Partially Ordered Statistics Demapping for Multi-Dimensional Modulation Formats

We propose a very low-complexity and high-performance algorithm for soft-demapping of multi-dimensional modulation formats. We assess its performance over the linear channel for four 8D formats, generated using binary arithmetics. This solution outperforms current algorithms in terms of complexity without loss in performances.Comment: Accepted in the Optical Fiber Communications Conference (OFC) 201

Time-Frequency Decomposition of an Ultrashort Pulse: Wavelet Decomposition

An efficient numerical algorithm is presented for the numerical modeling of the propagation of ultrashort pulses with arbitrary temporal and frequency characteristics through linear homogeneous dielectrics. The consequences of proper sampling of the spectral phase in pulse propagation and its influence on the efficiency of computation are discussed in detail. The numerical simulation presented here is capable of analyzing the pulse in the temporal-frequency domain. As an example, pulse propagation effects such as temporal and spectral shifts, pulse broadening effects, asymmetry and chirping in dispersive media are demonstrated for wavelet decomposition

Multibeam Antennas Array Pattern Synthesis Using a Variational Method

In this paper a new method is described for multibeam antennas synthesis where both the amplitude and phase of each radiating element is a design variable. The developed optimization method made possible to solve the synthesis problem and to answer all the constraints imposed by the radiation pattern. Two approaches for visualizing satellite antenna radiation patterns are presented. Gain-level contours drawn over a geographical map gives clearest qualitative information. A three-dimensional (3D) surface plot displays the qualitative shape of the radiation pattern more naturally. The simulations results have shown power, precision and speed of the variational method with respect to the constraints imposed on radiation pattern of the of multibeam antennas network

Neural Networks for Synthesis and Optimization of Antenna Arrays

This paper describes a usual application of back-propagation neural networks for synthesis and optimization of antenna array. The neural network is able to model and to optimize the antennas arrays, by acting on radioelectric or geometric parameters and by taking into account predetermined general criteria. The neural network allows not only establishing important analytical equations for the optimization step, but also a great flexibility between the system parameters in input and output. This step of optimization becomes then possible due to the explicit relation given by the neural network. According to different formulations of the synthesis problem such as acting on the feed law (amplitude and/or phase) and/or space position of the radiating sources, results on antennas arrays synthesis and optimization by neural networks are presented and discussed. However ANN is able to generate very fast the results of synthesis comparing to other approaches

Mining subjectively interesting attributed subgraphs

Community detection in graphs, data clustering, and local pattern mining are three mature fields of data mining and machine learning. In recent years, attributed subgraph mining is emerging as a new powerful data mining task in the intersection of these areas. Given a graph and a set of attributes for each vertex, attributed subgraph mining aims to find cohesive subgraphs for which (a subset of) the attribute values has exceptional values in some sense. While research on this task can borrow from the three abovementioned fields, the principled integration of graph and attribute data poses two challenges: the definition of a pattern language that is intuitive and lends itself to efficient search strategies, and the formalization of the interestingness of such patterns. We propose an integrated solution to both of these challenges. The proposed pattern language improves upon prior work in being both highly flexible and intuitive. We show how an effective and principled algorithm can enumerate patterns of this language. The proposed approach for quantifying interestingness of patterns of this language is rooted in information theory, and is able to account for prior knowledge on the data. Prior work typically quantifies interestingness based on the cohesion of the subgraph and for the exceptionality of its attributes separately, combining these in a parameterized trade-off. Instead, in our proposal this trade-off is implicitly handled in a principled, parameter-free manner. Extensive empirical results confirm the proposed pattern syntax is intuitive, and the interestingness measure aligns well with actual subjective interestingness

New scheme for PAPR reduction in FBMC-OQAM systems based on combining TR and deep clipping techniques

Filter bank multi-carrier with offset quadrature amplitude modulation (FBMC-OQAM) system is a very efficient multicarrier modulation technique for 5G, but it suffers as all multicarriers designs from large peak-to-average power ratio (PAPR). Tone reservation (TR) is a method designed to solve this problem by reserving several subcarriers called tones in the frequency domain to generate a cancellation signal in the time domain to eliminate high peaks. In this paper, we suggest a serial combination of tone reservation (TR) method with an enhanced version of clipping called deep clipping (DC) method (TR&DC) to enhance the peaks (PAPR) mitigation in FBMC-OQAM signal model without significantly impacting the quality of transmission. Numerical results and analysis show that the new TR&DC approach allows better overall performance and offers remarkable gain in term of PAPR mitigation than the TR method, with similar BER performance to TR over additive white gaussian noise channel and Rapp HPA model