Polarization mode dispersion

About: Polarization mode dispersion is a research topic. Over the lifetime, 5147 publications have been published within this topic receiving 80055 citations. The topic is also known as: PMD.

Quaternion approach to PMD and PDL phenomena in optical fiber systems

Abstract: In this paper, we introduce the concept of quaternions (which is a generalization of the complex numbers) and quaternion calculus and demonstrate how this theory may be used to simplify the treatment of polarization phenomena in optical fibers. We apply quaternion calculus to two examples: 1) the description of polarization-dependent loss (PDL) elements and concatenation of such and 2) the description of pulse dynamics and broadening in transmission lines with both polarization-mode dispersion (PMD) and PDL. Finally we present some novel results from the investigation of pulse broadening in a simple system comprising a PMD element, followed by a perfect polarizer.

Optical Performance Monitoring Using Artificial Neural Network Trained With Asynchronous Amplitude Histograms

Abstract: We propose an optical performance monitoring technique for simultaneous monitoring of optical signal-to-noise ratio (OSNR), chromatic dispersion (CD), and polarization-mode dispersion (PMD) using an artificial neural network trained with asynchronous amplitude histograms (AAHs). Simulations are conducted to demonstrate the technique for both 40-Gb/s return-to-zero differential quadrature phase-shift keying (RZ-DQPSK) and 40-Gb/s noneturn-to-zero 16 quadrature amplitude modulation (16-QAM) systems. The OSNR, CD, and PMD monitoring range and root-mean-square (rms) errors are 10-30 and 0.43 dB, 0-400 and 9.82 ps/nm, and 0-10 and 0.92 ps, respectively, for RZ-DQPSK systems. For 16-QAM system, the monitoring range and rms errors are 10-30 and 0.2 dB, 0-400 and 9.66 ps/nm, and 0-30 and 0.65 ps for OSNR, CD, and PMD, respectively. As the generation of AAH does not require any clock or timing recovery, the proposed technique can serve as a low-cost option to realize in-service multiparameter monitoring for the next-generation transparent optical networks.

Four-dimensional optical multiband-OFDM for beyond 1.4Tb/s serial optical transmission

Abstract: Systems and methods are disclosed to perform four-dimensional optical multiband OFDM communication by organizing an N-dimensional (ND) signal constellation points as a signal matrix; performing 2D-inverse FFT and 2D-FFT to perform modulation and demodulation, respectively; and applying both orthogonal polarizations in the OFDM communication to deal with chromatic dispersion, PMD and PDL effects, and multidimensional signal constellation to improve optical signal-to-noise ratio (OSNR) sensitivity.

Polarization-mode dispersion of installed recent vintage fiber as a parametric function of temperature

Abstract: We report the first polarization-mode dispersion measurement of installed 0.05-ps/km/sup 1/2/ fiber over 150-km span and 100-nm bandwidth. The apparent randomness of differential group delay (DGD) spectral components over time is removed when the DGD is considered as a function of temperature.

Polarization Demultiplexing for Stokes Vector Direct Detection

Abstract: The conventional intensity modulation with direct detection faces the capacity bottleneck beyond 100-Gb/s per wavelength, due to its 1-dimension (1-D) modulation and detection. To increase the spectral efficiency, there emerge a variety of direct detection subsystems based on the Stokes vector receiver (SV-R). The Stokes space contains the intensity information of three independent polarizations. Therefore, the SV-R enlarges the detection dimensions at receiver to 3. The SV-R can recover any 2-D or 3-D signal modulated in Stokes space. One of the most significant features of SV-R is the DSP-enabled polarization demultiplexing. Instead of a 2 × 2 Jones matrix, in Stokes space, a 3 × 3 rotation matrix (RM) characterizes the polarization variation during fiber transmission. Previously, we have demonstrated a training-assisted polarization demultiplexing algorithm, which uses three basis vectors in Stokes space to estimate the RM. In this paper, we propose a blind polarization demultiplexing using the signal distribution in Stokes space. Combined with the blind adaptive algorithm, the new method converts the two-stage polarization demultiplexing (RM estimation and channel equalization) to a single-stage blind 3 × 2 real-value multiple-input multiple-output equalization, which significantly simplify the DSP procedures. We experimentally demonstrate the SV-R based on either training or blind demultiplexing algorithms, and compare the performance between them.