Performance analysis of long band passive optical network using amplifier spontaneous noise and fiber Bragg gratings

Long band (L-Band) passive optical networks (PONs) are attracting a lot of attention these days, thanks to rising capacity demands. Because of PONs requesting more and more channels, fault detection/monitoring is critical. Fault detection in the conventional band (C-Band) employing reflecting Fiber Bragg Gratings (FBGs) and a probe signal integrating an additional amplified spontaneous noise (ASEN) source has been frequently demonstrated. However, interference occurs when ASEN and transmitter signals are in the same wavelength band, and adding additional ASEN sources to the network raises the overall cost. So, in L-Band PONs, a cost-effective, low-complexity fault detection/monitoring system is required. Therefore, in this work, a fault detection/monitoring system for L-Band PON using C-Band ASEN from inline erbium doped fiber amplifier (EDFA) and dual purpose FBG, i.e. (1) ASEN reflection for fault monitoring and (2) dispersion compensation is proposed. A 4 × 10 Gbps L-Band PON is investigated over 40 km feeder fiber (FF) and 1 km drop fibers (DFs) that serve 32 optical network units (ONUs)/different input powers, dispersion values, and laser linewidths in terms of reflective power of FBGs, eye opening factor, and bit error rate (BER), respectively.

Analysis of optical networks in presence of nodes noise and crosstalk

Optical packet switching has gained lot of momentum in last decade due to the advantages of optical fiber over copper cables. Optical switching is beneficial in optical networks which form connections of links and switching nodes. In these high speed networks minimum delay and high throughput are two important parameters which are considered. To minimize network delay shortest path algorithm is used for route selections. In previous studies while choosing shortest path distance among various nodes is considered. In this work we have shown that it is necessary to consider both distance and number of hops while choosing path from source to destination to minimize power per bit used for the transmission.

Actively MEMS-Based Tunable Metamaterials for Advanced and Emerging Applications

In recent years, tunable metamaterials have attracted intensive research interest due to their outstanding characteristics, which are dependent on the geometrical dimensions rather than the material composition of the nanostructure. Among tuning approaches, micro-electro-mechanical systems (MEMS) is a well-known technology that mechanically reconfigures the metamaterial unit cells. In this study, the development of MEMS-based metamaterial is reviewed and analyzed based on several types of actuators, including electrothermal, electrostatic, electromagnetic, and stretching actuation mechanisms. The moveable displacement and driving power are the key factors in evaluating the performance of actuators. Therefore, a comparison of actuating methods is offered as a basic guideline for selecting micro-actuators integrated with metamaterial. Additionally, by exploiting electro-mechanical inputs, MEMS-based metamaterials make possible the manipulation of incident electromagnetic waves, including amplitude, frequency, phase, and the polarization state, which enables many implementations of potential applications in optics. In particular, two typical applications of MEMS-based tunable metamaterials are reviewed, i.e., logic operation and sensing. These integrations of MEMS with metamaterial provide a novel route for the enhancement of conventional optical devices and exhibit great potentials in innovative applications, such as intelligent optical networks, invisibility cloaks, photonic signal processing, and so on.

Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario

Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.

Effect of optical pulse shaping and adaptive equalization on the performance of 100G DP-QPSK WDM system

Dual polarization quadrature phase shifting keying (DP-QPSK) modulation format along with coherent receiver helps in increasing the data carrying capability of existing optical networks without any major change in existing transmission infrastructure. The various linear and nonlinear fiber effects, frequency and phase errors are corrected in electrical domain at the receiver end with digital back propagation algorithms (DBP) instead of in-line compensation. In such a case the selection of optimum values of system parameters make the task easier for DBP algorithms. This paper highlights the importance of finding optimum operating point of continuous modulus algorithm (CMA) for better adaptive equalization (AE). The paper also discusses the optical pulse shaping using Gaussian optical band-pass filter to improve the spectral characteristics of DP-QPSK signal.

Fault Tolerance and Noise Immunity in Freespace Diffractive Optical Neural Networks

Free-space diffractive optical networks are a class of trainable optical media that are currently being explored as a novel hardware platform for neural engines. The training phase of such systems is usually performed in a computer and the learned weights are then transferred onto optical hardware ("ex-situ training"). Although this process of weight transfer has many practical advantages, it is often accompanied by performance degrading faults in the fabricated hardware. Being analog systems, these engines are also subject to performance degradation due to noises in the inputs and during optoelectronic conversion. Considering diffractive optical networks (DON) trained for image classification tasks on standard datasets, we numerically study the performance degradation arising out of weight faults and injected noises and methods to ameliorate these effects. Training regimens based on intentional fault and noise injection during the training phase are only found marginally successful at imparting fault tolerance or noise immunity. We propose an alternative training regimen using gradient based regularization terms in the training objective that are found to impart some degree of fault tolerance and noise immunity in comparison to injection based training regimen.

Brown-Field Migration Aware Routing and Spectrum Assignment in Backbone Optical Networks

With the development of optical networks technology, broad attention has been paid to flexible grid technology in optical networks due to its ability to carry large-capacity information as well as provide flexible and fine-grained services through on-demand spectrum resource allocation. However, a one-time green-field deployment of a flexible grid network may not be practical. The transition technology called the fixed/flex-grid optical networks is more applicable and highly pragmatic. In such network, many nodes would likely be upgraded from a fixed-grid to flex-grid. In fact, dynamic service provisioning during the process of a node upgrade in fixed/flex-grid optical networks have become a challenge because the service connection can be easily interrupted, which leads to considerable data loss because of node upgrade. To overcome this challenge, we propose a brown-field migration aware routing and spectrum assignment (BMA-RSA) algorithm in fixed/flex-grid optical networks. The aim is to construct a probabilistic migration label (PML) model. The well-designed label setting of PML can balance the relationship between distance and node-upgrade probability. Dynamic service provisioning operations are undertaken based on the PML model to achieve a migration-aware dynamic connection before network migration occurs. We also evaluate the performance of different service provisioning strategies under different traffic models. The simulation results show that the BMA-RSA algorithm can achieve: (1) the tradeoff between distance and node upgrade probability during the process of service provisioning; (2) lower service interruption compared with the traditional non-migration aware K-shortest-path routing and spectrum assignment algorithm.

Constructions of Optimal Optical Orthogonal Codes with Weights Set 5,7 via Cyclic Packing

Double-weight optical orthogonal codes are variable-weight optical orthogonal codes (OOCs), which have been widely applied in optical networks and systems. Some works have been devoted to optimal n , W , 1 , Q -OOCs with max w : w ∈ W ≤ 6 . So far, there is no explicit construction of optimal n , W , 1 , Q -OOCs with W = 5,7 . It is known that heavier-weight codewords have better code performance than lighter-weight codewords. So, in this paper, we use cyclic packing to construct two infinite classes of optimal OOCs with weights set 5,7 explicitly, for any prime p ≡ 3 mod 4 and p ≥ 7 . In addition, for 1 ≤ t < p − 1 / 2 , by breaking t blocks of size 7 into 3 of 31 p , 5,7 , 1 , 1 / 2 , 1 / 2 -OOCs and 41 p , 5,7 , 1 , 2 / 3 , 1 / 3 -OOCs, we obtain new infinite classes of optimal 31 p , 3,5,7 , 1 , 7 t / p − 1 + 6 t , p − 1 / 2 p − 1 + 6 t , p − 1 − 2 t / 2 p − 1 + 6 t -OOCs and 41 p , 3,5,7 , 1 , 14 t / 3 p − 1 + 4 t , 2 p − 1 / 3 p − 1 + 4 t , p − 1 − 2 t / 3 p − 1 + 4 t -OOCs, respectively.