Polyperiodic and widely linear array filtering for cyclostationnary and non circular signals

Since several decades, the optimal array filtering problem assumes stationary signals and consists mainly to implement a linea r and time invariant complex filter whose output optimizes a second order criterion under some possible constraints. Limiting th e analysis to the exploitation of the second order statistics of the data, this approach, although optimal for stationary signals , becomes sub-optimal for non stationary signals for which the optimal complex filters become time variant, and more precisely polyperiodic for (quasi)-cyclostationary signals, and, under some non circularity conditions, widely linear. Considering the optima l estimation of a useful signal by using a polyperiodic and potentially widely linear filtering of the data, this paper aims at presenting a synthesis of the main results available about the definition, the performance, the implementations and the applications of suc h spatio-temporal filters in (quasi)-cyclostationary and/or non circular context, omnipresent in radiocommunications .Depuis plusieurs décennies, la problématique classique du filtrage d'antenne optimal considère des signaux stationnaires et consiste à implanter un filtre complexe linéaire et invariant dans le temps dont la sortie optimise un critère à l'ordre deux sous d'éventuelles contraintes. En restreignant l'analyse à l'exploitation des statistiques d'ordre deux des observations, l'approche précédente, bien qu'optimale pour des signaux stationnaires, devient sous-optimale pour des signaux non stationnaires pour lesquels les filtres complexes optimaux deviennent variables dans le temps, et plus précisément polypériodiques pour des observations (quasi)-cyclostationnaires, et, sous certaines conditions de non circularité, linéaires au sens large. En se plaçant dans le contexte de l'estimation optimale d'un signal dit utile par filtrage polypériodique d'ordre fini et potentiellement linéaire au sens large des observations, cet article vise à présenter une synthèse des principaux résultats disponibles à ce jour quant à la définition, aux performances, à la mise en oeuvre et aux applications de tels filtres en environnement (quasi)-cyclostationnaire et/ou non circulaire, omniprésent en radiocommunications

Noncircularity exploitation in signal processing overview and application to radar

International audienceWith new generation of Active Digital Radar Antenna, there is a renewal of waveform generation and processing approaches, and new strategies can be explored to optimize waveform design and waveform analysis and to benefit of all potential waveform diversity. Among these strategies, building and exploitation of the Noncircularity of waveforms is a promising issue. Up to the middle of the nineties, most of the signals encountered in practice are assumed to be second order (SO) circular (or proper), with a zero second correlation function. However, in numerous operational contexts such as in radio communications, the observed signals are either SO noncircular (or improper) or jointly SO noncircular with a particular signal to estimate, to detect or to demodulate, with some information contained in the second correlation function of the signals. Exploitation of this information in the processing of SO noncircular signals may generate dramatic gain in performance with respect to conventional processing and opens new perspective in signal processing. The purpose of this paper is to present a short overview of the interest of taking into account the potential SO noncircularity of the signals in signal processing and to describe the potential interest of SO noncircular waveforms for radar applications

Noncircular Waveforms Exploitation for Radar Signal Processing : Survey and Study for Agile Radar Waveform

International audienceWith new generation of Active Digital Radar Antenna, there is a renewal of waveform generation and processing approaches, and new strategies can be explored to optimize waveform design and waveform analysis and to benefit of all potential waveform diversity. Among these strategies, building and exploitation of the Noncircularity of waveforms is a promising issue. Up to the middle of the nineties, most of the signals encountered in practice are assumed to be second order (SO) circular (or proper), with a zero second correlation function. However, in numerous operational contexts such as in radio communications, the observed signals are either SO noncircular (or improper) or jointly SO noncircular with a particular signal to estimate, to detect or to demodulate, with some information contained in the second correlation function of the signals. Exploitation of this information in the processing of SO noncircular signals may generate dramatic gain in performance with respect to conventional processing and opens new perspective in signal processing. The purpose of this paper is to present a short overview of the interest of taking into account the potential SO noncircularity of the signals in signal processing and to describe the potential interest of SO noncircular waveforms for radar applications

Bayesian Sequential Track Formation

This paper presents a theoretical framework for track building in multiple-target scenarios from the Bayesian point of view. It is assumed that the number of targets is fixed and known. We propose two optimal methods for building tracks sequentially. The first one uses the labelling of the current multitarget state estimate that minimizes the mean-square labeled optimal subpatternassignment error. This method requires knowledge of the posterior density of the vector-valued state. The second assigns the labeling that maximizes the probability that the current multi-targetstate estimate is optimally linked with the available tracks at the previous time step. In this case, we only require knowledge of the random finite-set posterior density without labels

Equalization of MIMO Channels in LTE-Advanced

LTE-Advanced is one of the most evolving and competing standards that target the high speed 4G wireless communications. In order to meet the target of this new cellular technology developed under auspices of the 3GPP standardization bodies, it is necessary to ensure that this technology is able to provide the headline requirements recommended for the terrestrial components of the IMT-Advanced radio interface for 4G broadband mobile communications. One of the key radio technologies that will enable LTE-Advanced to achieve the high data throughput rates is the use of MIMO antennas that play an important role as the conventional communications like using more bandwidths and higher modulation types are limited. Together with this are the downlink OFDMA and the uplink SC-FDMA techniques that are employed to improve the system architecture burdened with the data rates rising pretty well above what was previously in use. The combination of these technologies will help LTE-Advanced keep pace with other wireless technologies that may be competing to offer very high data rates and high level of mobility. But achieving the high data rate up to 1 Gbits/s in 4G mobile networks over wide frequency bandwidths and recovering the original information without being corrupted and downgraded has been a daunting task for engineers. Thus, this paper will briefly discuss the performances of MIMO equalization techniques such as MMSE, ZF and ZF-SIC equalizers in a Rayleigh multichannel fading.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Forecasting Network Traffic: A Survey and Tutorial with Open-Source Comparative Evaluation

This paper presents a review of the literature on network traffic prediction, while also serving as a tutorial to the topic. We examine works based on autoregressive moving average models, like ARMA, ARIMA and SARIMA, as well as works based on Artifical Neural Networks approaches, such as RNN, LSTM, GRU, and CNN. In all cases, we provide a complete and self-contained presentation of the mathematical foundations of each technique, which allows the reader to get a full understanding of the operation of the different proposed methods. Further, we perform numerical experiments based on real data sets, which allows comparing the various approaches directly in terms of fitting quality and computational costs. We make our code publicly available, so that readers can readily access a wide range of forecasting tools, and possibly use them as benchmarks for more advanced solutions

Resynthesis of Acoustic Scenes Combining Sound Source Separation and WaveField Synthesis Techniques

[ES] La Separacón de Fuentes ha sido un tema de intensa investigación en muchas aplicaciones de tratamiento de señaal, cubriendo desde el procesado de voz al análisis de im'agenes biomédicas. Aplicando estas técnicas a los sistemas de reproducci'on espacial de audio, se puede solucionar una limitaci ón importante en la resíntesis de escenas sonoras 3D: la necesidad de disponer de las se ñales individuales correspondientes a cada fuente. El sistema Wave-field Synthesis (WFS) puede sintetizar un campo acústico mediante arrays de altavoces, posicionando varias fuentes en el espacio. Sin embargo, conseguir las señales de cada fuente de forma independiente es normalmente un problema. En este trabajo se propone la utilización de distintas técnicas de separaci'on de fuentes sonoras para obtener distintas pistas a partir de grabaciones mono o estéreo. Varios métodos de separación han sido implementados y comprobados, siendo uno de ellos desarrollado por el autor. Aunque los algoritmos existentes están lejos de conseguir una alta calidad, se han realizado tests subjetivos que demuestran cómo no es necesario obtener una separación óptima para conseguir resultados aceptables en la reproducción de escenas 3D[EN] Source Separation has been a subject of intense research in many signal processing applications, ranging from speech processing to medical image analysis. Applied to spatial audio systems, it can be used to overcome one fundamental limitation in 3D scene resynthesis: the need of having the independent signals for each source available. Wave-field Synthesis is a spatial sound reproduction system that can synthesize an acoustic field by means of loudspeaker arrays and it is also capable of positioning several sources in space. However, the individual signals corresponding to these sources must be available and this is often a difficult problem. In this work, we propose to use Sound Source Separation techniques in order to obtain different tracks from stereo and mono mixtures. Some separation methods have been implemented and tested, having been one of them developed by the author. Although existing algorithms are far from getting hi-fi quality, subjective tests show how it is not necessary an optimum separation for getting acceptable results in 3D scene reproductionCobos Serrano, M. (2007). Resynthesis of Acoustic Scenes Combining Sound Source Separation and WaveField Synthesis Techniques. http://hdl.handle.net/10251/12515Archivo delegad

Strategies for Devising Automatic Signal Recognition Algorithms in a Shared Radio Environment

In an increasingly congested and complex radio environment interference is to be expected, which poses problems for Automatic Signal Recognition (ASR) systems. This thesis explores strategies for improving ASR performance in the presence of interference. The thesis breaks the overall research question down into a number of subquestions and explores each of these in turn. A Phase-symmetric Cross Recurrence Plot is developed and used to show how a radio signal can be manipulated to separate information about the modulation from the information being carried. The Logarithmic Cyclic frequency Domain Profile is introduced to illustrate how a logarithmic representation can be used for analysing mixtures of signals with very different cyclic frequencies. After defining a canonical ASR system architecture, the concepts of an Ideal Feature and Interference Selectivity are introduced and applied to typical features used in ASR processing. Finally it is shown how these algorithmic developments can be combined in a Bayesian chain implementation that can accommodate a wide variety of feature extraction algorithms. It is concluded that future ASR systems will require features that can handle a wide range of signal types with much higher levels of interference selectivity if they are to achieve acceptable performance in shared spectrum bands. Intelligent segmentation is shown to be a requirement for future ASR systems unless features can be developed that have near ideal performance

Towards joint communication and sensing (Chapter 4)

Localization of user equipment (UE) in mobile communication networks has been supported from the early stages of 3rd generation partnership project (3GPP). With 5th Generation (5G) and its target use cases, localization is increasingly gaining importance. Integrated sensing and localization in 6th Generation (6G) networks promise the introduction of more efficient networks and compelling applications to be developed