Optical Networking and SensingRead our Optical Networking and Sensing publications from our team of researchers. We are leading world-class research into the next generation of optical networks and sensing systems that will power ICT-based social solutions for years. We advance globally acknowledged innovation by engaging in visionary theoretical research, pioneering experiments, and leading technology field trials. Our work not only foresees the future but also transforms it into today’s reality.

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Multi user Beam Alignment in Presence of Multi path

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To overcome the high path loss and the intense shadowing in millimeter wave (mmWave) communications, effective beamforming schemes are required which incorporate narrow beams with high beamforming gains. The mmWave channel consists of a few spatial clusters each associated with an angle of departure (AoD). The narrow beams must be aligned with the channel AoDs to increase the beamforming gain. This is achieved through a procedure called beam alignment (BA). Most of the BA schemes in the literature consider channels with a single dominant path while in practice the channel has a few resolvable paths with different AoDs, hence, such BA schemes may not work correctly in the presence of multi path or at the least do not exploit such multipath to achieve diversity or increase robustness. In this paper, we propose an efficient BA scheme in presence of multi path. The proposed BA scheme transmits probing packets using a set of scanning beams and receives feedback for all the scanning beams at the end of the probing phase from each user. We formulate the BA scheme as minimizing the expected value of the average transmission beamwidth under different policies. The policy is defined as a function from the set of received feedback to the set of transmission beams (TB). In order to maximize the number of possible feedback sequences, we prove that the set of scanning beams (SB) has a special form, namely, Tulip Design. Consequently, we rewrite the minimization problem with a set of linear constraints and a reduced number of variables which is solved by using an efficient greedy algorithm.

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Distributed Fiber Sensor Network Using Telecom Cables as Sensing Media: Technology Advancements and Applications

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Distributed fiber optic sensing (DFOS) is a rapidly evolving field that allows the existing optical fiber infrastructure for telecommunications to be reused for wide-area sensing. Using the backscattering mechanisms of glass—which includes Rayleigh, Brillouin, and Raman backscatter—it is possible to realize distributed vibration and temperature sensors with good sensitivity at every fiber position, and spatial resolution is determined by the bandwidth of the interrogation signal. In this paper, we will review the main technologies in currently deployed DFOS. We review the digital signal processing operations that are performed to extract the sensing parameters of interest. We report recent distributed vibration sensing, distributed acoustic sensing, and distributed temperature sensing field trial results over an existing network with reconfigurable add/drop multiplexers carrying live telecom traffic, showing that the network is capable of simultaneous traffic and temperature monitoring. We report Brillouin optical time-domain reflectometry experimental results for monitoring static strain on aerial fiber cables suspended on utility poles. Finally, we demonstrate an example of network modification to make passive optical networks compatible with DFOS by adding reflective semiconductor optical amplifiers at optical network units.

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Detection and Localization of Stationary Weights Hanging on Aerial Telecommunication Fibers using Distributed Acoustic Sensing

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For the first time to our knowledge, a stationary weight hanging on an operational aerial telecommunication field fiber was detected and localized using only ambient data collected by a φ-DAS system. Although stationary weights do not create temporally varying signals, and hence cannot be observed directly from the DAS traces, the existence and the location of the additional weights were revealed by the operational modal analysis of the aerial fiber structure.

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Bipolar Cyclic Linear Coding for Brillouin Optical Time Domain Analysis

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We demonstrate, for the first time, that cyclic linear pulse coding can be bipolar for BOTDA sensors, breaking the unipolar limitation of linear coding techniques and elevating the coding gain for a given code length.

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First Field Trial of Monitoring Vehicle Traffic on Multiple Routes by Using Photonic Switch and Distributed Fiber Optics Sensing System on Standard Telecom Networks

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We demonstrated for the first time that motor vehicle traffic and road capacity on multiple fiber routes can be monitored by using a distributed-fiber-optics-sensing system with a photonic switch on in-service telecom fiber cables.

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Employing Telecom Fiber Cables as Sensing Media for Road Traffic Applications

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Distributed fiber optic sensing systems (DFOS) allow deployed fiber cables to be sensing media, not only dedicated function of data transmission. The fiber cable can monitor the ambient environment over wide area for many applications. We review recent field trial results, and show how artificial intelligence (AI) can help on the application of road traffic monitoring. The results show that fiber sensing can monitor the periodic traffic changes in hourly, daily, weekly and seasonal.

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A Silicon Photonic-Electronic Neural Network for Fiber Nonlinearity Compensation

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In optical communication systems, fibre nonlinearity is the major obstacle in increasing the transmission capacity. Typically, digital signal processing techniques and hardware are used to deal with optical communication signals, but increasing speed and computational complexity create challenges for such approaches. Highly parallel, ultrafast neural networks using photonic devices have the potential to ease the requirements placed on digital signal processing circuits by processing the optical signals in the analogue domain. Here we report a silicon photonic–electronic neural network for solving fibre nonlinearity compensation in submarine optical-fibre transmission systems. Our approach uses a photonic neural network based on wavelength-division multiplexing built on a silicon photonic platform compatible with complementary metal–oxide–semiconductor technology. We show that the platform can be used to compensate for optical fibre nonlinearities and improve the quality factor of the signal in a 10,080 km submarine fibre communication system. The Q-factor improvement is comparable to that of a software-based neural network implemented on a workstation assisted with a 32-bit graphic processing unit.

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Guided Acoustic Brillouin Scattering Measurements In Optical Communication Fibers

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Guided acoustic Brillouin (GAWBS) noise is measured using a novel, homodyne measurement technique for four commonly used fibers in long-distance optical transmission systems. The measurements are made with single spans and then shown to be consistent with separate multi-span long-distance measurements. The inverse dependence of the GAWBS noise on the fiber effective area is confirmed by comparing different fibers with the effective area varying between 80 µm2 and 150 µm2. The line broadening effect of the coating is observed, and the correlation between the width of the GAWBS peaks to the acoustic mode profile is confirmed. An extensive model of the GAWBS noise in long-distance fibers is presented, including corrections to some commonly repeated mistakes in previous reports. It is established through the model and verified with the measurements that the depolarized scattering caused by TR2m modes contributes twice as much to the optical noise in the orthogonal polarization to the original source, as it does to the noise in parallel polarization. Using this relationship, the polarized and depolarized contributions to the measured GAWBS noise is separated for the first time. As a result, a direct comparison between the theory and the measured GAWBS noise spectrum is shown for the first time with excellent agreement. It is confirmed that the total GAWBS noise can be calculated from fiber parameters under certain assumptions. It is predicted that the level of depolarized GAWBS noise created by the fiber may depend on the polarization diffusion length, and consequently, possible ways to reduce GAWBS noise are proposed. Using the developed theory, dependence of GAWBS noise on the location of the core is calculated to show that multi-core fibers would have a similar level of GAWBS noise no matter where their cores are positioned.

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Optical Fiber Sensing Technology Visualizing the Real World via Network Infrastructures – AI technologies for traffic monitoring

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Optical fibers have a sensing function that captures environmental changes around the fiber cable. According to the recent technology evolution of optical transmission and AI, the application of the fiber sensing has expanded and visualization accuracy has improved. We have proposed to monitor the traffic flow on the road using the existing optical fiber infrastructure along the road. In this paper, we propose a traffic flow analysis AI algorithm with high environmental resistance and show the evaluation results of traffic monitoring.

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An Efficient Approach for Placing Distributed Fiber Optic Sensors with Concurrent Sensing Capability

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We propose an efficient approach for placing distributed fiber optic sensors (DFOS) with concurrent sensing capability. It consumes 5.7% to 9.5% fewer sensors than that using DFOS without concurrent sensing, for covering the same network.

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