Related Experiment Video
Updated: Jul 3, 2026

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
Published on: March 20, 2017
Joint channel coding and fiber nonlinearity compensation with adaptive perturbation estimation in coherent optical
None:
A joint channel coding and fiber nonlinearity compensation scheme based on adaptive perturbation estimation is proposed for coherent optical transmission systems. The proposed PB-JCNC framework combines perturbation-based nonlinear modeling with iterative soft-information exchange from the forward error correction (FEC) decoder, enabling accurate estimation of nonlinear distortion without requiring precise knowledge of transmission link parameters. Simulation and experimental results demonstrate the effectiveness of the proposed method for both PDM-16QAM and PDM-64QAM signals. For 400 km PDM-64QAM transmission, a pre-FEC Q-factor improvement of up to 2.03 dB (simulation) and 1.46 dB (experiment) is achieved, along with a post-FEC launch power tolerance gain of up to 0.38 dB. For 1000 km PDM-16QAM transmission, consistent performance improvements are also observed. The results indicate that the PB-JCNC highlights the critical role of soft-information reliability in iterative nonlinear compensation.
Related Concept Videos
Linear Approximation in Frequency Domain
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Linear Approximation in Time Domain
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...
Transmission Line Design Considerations
Propagation of Uncertainty from Systematic Error
Transmission-Line Differential Equations
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from the...
Propagation of Uncertainty from Random Error
