angle-of-view photoreceiver is therefore crucial for establishing a high-speed yet reliable communication link under non-directional pointing in a turbulent underwater environment. In this work, we demonstrated a large-area, of up to a few tens of cm2, photoreceiver design based on ultraviolet(UV)-to-blue color-converting plastic scintillating fibers, and yet offering high 3-dB bandwidth of up to 86.13 MHz. Tapping on the large modulation bandwidth, we demonstrated a high data rate of 250 Mbps at bit-error ratio (BER) of 2.2 × 10-3 using non-return-to-zero on-off keying (NRZ-OOK) pseudorandom binary sequence (PRBS) 210-1 data stream, a 375-nm laser-based communication link over the 1.15-m water channel. This proof-of-concept demonstration opens the pathway for revolutionizing the photodetection scheme in UWOC, and for non-line-of-sight (NLOS) free-space optical communication.
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We study the effect of nonlinear coupling in a WDM configuration over a two-mode fiber. A statistical analysis is presented that takes into account the effect of the random phase-sensitive amplification or depletion. Our results show high nonlinear coupling between the modes. We have quantified the channel power fluctuations, due to the wave phase random variations, at the output of the fiber. We also investigate the effect of random linear mode coupling on the nonlinear mode coupling.
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We experimentally demonstrate an efficient information transmission technique using Laguerre Gaussian (LG) modes. This technique is based on multiplexing and demultiplexing multiple LG modes with different azimuthal and radial components. At the reception, the initially sent modes encoding the information are extracted with high fidelity using a complete decomposition allowing to identify a particular mode from a set of modes within a unique iteration. Importantly, we investigate the effects of the atmospheric turbulence on the proposed communication system. We believe that the proposed technique is promising for high-bit-rate spatial division multiplexing in optical fiber and free space communication systems.
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We numerically studied supercontinuum (SC) generation in a few-mode photonic crystal fiber (PCF). We have shown the impact of the intermodal nonlinear effects that could limit the fundamental mode nonlinear propagation due to the coupling induced by high-order optical modes. We have demonstrated an accurate modeling of the SC generation into the multimode PCF by solving the multimode generalized nonlinear Shrödinger equation (MM-GNLSE). Our detailed investigation of the dynamics of the intermodal nonlinear effects on the SC process confirms the energy transfer between optical degenerate modes during propagation inside the few-mode PCF.
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We propose a simple method for the detection of Bessel beams with arbitrary radial and azimuthal indices, and then demonstrate it in an all-digital setup with a spatial light modulator. We confirm that the fidelity of the detection method is very high, with modal cross-talk below 5%, even for high orbital angular momentum carrying fields with long propagation ranges. To illustrate the versatility of the approach we use it to observe the modal spectrum changes during the self-reconstruction process of Bessel beams after encountering an obstruction, as well as to characterize modal distortions of Bessel beams propagating through atmospheric turbulence.
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Simultaneous lightwave information and power transfer (SLIPT), co-existing with optical wireless communication, holds an enormous potential to provide continuous charging to remote Internet of Things (IoT) devices while ensuring connectivity. Combining SLIPT with an omnidirectional receiver, we can leverage a higher power budget while maintaining a stable connection, a major challenge for optical wireless communication systems. Here, we design a multiplexed SLIPT-based system comprising an array of photodetectors (PDs) arranged in a 3 × 3 configuration. The system enables decoding information from multiple light beams while simultaneously harvesting energy. The PDs can swiftly switch between photoconductive and photovoltaic modes to maximize information transfer rates and provide on-demand energy harvesting. Additionally, we investigated the ability to decode information and harvest energy with a particular quadrant set of PDs from the array, allowing beam tracking and spatial diversity. The design was explored in a smaller version for higher data rates and a bigger one for higher power harvesting. We report a self-powering device that can achieve a gross data rate of 25.7 Mbps from a single-input single-output (SISO) and an 85.2 Mbps net data rate in a multiple-input multiple-output (MIMO) configuration. Under a standard AMT1.5 illumination, the device can harvest up to 87.33 mW, around twice the power needed to maintain the entire system. Our work paves the way for deploying autonomous IoT devices in harsh environments and their potential use in space applications.
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Oceans are crucial to human survival, providing natural resources and most of the global oxygen supply, and are responsible for a large portion of worldwide economic development. Although it is widely considered a silent world, the sea is filled with natural sounds generated by marine life and geological processes. Man-made underwater sounds, such as active sonars, maritime traffic, and offshore oil and mineral exploration, have significantly affected underwater soundscapes and species. In this work, we report on a joint optical fiber-based communication and sensing technology aiming to reduce noise pollution in the sea while providing connectivity simultaneously with a variety of underwater applications. The designed multifunctional fiber-based system enables two-way data transfer, monitoring marine life and ship movement near the deployed fiber at the sea bottom and sensing temperature. The deployed fiber is equally harnessed to transfer energy that the internet of underwater things (IoUTs) devices can harvest. The reported approach significantly reduces the costs and effects of monitoring marine ecosystems while ensuring data transfer and ocean monitoring applications and providing continuous power for submerged IoUT devices.
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Mode division multiplexing (MDM) is mooted as a technology to address future bandwidth issues, and has been successfully demonstrated in free space using spatial modes with orbital angular momentum (OAM). To further increase the data transmission rate, more degrees of freedom are required to form a densely packed mode space. Here we move beyond OAM and demonstrate multiplexing and demultiplexing using both the radial and azimuthal degrees of freedom. We achieve this with a holographic approach that allows over 100 modes to be encoded on a single hologram, across a wide wavelength range, in a wavelength independent manner. Our results offer a new tool that will prove useful in realizing higher bit rates for next generation optical networks.