Increasing resolution transmission through imaging multi-core fiber via code mask multiplexing

Abstract In optical fiber shape sensing technology, traditional multi-core fiber optic sensors are limited by their small sensing fiber radius, making it difficult to respond to small curvature bending. This paper proposes a novel fiber optic shape sensor scheme, including a fiber optic shape sensor with a diameter of 4 mm based on a glass fiber reinforced plastic substrate, and an adaptive equivalent core distance correction algorithm for correcting core position errors. Simulation results show that the sensor can effectively measure deformations with curvature radius exceeding 5 meters. To verify the theoretical model, a three-dimensional (3D) sensing experiment was conducted. The experiment showed that after correction by the equivalent core distance correction algorithm, the measurement accuracy of the sensor was significantly improved, with the maximum relative error decreasing from 38% to 2.5%.

Abstract Multicore fibers (MCF) can overcome the capacity limitations of the network by enabling space-division multiplexing (SDM). Based on inter-core interaction, classification puts the MCFs into two groups. The first group is weakly-coupled (WC) MCFs. The second group is strongly-coupled (SC) MCFs. WC-MCFs are the weakly-coupled MCFs that minimize crosstalk through optimized core spacing and refractive-index engineering. Many researchers consider the independent transmission channels suitable for long-haul networks, high-capacity optical links, and emerging 5G/6G fronthaul deployment due to their stability and compatibility with existing infrastructure. Recent research highlights the complementary nature of WC and SC designs: WC-MCF is better for low-crosstalk independent-channel long-haul and practical deployment, while SC-MCF is better for maximizing spatial-spectral capacity and petabit-class core transport. In terms of capacity, strongly coupled MCF (SC-MCF) is better because its supermode-based spatial multiplexing supports far higher spatial channel counts and ultra-high petabit-class throughput compared to weakly coupled MCF.

We present a high-precision endoscopic shape-sensing method using only two calibrated outer cores of a multicore fiber Bragg grating (MC-FBG) array. By leveraging the geometric relationship among two non-collinear outer cores and the central core, the method estimates curvature and bending angle without relying on multiple outer-core channels, thereby reducing complexity and error propagation. On canonical shapes, the proposed method achieves maximum relative reconstruction errors of 1.62% for a 2D circular arc and 2.81% for a 3D helix, with the corresponding RMSE values reported for completeness. In addition, representative endoscope-relevant configurations including the α-loop, reversed α-loop, and N-loop are accurately reconstructed, and temperature tests over 25–81 °C further verify stable reconstruction performance under thermal disturbances. This work provides a resource-efficient and high-fidelity solution for endoscopic shape sensing with strong potential for integration into next-generation image-guided and robot-assisted surgical systems.

We propose a vector bending sensor based on a tapered few-mode multi-core fiber (FM-MCF). A seven-core six-mode fiber is tapered with an optimized taper ratio, enabling bending sensing through power monitoring. When the tapered FM-MCF bends, coupling occurs between the central core and side cores in the tapered region. By monitoring the power of all cores and employing a power differential method, the bending direction and curvature can be reconstructed. The results show that within a curvature range of 2.5 m−1 to 10 m−1, the sensitivity of the ratio of the side core’s power to the middle core’s power with respect to curvature is not less than 0.14/m−1. A deep fully connected feedforward neural network (DNN) is used to demodulate all power information and predict the bending shape of the optical fiber. The algorithm predicts the bending radius and rotation angle with mean absolute errors less than 0.038 m and 3.087°, respectively. This method is expected to achieve low-cost, high-sensitivity bending measurement applications with vector direction perception, providing an effective solution for scenarios with small curvatures that are challenging to detect using conventional sensing methods.

Co-transmission of radio frequency reference and data signal over multi-core fiber.

We investigated the performance of an adaptive multiple-input multiple-output (MIMO) filter with non-integer fractional sampling at sub-symbol rate sampling for long-haul space-division multiplexed (SDM) transmission over coupled-core multi-core fibers. We evaluated a frequency-domain adaptive 8×8 filter operating at a fractional sampling through a numerical simulation of long-haul SDM transmission of 32-Gbaud polarization-division multiplexed quadrature phase shift keying (PDM-QPSK) signals over four-coupled-core fiber (4-CCF) under a sampling timing offset. The fractional sampling frequency-domain adaptive MIMO filter maintained a nearly constant pre-forward error correction (FEC) Q factor across a sampling timing offset range of one symbol period after 100×100-km transmission, even when the sampling rate was reduced to 7/8× of the symbol rate, demonstrating excellent tolerance to timing offset. To mitigate the performance penalty due to intersymbol interference (ISI) at sub-symbol rate sampling, we also examined an adaptive interference canceller that generates interference replicas on the basis of tentative decision results of signals and an adaptive MIMO filter. With 15/16× sampling, the penalty of the pre-FEC Q from the case with 2× oversampling after 100×100 km transmission was reduced by 1 dB when the adaptive interference canceller was used after the frequency-domain adaptive MIMO filter. We also confirmed the compensation of the sampling timing offset by the fractional sampling frequency-domain adaptive MIMO filter at sub-symbol rate sampling and the mitigation of ISI by the adaptive interference canceller in a transmission experiment with 32-Gbaud PDM-QPSK signals over 4-CCFs in a recirculating loop configuration after 6240 km.

The explosive growth of optical interconnection service traffic urgently necessitates the evolution of optical transponders and fibers. The core-division-multiplexed (CDM) transmission technique using weakly coupled multi-core fibers (MCFs) and beyond-1T optical transport network (OTN) transponders has emerged as an attractive solution to meet the bandwidth demands of future networks. In this paper, we demonstrate an ultra-high-speed OTN system using C+L-band 1.2 Tb/s OTN transponders with a weakly coupled seven-core fiber. The OTN transponders support two configurable modulation rates of 135 Gbaud and 155 Gbaud, along with a probability constellation-shaping 64-ary quadrature amplitude modulation (PCS-64QAM) format. The MCF exhibits characteristics comparable to those of SMFs and negligible inter-core crosstalk, providing a superior physical channel for ultra-high-speed CDM transmission. Fiber length and low-noise EDFAs are also chosen to enhance the transmission distance under the limited optical signal-to-noise ratio (OSNR) budget when using 1.2 Tb/s OTN transponders. Benefiting from the high-performance OTN transponders and MCF, we achieve real-time 0.672 Pb/s and 0.571 Pb/s 4 × 89 km CDM transmissions using 135 Gbaud and 155 Gbaud modulation rates, respectively. The performance of the two modulation configurations is also compared and discussed. This work demonstrates the feasibility of implementing 1.2 Tb/s OTN transponders with weakly coupled MCFs to achieve ultra-high-speed metro–regional transmission, presenting a promising solution for next-generation inter-city data center interconnections.

Cladding-Pumped Multicore Erbium-Doped Fiber Amplifier for Simultaneous C- and L-Band Amplification

High-power ytterbium-doped multicore fibers

Self-sensing multicore fiber probe for interferometric measurement of lateral displacement and force

Stress Effects on Crosstalk and Skew in Bent Multicore Fibers: A Revisit to Effective Bending Radius

ABSTRACT Curvature sensing is a critical function of optical fiber sensors for applications in structural monitoring, biomedicine, and photonic integration, where multicore fibers (MCFs) provide distinctive opportunities. This work exploits intrinsic inter‐core coupling in randomly‐coupled MCFs (RC‐MCFs) to realise ultra‐sensitive curvature sensing. A coupled‐mode theory establishes the relationship between structural parameters and inter‐core coupling. Numerical simulations reveal that bending‐induced propagation constant mismatches dynamically reconfigure inter‐core coupling, leading to optical path difference amplification. This mechanism enables curvature sensing in centimeter‐scale RC‐MCFs and differs fundamentally from cladding‐mode coupling in weakly coupled MCFs and supermode coupling in strongly coupled MCFs. Broadband spectral interrogation experiments reveal pitch‐dependent and wavelength‐dependent interference patterns. A record curvature sensitivity of −65 nm/m −1 is achieved in 4CF over the range of 1.6–2.8 m −1 , corresponding to sub‐millimeter bending radius resolution. Using a 16CF with a larger core pitch and a two‐layer structure, sensitivities up to −190 nm·m −1 are achieved over a narrower curvature range, demonstrating the extendability of inter‐core‐coupling‐based curvature sensing to other RC‐MCF structures. Multi‐directional bending experiments further demonstrate orientation‐dependent responses, indicating the potential of RC‐MCFs for vector curvature sensing, underscoring their potential for structural monitoring and advanced photonic integration.

Single-shot hyperspectral wavefront sensing is essential for applications like spatio-spectral coupling metrology in high-power laser or fast material dispersion imaging. Under broadband illumination, traditional wavefront sensors assume an achromatic wavefront, which makes them unsuitable. We introduce a hyperspectral wavefront sensing scheme based on the Hartmann wavefront sensing principles, employing a multicore fiber as a Hartmann mask to overcome these limitations. Our system leverages the angular memory effect and limited spectral correlation width of the multicore fiber, encoding wavefront gradients into displacements and the spectral information into uncorrelated speckle patterns. This method retains the simplicity, compactness, and single-shot capability of conventional wavefront sensors, with only a slight increase in computational complexity. It also allows a tunable trade-off between spatial and spectral resolution. We demonstrate its efficacy for recording the hyperspectral wavefront cube from single-pulse acquisitions at the Apollon multi-petawatt laser facility, and for performing multispectral microscopic imaging of dispersive phase objects.

Intensity-modulated rotation angle sensor based on multi-core fibers

Rayleigh scattering-based distributed sensing in multicore optical fibers for shape reconstruction in multiplanar disturbance

Design of a four channel green-wavelength multiplexer based on multicore polymer optical fiber

Fading suppression method based on multi-core optical fiber bidirectional sensing loop for Φ-OTDR system

A multicore fiber platform for distributed temperature sensing enhanced by machine learning algorithms

We report a novel and highly sensitive torsion sensor that integrates a multicore fiber (MCF) within a Sagnac interferometer so that the same MCF segment serves as both the reflective element and the sensing head of a fiber-ring laser. The laser architecture incorporates a distributed reflector implemented as a ZnGa₂O₄-nanocrystal-doped fiber section, which enhances overall system performance. The device exhibits high torsional responsivity over 0°–150°, with distinct behavior across sub-ranges: in 0°–50°, phase analysis yields a sensitivity of 0.08 rad/° with R² = 0.991; in 88°–150°, amplitude analysis—under the ring-laser configuration—shows an improvement in sensitivity from 0.2 to 0.5 dBm/° (R² = 0.995). In the intermediate interval (50°–88°) neither phase nor power varies monotonically, so a function-fitting neural network was employed to bridge this gap, achieving a root-mean-square error of 0.06°. The system attains an angular resolution of 0.8°, ensuring accurate torsion estimation across the entire measurement span.