Dual D-shaped plastic optical fiber for simultaneous measurement of refractive index and temperature based on specklegram.

The refractive index (RI) measurment of the liquid often changes with the sensor's temperature. Accurate RI measurements require simultaneous measurements of the liquid temperature to calibrate the RI measurement. This study proposed what we believe to be a novel dual D-shaped plastic optical fiber sensor capable of simultaneously measuring both RI and temperature. A fluorescent material made of rhodamine B (RhB) is embedded in one of the D-shaped structures of the dual D-shaped fiber, which can be excited by a green laser to produce orange fluorescence. The fluorescence and the input laser of the fiber are superimposed at the output end of the fiber to form a specklegram containing information of two wavelengths. It was found through experiments that the effects of temperature and RI change on the red and green channels of the specklegrams are different, and the neural network can learn this feature to complete the measurement of both RI and temperature parameters. For RI sensing, the maximum error between the average predicted value and the true value of the test set is 0.0005. For temperature sensing, the maximum error between the average predicted value and the true value of the test set is 0.26°C. In addition, because the intensity change of the fluorescence varies linearly with RI and temperature, the sensor also has good stability.

Auxiliary management and control channel aided crosstalk online monitoring in multi-core fibers.

As a stochastic perturbation, the inter-core crosstalk (IC-XT) severely distorts the signal in multi-core fibers (MCF), especially for long-haul transmission. How to quickly measure and monitor the IC-XT online for an MCF-based space division multiplexing (SDM) system is of special importance. In this paper, we introduce the technology of auxiliary management and control channel (AMCC) to online monitor the IC-XT of MCF, in which the unique advantage of low-frequency auxiliary management and control signal is fully utilized with the limited influence on high-speed data transmission. Specifically, two orthogonal sequences are chosen as monitoring signals for the signal-channel core and the crosstalk-channel core, respectively, followed by digital signal processing (DSP) for the received signal to evaluate the real-time crosstalk accurately. The experimental verifications of XT online monitoring confirm the effectiveness of our proposed method with very small monitoring error (mostly < 0.5 dB) for both heterodyne XT and homodyne XT in the C and L bands, showing its great potential for future SDM systems.

MIMO detection using an ALR-CNN in SDM transmission systems.

Multiple-input multiple-output (MIMO) detectors have been a key technology in communication systems. In this paper, a new MIMO detector is designed by combining the adaptive learning rate (ALR) with the convolutional neural network (CNN) and successfully implementing it in a mode division multiplexing (MDM) optical transmission system. The results show that the training and test accuracy of the signal in the system we proposed reaches 100%. What is more, we used the ALR-CNN to compare the performance with conventional detection algorithms. The results confirm that our DLNN exceeds the conventional MIMO detectors in performance and is able to achieve the ideal QPSK BER level. The minimum difference in the SNR is about 9.5 dB at a BER of the 10-3 order.