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.

Posts

Seamless Service Handover in UAV-based Mobile Edge Computing

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Unmanned aerial vehicles (UAVs), such as drones, can carry high-performance computing devices (e.g., servers) to provide flexible and on-demand data processing services for theusers in the network edge, leading to the so-called mobile edge computing. In mobile edge computing, researchers have already explored how to optimize the computation offloading and the trajectory planning of UAVs, as well as how to perform the service handover when mobile users move from one location to another. However, there is one critical challenge that has been neglected in past research, which is the limited battery life of UAVs. On average, commercial-level drones only have a battery life of around 30 minutes to 2 hours. As a result, during operation, mobile edge computing carriers have to frequently deal with service handovers that require shifting users and their computing jobs from low-battery UAVs to new fully-charged UAVs. This is the first work that focuses on addressing this challenge with the goal of providing continuous and uninterrupted mobile edge computing service. In particular, we propose a seamless service handover system that achieves minimum service downtime when handling the duty shift between low-battery UAVs and new fullycharged UAVs. In addition, we propose a novel UAV dispatchalgorithm that provides guidelines about how to dispatch new fully-charged UAVs and where to retrieve low-battery UAVs, with the objective of maximizing UAVs’ service time. The effectiveness of the proposed service handover system and the proposed UAV dispatch algorithm is demonstrated through comprehensive simulations using a time-series event-driven simulator.

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Long Term Monitoring and Analysis of Brood X Cicada Activity by Distributed Fiber Optic Sensing Technology

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Brood X is the largest of the 15 broods of periodical cicadas, and individuals from this brood emerged across the Eastern United States in spring 2021. Using distributed acoustic sensing (DAS) technology, the activity of Brood X cicadas was monitored in their natural environment in Princeton, NJ. Critical information regarding their acoustic signatures and activity level is collected and analyzed using standard outdoor-grade telecommunication fiber cables. We believe these results have the potential to be a quantitative baseline for regional Brood X activity and pave the way for more detailed monitoring of insect populations to combat global insect decline. We also show that it is possible to transform readily available fiber optic networks into environmental sensors with no additional installation costs. To our knowledge, this is the first reported use case of a distributed fiber optic sensing system for entomological sciences and environmental studies.

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Real-Time Photonic Blind Interference Cancellation

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mmWave devices can broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates. Data transfer can, however, be compromised by interference. Photonic blind interference cancellation systems offer a power-efficient means of mitigating interference, but previous demonstrations of such systems have been limited by high latencies and the need for regular calibration. Here, we demonstrate real-time photonic blind interference cancellation using an FPGA-photonic system executing a zero-calibration control algorithm. Our system offers a greater than 200-fold reduction in latency compared to previous work, enabling sub-second cancellation weight identification. We further investigate key trade-offs between system latency, power consumption, and success rate, and we validate sub-Nyquist sampling for blind interference cancellation. We estimate that photonic interference cancellation can reduce the power required for digitization and signal recovery by greater than 74 times compared to the digital electronic alternative.

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Beyond Communication: Telecom Fiber Networks for Rain Detection and Classification

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We present the field trial of an innovative neural network and DAS-based technique, employing a pre-trained CNN fine-tuning strategy for effective rain detection and classification within two practical scenarios.

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Distributed Fiber-Optic Sensor as an Acoustic Communication Receiver Array

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A novel acoustic transmission technique using distributed acoustic sensors is introduced. By choosing better incident angles for smaller fading and employing an 8- channel beamformer, over 10KB data is transmitted at a 6.4kbps data rate.

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OFDM Signal Transmission Using Distributed Fiber-Optic Acoustic Sensing

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Acoustic data transmission with the Orthogonal Frequency Division Multiplexing (OFDM) signal has been demonstrated using a Distributed Acoustic Sensor (DAS) based on Phase-sensitive Optical Time-Domain Reflectometry (?-OTDR).

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Long Reach Fibre Optic Distributed Acoustic Sensing using Enhanced Scattering Fibre

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We report significant noise reduction in distributed acoustic sensing (DAS) link using enhanced-scatter fibre (ESF). The longest reach of 195km DAS link without inline amplifications is also demonstrated. We further present demonstration of simultaneous fibre-optic sensing and 400Gb/s data transmissions over 195km fibre using ESF.

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First Field Demonstration of Automatic WDM Optical Path Provisioning over Alien Access Links for Data Center Exchange

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We demonstrated under six minutes automatic provisioning of optical paths over field- deployed alien access links and WDM carrier links using commercial-grade ROADMs, whitebox mux-ponders, and multi-vendor transceivers. With channel probing, transfer learning, and Gaussian noise model, we achieved an estimation error (Q-factor) below 0.7 dB

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Real-time Intrusion Detection and Impulsive Acoustic Event Classification with Fiber Optic Sensing and Deep Learning Technologies over Telecom Networks

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We review various use cases of distributed-fiber-optic-sensing and machine-learning technologies that offer advantages to telecom fiber networks on existing fiber infrastructures. Byleveraging an edge-AI platform, perimeter intrusion detection and impulsive acoustic event classification can be performed locally on-the-fly, ensuring real-time detection with low latency.

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A Temperature-Informed Data-Driven Approach for Behind-the-Meter Solar Disaggregation

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The lack of visibility to behind-the-meter (BTM) PVs causes many challenges to utilities. By constructing a dictionary of typical load patterns based on daily average temperatures and power consumptions, this paper proposes a temperature-informed data-driven approach for disaggregating BTM PV generation. This approach takes advantage of the high correlation between outside temperature and electricity consumption, as well as the high similarity between PV generation profiles. First, temperature-based fluctuation patterns are extracted from customer load demands without PV for each specific temperature range to build a temperature-based dictionary (TBD) in the offline stage. The dictionary is then used to disaggregate BTM PV in real-time. As a result, the proposed approach is more practical and provides a useful guideline in using temperature for operators in online mode. The proposed methodology has been verified using real smart meter data from London.

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