Bidirectional Wavelength Reconfigurable Module Based on Tunable Fiber Bragg Grating and Remote Pump Amplifier

Abstract

This article presents a novel bidirectional wavelength reconfigurable optical network utilizing a remotely pumped erbium-doped fiber amplifier and tunable fiber Bragg gratings. The system is experimentally demonstrated at a 10-Gb/s per channel over 20-km fiber span that verifies the metro-network range system performance. The achieved power penalty is less than 1 dB when compared to the back-to-back transmission link. An example of practical application where the proposed module is used as an add/drop multiplexer and a remote node in the bidirectional wavelength division multiplexing passive optical network system is described.     

Bit-error-rate analysis for a 100-Gbit/s nonlinear optical loop mirror demultiplexer employing soliton control and signal pulses

On the basis of a previously derived mathematical model, the power penalty associated with a nonlinear optical loop mirror (NOLM) demultiplexer was calculated, with timing jitter noise, bit-to-bit cross talk, and channel cross talk taken into consideration. Simulation results show that a 3-dBm improvement in the receiver sensitivity at a bit error rate of 10(-9) can be achieved by choice of the appropriate walk-off time between the control and the signal pulses within the NOLM demultiplexer.     

Comparative study of classifiers to mitigate intersymbol interference in diffuse indoor optical wireless communication links

The maximum data rate that can be achieved in diffuse indoor optical wireless communication (OWC) is limited due to the effect of intersymbol interference (ISI). The adverse effect of ISI on the system performance can be minimised using a channel equaliser at the receiver. In this study, digital signal detection is formulated as a classification problem and hence a classifier is adopted at the receiver. The bit error performance of classifiers with non-linear decision boundary including a multilayer perceptron (MLP), a support vector machine (SVM), the radial basis function (RBF), and the Bayesian classifier is studied along with traditional equaliser and reported here. The MLP offers the best performance; however there is trade-off between the performance and complexity especially at highly diffuse channel.     

Simultaneous multiple volume (SMV) acquisition algorithm for real-time navigator gating

Navigator gating techniques can effectively reduce motion effects in MRI by accepting data only when the object is in a small range of positions at the cost of significantly prolonging scan time. A simultaneous multiple volume (SMV) algorithm is reported here that can substantially increase the scan efficiency while maintaining the effectiveness of motion suppression. This is achieved by acquiring different image volumes at different motion states. Initial experiments demonstrate that SMV can significantly increase the scan efficiency of navigator MRI.