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We present the use of interconnected optical mesh networks for early earthquake detection and localization, exploiting the existing terrestrial fiber infrastructure. Employing a waveplate model, we integrate real ground displacement data from seven earthquakes with magnitudes ranging from four to six to simulate the strains within fiber cables and collect a large set of light polarization evolution data. These simulations help to enhance a machine learning model that is trained and validated to detect primary wave arrivals that precede earthquakes' destructive surface waves. The validation results show that the model achieves over 95% accuracy. The machine learning model is then tested against an M4.3 earthquake, exploiting three interconnected mesh networks as a smart sensing grid. Each network is equipped with a sensing fiber placed to correspond with three distinct seismic stations. The objective is to confirm earthquake detection across the interconnected networks, localize the epicenter coordinates via a triangulation method and calculate the fiber-to-epicenter distance. This setup allows early warning generation for municipalities close to the epicenter location, progressing to those further away. The model testing shows a 98% accuracy in detecting primary waves and a one second detection time, affording nearby areas 21 s to take countermeasures, which extends to 57 s in more distant areas. [ABSTRACT FROM AUTHOR]

Presents a method for the evaluation of bit error rate (BER) in optical systems where the received noise can have an arbitrary spectral shape. Assumptions for the method of evaluating the BER system; Algorithms used to implement the method; Validation of the method.

The authors study the performance of pulse-amplitude modulation, with 2, 4 and 8 levels per symbol, for short reach applications with propagation over up to 2 km of standard single mode fibre. They consider the three modulation formats operated both at the same bit-rate of 25 Gbps and at same symbol rate of 25 Gbaud, supposing 3.125% forward error-correction overhead and bit error rate threshold of 10-4. They analyse transmitters (Tx) and receivers (Rx) based on digital signal processing, including a training-driven finite impulse response (FIR) filter equaliser set through the least-mean-square algorithm. They analyse the sensitivity impairments induced by a limited Tx/Rx electrical bandwidth and evaluate the minimum number of taps - and consequent latency - needed by the FIR equaliser to obtain sensitivity benefits. [ABSTRACT FROM AUTHOR]