Distributed optical fiber sensing is a unique technology that offers unprecedented advantages and performance, especially in those experimental fields where requirements such as high spatial resolution, the large spatial extension of the monitored area, and the harshness of the environment limit the applicability of standard sensors. In this paper, we focus on one of the scattering mechanisms, which take place in fibers, upon which distributed sensing may rely, i.e., the Rayleigh scattering. One of the main advantages of Rayleigh scattering is its higher efficiency, which leads to higher SNR in the measurement; this enables measurements on long ranges, higher spatial resolution, and, most importantly, relatively high measurement rates. The first part of the paper describes a comprehensive theoretical model of Rayleigh scattering, accounting for both multimode propagation and double scattering. The second part reviews the main application of this class of sensors.

Experimental results of measurement of the beat length and the differential group delay of several types of long single-mode fiber are presented. The proposed measurement technique is based on a polarization-sensitive analysis of the backscattered signal and allows one to calculate the correlation length of the random birefringence affecting the fiber.

This paper aims to comprehensively review the literature on Gaseous Plasma Antennas (GPAs). These innovative devices transmit electromagnetic (EM) signals through ionized gas, known as plasma, instead of conventional metal structures. GPAs offer distinct advantages over their metallic counter-parts, particularly in performance reconfigurability. The paper begins by evaluating the EM properties of the plasma medium, exploring methodologies for its generation, measurement, and simulation. Subsequently, the prevalent GPA architectures are presented, distinguishing between active and passive concepts based on the plasma’s primary role: either emitting EM signals or manipulating them. Additionally, unconventional GPA implementations, such as explosive or laser-based technologies, are examined. Finally, the paper assesses the most promising applications for leveraging GPAs in various fields.

This paper describes the implementation of an FBG sensor to measure water levels in a dike. The sensor is based on a 3D-printed mechanical transducer through which the external pressure is converted into longitudinal strain exerted on the fiber. An additional FBG integrated within the sensor measures temperature and is used to compensate for the temperature effects on the first FBG. By employing an aluminum alloy case, the sensor is suitable for operations in harsh environments and rough installation procedures. Four sensors of this kind have been successfully tested on a real scale dike at the Water Proof Holland facility in The Netherlands.

One of the most promising solutions to overcome the capacity limit of current optical fiber links is space-division multiplexing, which allows the transmission on various cores of multi-core fibers or modes of few-mode fibers. In order to realize such systems, suitable optical fiber amplifiers must be designed. In single mode fibers, Raman amplification has shown significant advantages over doped fiber amplifiers due to its low-noise and spectral flexibility. For these reasons, its use in next-generation space-division multiplexing transmission systems is being studied extensively. In this work, we propose a deep learning method that uses automatic differentiation to embed a complete few-mode Raman amplification model in the training process of a neural network to identify the optimal pump wavelengths and power allocation scheme to design both flat and tilted gain profiles. Compared to other machine learning methods, the proposed technique allows to train the neural network on ideal gain profiles, removing the need to compute a dataset that accurately covers the space of Raman gains we are interested in. The ability to directly target a selected region of the space of possible gains allows the method to be easily generalized to any type of Raman gain profiles, while also being more robust when increasing the number of pumps, modes, and the amplification bandwidth. This approach is tested on a 70 km long 4-mode fiber transmitting over the C+L band with various numbers of Raman pumps in the counter-propagating scheme, targeting gain profiles with an average gain in the interval from 5 dB to 15 dB and total tilt in the interval from —1.425 dB to 1.425 dB. We achieve wavelength- and mode-dependent gain fluctuations lower than 0.04 dB and 0.02 dB per dB of gain, respectively.

Coupled-mode theory is a powerful tool to understand and control the effects of deployment and fabrication imperfections on optical waveguides. Although it provides many advantages compared to the finite element method, it still lacks the ability to treat geometric and material perturbations when they act simultaneously on the waveguide. This work fills this gap, providing a novel framework for a unified treatment of geometric and material perturbations in the coupled-mode analysis. The proposed approach consists of, first, applying the theory of transformation optics to convert geometric deformation into material perturbations and, second, studying the obtained waveguide by using a custom-developed coupled-mode theory able to deal with perturbations of both the permittivity and the permeability tensor. The framework is applied to three examples: a solid-core fiber affected by intrinsic perturbations, a bent solid-core fiber, and an elliptical hollow-core fiber. Results are validated against simulations based on the finite element method and compared with the standard coupled-mode theory most suitable for each specific example; they show that the proposed unified coupled-mode theory performs consistently better than standard theories, confirming it as a general and accurate tool for the design and analysis of optical waveguides.