In Wireless Mesh Networks (WMNs) the meshing architecture, consisting of a grid of mesh routers, provides connectivity services to different mesh client nodes. The good performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical area to achieve network connectivity and stability. Thus, finding optimal or nearoptimal mesh router nodes placement is crucial to such networks. In this work we propose and evaluate Genetic Algorithms (GAs) for near-optimally solving the problem. In our approach we seek a two-fold optimization, namely, the maximization of the size of the giant component in the network and that of user coverage. The size of the giant component is considered here as a criteria for measuring network connectivity. GAs explore the solution space by means of a population of individuals, which are evaluated, selected, crossed and mutated to reproduce new individuals of better quality. The fitness of individuals is measured with respect to network connectivity and user coverage being the former a primary objective and the later a secondary one. Several genetic operators have been considered in implementing GAs in order to find the configuration that works best for the problem. We have experimentally evaluated the proposed GAs using a benchmark of generated instances varying from small to large size. In order to evaluate the quality of achieved solutions for different possible client distributions, instances have been generated using different distributions of mesh clients (Uniform, Normal, Exponential and Weibull). The experimental results showed the efficiency of the GAs for computing high quality solutions of mesh router nodes placement in WMNs.

Abstract

We present, to the best of our knowledge, the first known detailed analysis and fair comparison of complexity of a 56 Gb/s multi-band carrierless amplitude and phase (CAP) and discrete multi-tone (DMT) over 80 km dispersion compensation fiber-free single-mode fiber links based on intensity modulation and direct detection for data center interconnects. We show that the matched finite impulse response filters and inverse fast Fourier transform (IFFT)/FFT take the majority of the complexity of the multi-band CAP and DMT, respectively. The choice of the multi-band CAP sub-band count and the DMT IFFT/FFT size makes significant impact on the system complexity or performance, and trade-off must be considered.

Mesh router nodes placement is a central problem in Wireless Mesh Networks (WMNs). An efficient placement of mesh router nodes is indispensable for achieving network performance in terms of both network connectivity and user coverage. Unfortunately the problem is computationally hard to solve to optimality even for small deployment areas and a small number of mesh router nodes. As WMNs are becoming an important networking infrastructure for providing cost-efficient broadband wireless connectivity, researchers are paying attention to the resolution of the mesh router placement problem through heuristic approaches in order to achieve near optimal, yet high quality solutions in reasonable time. In this work we propose and evaluate a Simulated Annealing (SA) approach to placement of mesh router nodes in WMNs. The optimization model uses two maximization objectives, namely, the size of the giant component in the network and user coverage. Both objectives are important to deployment of WMNs; the former is crucial to

Based on a comprehensive theoretical optical orthogonal frequency division multiplexing (OOFDM) system model rigorously verified by comparing numerical results with end-to-end real-time experimental measurements at 11.25Gb/s, detailed explorations are undertaken, for the first time, of the impacts of various physical factors on the OOFDM system performance over directly modulated DFB laser (DML)-based, intensity modulation and direct detection (IMDD), single-mode fibre (SMF) systems without in-line optical amplification and chromatic dispersion compensation. It is shown that the low extinction ratio (ER) of the DML modulated OOFDM signal is the predominant factor limiting the maximum achievable optical power budget, and the subcarrier intermixing effect associated with square-law photon detection in the receiver reduces the optical power budget by at least 1dB. Results also indicate that, immediately after the DML in the transmitter, the insertion of a 0.02nm bandwidth optical Gaussian bandpass filter with a 0.01nm wavelength offset with respect to the optical carrier wavelength can enhance the OOFDM signal ER by approximately 1.24dB, thus resulting in a 7dB optical power budget improvement at a total channel BER of 1 × 10(-3).

Abstract:The first blind nonlinear equalizer using affinity propagation (AP) clustering is experimentally demonstrated for single-channel and WDM CO-OFDM. AP outperforms fuzzylogic c-means clustering and digital-back propagation for both QPSK and 16-QAM formats. IntroductionEndeavors to surpass the Kerr nonlinearity limit in long-haul coherent communications have been attempted in digital domain by Volterra-based nonlinear equalization (V-NLE) [1] and digital-back propagation (DBP) [2]. V-NLE and DBP however, can only tackle deterministic nonlinearities such as self-phase modulation, without considering the stochastic nonlinear interaction from polarization-mode dispersion and amplified spontaneous emission noise caused by cascaded optical amplifiers. On the other hand, full-step DBP (FS-DBP) is very complex and V-NLE shows marginal performance enhancement accompanied with a significant amount of floating-point operations, thus forbidding their implementation in real-time communications. Moreover, albeit the Kerr-induced nonlinear process is deterministic, in multicarrier schemes like coherent optical OFDM (CO-OFDM) the resulting nonlinear interaction between subcarriers becomes very complicated appearing random due to its high peak-toaverage power ratio (PAPR) [3]. Recently, unsupervised and supervised machine learning such as K-means clustering [4] and artificial neural network classification [3] have been introduced in optical communications to combat stochastic source of noises, performing blind and non-blind NLE, respectively. Here, we demonstrate the first blind-NLE using affinity propagation (AP) clustering for single-channel and WDM CO-OFDM. AP outperforms fuzzy-logic C-means (FL) and K-means clustering, as well as digital deterministic solutions such as FS-DBP and V-NLE, by reducing a significant amount of stochastic nonlinear noise on middle subcarriers.

Nonlinear distortion in few-mode fibers for intermediate coupling is studied for the first time. Coupling strengths beyond-20 dB/100m give suppression of nonlinear distortion below the isolated mode without mode coupling.

Wireless Mesh Networks (WMNs) are an important networking paradigm that offer cost effective Internet connectivity. The performance and operability of WMNs depend, among other factors, on the placement of network nodes in the area. Among the most important objectives in designing a WMN is the formation of a mesh backbone to achieve high user coverage. Given a number of router nodes to deploy, a deployment area and positions of client nodes in the area, an optimization problem can be formulated aiming to find the placement of router nodes so as to maximize network connectivity and user coverage. This optimization problem belongs to facility location problems, which are computationally hard to solve to optimality. In this paper we present the implementation and evaluation of Tabu Search (TS) for the problem of mesh router node placement in WMNs. The experimental evaluation showed the efficiency of TS in solving a benchmark of instances.