In this thesis work, Cyclic Root MUSIC method is integrated with spatial smoothing and interpolation techniques to estimate the direction of arrivals of coherent,cyclostationary signals received via a Uniform Circular Array (UCA). Cyclic Root MUSIC and Conventional Root MUSIC algorithms are compared for various signal scenarios by computer simulations. A cyclostationary process is a random process with probabilistic parameters, such as the autocorrelation function, that vary periodically with time. Most of the man-made communication signals exhibit cyclostationarity due to the periodicity arising from their carrier frequencies, chip rates, baud rates, etc. Cyclic Root MUSIC algorithm exploits the cyclostationarity properties of signals to achieve signal selective direction of arrival estimation. Spatial smoothing is presented to overcome the coherent signals problem in a multipath propagation environment. Forward spatial smoothing and forward backward spatial smoothing techniques are investigated. Interpolation method is presented to cope with the restrictions of spatial smoothing on array structure. Although the array structure that is considered in this thesis (Uniform Circular Array), is not suitable for applying spatial smoothing directly, using interpolation method makes it possible. Performance of Cyclic Root MUSIC and Conventional Root MUSIC algorithms are compared under variation of various factors by computer simulations. Effects of signal type on the performance of the algorithms are observed by using different signal scenarios.

Au cours des vingt dernières années, le débit croissant des communications radiofréquences a imposé la mise en œuvre de techniques d'égalisation de plus en plus complexes. Pour résoudre ce problème, les modulations multi-porteuses ont été massivement employées dans les standards de communications à très haut débit. Un exemple caractéristique de la démocratisation de ces formes d'ondes est l'utilisation de l'OFDM (Orthogonal Frequency Division Multiplexing) sur le lien descendant des réseaux 4G. Toutefois, pour les futurs réseaux 5G, l'émergence prévue des communications M2M (Machine-to-Machine) impose aux formes d'ondes une grande tolérance aux asynchronismes au sein de ces réseaux et ne permet pas l'emploi de l'OFDM qui nécessite une synchronisation stricte en temps et en fréquence. Egalement, l'utilisation efficace du spectre par les techniques de la radio cognitive est incompatible avec l'OFDM en raison de la mauvaise localisation en fréquence de cette forme d'onde.Dans ce contexte, la forme d'onde FBMC-OQAM (Filter Bank Multi-Carrier - Offset Quadrature Amplitude Modulation) est apparue comme une solution potentielle à ces problèmes. Toutefois, l'égalisation des signaux FBMC-OQAM en canal sélectif en fréquence et/ou canal MIMO (Multiple Input Multiple Output) est rendue difficile par la subsistance d'interférences entre les sous-porteuses du schéma FBMC-OQAM. Cette thèse étudie donc l'égalisation de ces liaisons. L'étude de récepteurs WL (Widely Linear) qui permettent la suppression d'interférences, sans diversité d'antenne en réception, au sein des réseaux utilisant des signaux noncirculaires au second ordre (e.g. signaux ASK, GMSK, OQAM) est privilégiée. Cette technique nommée SAIC (Single Antenna Interference Cancellation) et utilisée dans les réseaux GSM pour la suppression d'interférences co-canal est envisagée pour une extension à la suppression des interférences entre porteuses des formes d'ondes FBMC-OQAM. La technologie SAIC, qui a été étendue pour plusieurs antennes en réception (MAIC - Multiple Antenna Interference Cancellation) a l'avantage de sa faible complexité et ne génère pas de propagation d'erreur à faible SNR contrairement aux solutions de suppression successive d'interférences. Une approche progressive est adoptée, depuis l'élaboration du SAIC pour la suppression d'interférences co-canal où nous démontrons l'importance de considérer le caractère cyclostationnaire des signaux OQAM. Basée sur cette constatation, une nouvelle structure de réception utilisant un filtre WL-FRESH (FREquency-SHift) est proposée et ses meilleures performances comparé au récepteur WL standard sont présentées analytiquement et par simulations numériques. L'extension du SAIC pour la suppression d'une interférence décalée en fréquence est ensuite menée et différentes structures de réception sont proposées et analysées en détail. L'aptitude des traitements SAIC utilisant des filtres WL-FRESH à supprimer 2 interférences décalées en fréquence est présentée. Dans le contexte des signaux FBMC-OQAM qui utilisent généralement le filtre de mise en forme PHYDYAS, chaque sous-porteuse est polluée par ses deux sous-porteuses adjacentes. Cependant, pour évaluer les traitements SAIC sans devoir prendre en compte la contribution des sous-porteuses voisines à ces sous-porteuses adjacentes, un filtre doit précéder le traitement de réception. Pour cette raison, l'analyse de l'impact d'un filtre de réception sur les performances des traitements SAIC proposés est effectuée et les conditions sur la bande passante du filtre nécessaires pour justifier l'intérêt d'un traitement SAIC par filtrage WL sont présentées. Dans un dernier temps, une approche alternative d'égalisation des signaux FBMC-OQAM est présentée. Elle consiste à démoduler conjointement les sous-porteuses interférentes après filtrage. Cette technique est abordée dans le contexte de liaisons MIMO Alamouti FBMC-OQAM. / During the last two decades, the increase of wireless communications throughput has necessitated more and more complex equalization techniques. To solve this issue, multicarrier modulations have been massively adopted in high data rates wireless communications standards. A typical example of the wide use of these waveforms is the adoption of OFDM (Orthogonal Frequency Division Multiplexing) for the downlink of 4G mobile networks. However, for next-generation 5G networks, the expected increase of M2M (Machine-to-Machine) communications forbids the use of OFDM because of the tight time and frequency synchronization constraints imposed by this waveform. Additionally, efficient spectrum occupation through cognitive radio strategies are incompatible with the poor spectral localization of OFDM. In this context, FBMC-OQAM (Filter Bank Multi-Carrier - Offset Quadrature Amplitude Modulation) waveforms appeared as a potential solution to these issues. However, equalization of FBMC-OQAM in frequency selective channels and/or MIMO (Multiple Input Multiple Output) channels is not straightforward because of residual intrinsic interferences between FBMC-OQAM subcarriers. Thus, this thesis considers equalization techniques for these links. In particular, the study of WL (Widely Linear) receivers allowing the mitigation of interferences, with only a single antenna, among networks using second-order noncircular waveforms (e.g. ASK, GMSK, OQAM signals) is privileged. This work studied this technique, named SAIC (Single Antenna Interference Cancellation) and applied for the suppression of co-channel interferences in GSM networks in order to adapt it for the cancellation of FBMC-OQAM intercarrier interferences. SAIC, which was further extended to multiple receive antennas (MAIC - Multiple Antenna Interference Cancellation) benefits from its low complexity and does not generate error propagation at low SNR contrary to successive interference cancellation based solutions. A progressive approach is adopted, from SAIC/MAIC for the suppression of co-channel interferences where we emphasize the importance of considering the cyclostationary nature of OQAM communication signals. Based on this, the proposal of a new WL-FRESH (FREquency-SHift) filter based receiver for OQAM-like signals is made and its performance is characterized analytically and by numerical simulations asserting its superior performance with respect to the standard WL receiver. The extension of SAIC/MAIC for the mitigation of a frequency-shifted interference is then considered and reception structures are proposed and analyzed in detail. The ability of WL-FRESH filter based SAIC receivers to perform the suppression of multiple frequency-shifted interferences is assessed. In the context of FBMC-OQAM signals which frequently utilize the PHYDYAS pulse-shaping prototype filter, each subcarrier is polluted only by its adjacent subcarriers. However, to evaluate SAIC processing without having to consider neighboring subcarriers of the adjacent ones, a filtering operation prior to the SAIC processing is needed. For this reason, the impact of a reception filter on the performance gain provided by the SAIC processing was conducted and conditions on the filter bandwidth have been established which governs the potential performance gain of a WL filter based processing for SAIC of frequency-shifted interferences.In a last step, an alternative equalization approach for FBMC-OQAM is investigated. This proposed technique consists in the per-subcarrier joint demodulation of the subcarrier of interest and its interfering adjacent ones after a filtering step. This proposal is considered in the context of MIMO Alamouti FBMC-OQAM links.

The tremendous ongoing growth of wireless digital communications has raised spectrum shortage and security issues. In particular, the need for new spectrum is the main obstacle in continuing this growth. Recent studies on radio spectrum usage have shown that pre-allocation of spectrum bands to specific wireless communication applications leads to poor utilization of those allocated bands. Therefore, research into new techniques for efficient spectrum utilization is being aggressively pursued by academia, industry, and government. Such research efforts have given birth to two concepts: Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) network. CR is believed to be the key enabling technology for DSA network implementation. CR based DSA (cDSA) networks utilizes white spectrum for its operational frequency bands. White spectrum is the set of frequency bands which are unoccupied temporarily by the users having first rights to the spectrum (called primary users). The main goal of cDSA networks is to access of white spectrum. For proper access, CR nodes must identify the right cDSA network and the absence of primary users before initiating radio transmission. To solve the cDSA network access problem, methods are proposed to design unique second-order cyclic features using Orthogonal Frequency Division Multiplexing (OFDM) pilots. By generating distinct OFDM pilot patterns and measuring spectral correlation characteristics of the cyclostationary OFDM signal, CR nodes can detect and uniquely identify cDSA networks. For this purpose, the second-order cyclic features of OFDM pilots are investigated analytically and through computer simulation. Based on analysis results, a general formula for estimating the dominant cycle frequencies is developed. This general formula is used extensively in cDSA network identification and OFDM signal detection, as well as pilot pattern estimation. CR spectrum awareness capability can be enhanced when it can classify the modulation type of incoming signals at low and varying signal-to-noise ratio. Signal classification allows CR to select a suitable demodulation process at the receiver and to establish a communication link. For this purpose, a threshold-based technique is proposed which utilizes cycle-frequency domain profile for signal detection and feature extraction. Hidden Markov Models (HMMs) are proposed for the signal classifier. The spectrum awareness capability of CR can be undermined by spoofing radio nodes. Automatic identification of malicious or malfunctioning radio signal transmitters is a major concern for CR information assurance. To minimize the threat from spoofing radio devices, radio signal fingerprinting using second-order cyclic features is proposed as an approach for Specific Emitter Identification (SEI). The feasibility of this approach is demonstrated through the identification of IEEE 802.11a/g OFDM signals from different Wireless Local Area Network (WLAN) card manufactures using HMMs. / Ph. D.

Dans le cadre de l’analyse de signaux mécaniques ou biomécaniques les outils d’aide à la décision reposent sur des hypothèses statistiques fortes: loi de probabilité normale, stationnarité des variables, variables centrées, variables indépendantes,…Or ces hypothèses sont parfois non vérifiées et engendrent des décisions erronées. Ce travail a pour objectif de proposer des méthodes qui font abstractions de certaines hypothèses et notamment de la stationnarité et de la gaussiannité des variables aléatoires. Dans cette thèse, nous avons revisité certaines méthodes de ré échantillonnages statistiques et de bootstrap et développé d’autres en incluant la cyclostationnarité des signaux. Ensuite, nous avons appliqué ces méthodes pour l’analyse de signaux biomécaniques provenant de coureurs expérimentés et d’une population de personnes âgées. Les résultats obtenus ont permis de mettre en évidence des changements significatifs dans le contenu fréquentiel du second ordre des signaux étudiés. Ces changements ont été des indicateurs très pertinents pour la description et la caractérisation de la fatigue d’un coureur professionnel, d’une part, et pour la compréhension du mécanisme complexe de la marche à pied simple et avec tâche cognitive chez les personnes âgées d’autre part / In mechanical and biomechanical signal analysis field, the decision support tools are based on strong statistical assumptions such as: normality, stationarity of variables, independence... However, these assumptions are very often unverified, consequently, wrong decisions could be taken. This work aims to propose new methods that make abstractions of such assumptions, including the stationarity and gaussianity of variables. In this thesis, we revisited some statistical resampling methods and developed new bootstrap approaches with including the cyclostationary nature of signals. Next, we applied these methods to the analysis of biomechanical signals from experienced runners and a population of elderly people. The obtained results allowed us to demonstrate significant changes in the second order frequency content of the signals under study. These changes were very relevant indicators for the description and characterization of the fatigue of a high level professional runner. Moreover, these changes helped us to understand the mechanism of normal walking and under a cognitive task condition (double task walking) in elderly

Cette thèse est une contribution à l’amélioration des observations pour les radiotélescopes à réseaux phasés en présence d’interférences. L’originalité de cette thèse repose sur l’utilisation de la séparation spatiale entre les sources cosmiques et les brouilleurs issus des télécommunications en se basant sur la cyclostationnarité de ces derniers. Cette thèse s’inscrit dans le cadre du projet européen SKADS pour l’amélioration des techniques de suppression d’interférences en radioastronomie pour les futurs instruments d’observations.Nous avons proposé trois techniques de traitement d’interférences : la détection,l’estimation et la soustraction, et le filtrage spatial. Les performances des techniques proposées ont été évaluées à travers des simulations sur des données synthétiqueset/ou réelles, et comparées aux techniques existantes. / This thesis is a contribution to observation improvements for phased array radiotelescopes, in the presence of radio frequency interferers (RFIs). The originality ofthe study is the use of the cyclostationarity property, in order to improve the spatial separation between cosmic sources and telecommunication signals. This thesis is part of the European SKADS project, which aims to improve RFI mitigation techniques for future instruments in radio astronomy.We have proposed three spatial processing techniques: detection, estimation and subtraction and spatial filtering. The performance of the techniques presented have been evaluated through simulations on synthetic and/or real data, and compared to existing approaches.

Being one of the fastest growing fields of engineering, wireless has gained the attention of researchers and commercial businesses all over the world. Extensive research is underway to improve the performance of existing systems and to introduce cutting edge wireless technologies that can make high speed wireless communications possible. The first part of this dissertation deals with discrete channel models that are used for simulating error traces produced by wireless channels. Most of the time, wireless channels have memory and we rely on discrete time Markov models to simulate them. The primary advantage of using these models is rapid experimentation and prototyping. Efficient estimation of the parameters of a Markov model (including its number of states) is important to reproducing and/or forecasting channel statistics accurately. Although the parameter estimation of Markov processes has been studied extensively, its order estimation problem has been addressed only recently. In this report, we investigate the existing order estimation techniques for Markov chains and hidden Markov models. Performance comparison with semi-hidden Markov models is also discussed. Error source modeling in slow and fast fading conditions is also considered in great detail. Cognitive Radio is an emerging technology in wireless communications that can improve the utilization of radio spectrum by incorporating some intelligence in its design. It can adapt with the environment and can change its particular transmission or reception parameters to execute its tasks without interfering with the licensed users. One problem that CR network usually faces is the difficulty in detecting and classifying its low power signal that is present in the environment. Most of the time traditional energy detection techniques fail to detect these signals because of their low SNRs. In the second part of this thesis, we address this problem by using higher order statistics of incoming signals and classifying them by using the pattern recognition capabilities of HMMs combined with cased-based learning approach. This dissertation also deals with dynamic spectrum allocation in cognitive radio using HMMs. CR networks that are capable of using frequency bands assigned to licensed users, apart from utilizing unlicensed bands such as UNII radio band or ISM band, are also called Licensed Band Cognitive Radios. In our novel work, the dynamic spectrum management or dynamic frequency allocation is performed by the help of HMM predictions. This work is based on the idea that if Markov models can accurately model spectrum usage patterns of different licensed users, then it should also correctly predict the spectrum holes and use these frequencies for its data transmission. Simulations have shown that HMMs prediction results are quite accurate and can help in avoiding CR interference with the primary licensed users and vice versa. At the same time, this helps in sending its data over these channels more reliably. / Ph. D.

Le problème de séparation aveugle de sources a but de retrouver un ensemble des sources signaux statistiquement indépendants à partir seulement d’un ensemble des observations du capteur. Ces observations peuvent être modélisées comme un mélanges linéaires instantané ou convolutifs de sources. Dans cette thèse, les sources signaux sont supposées être cyclostationnaire où leurs fréquences cycles peuvent être connues ou inconnu par avance. Premièrement, nous avons établi des relations entre le spectre, spectre de puissance d’un signal source et leurs composants, puis nous avons proposé deux nouveaux algorithmes pour estimer sa fréquences cycliques. Ensuite, pour la séparation aveugle de sources en mélanges instantanés, nous présentons quatre algorithmes basés sur diagonalisation conjoint approchées orthogonale (ou non-orthogonales) d’une famille des matrices cycliques multiples moment temporel, or l’approche matricielle crayon pour extraire les sources signaux. Nous introduisons aussi et prouver une nouvelle condition identifiabilité pour montrer quel type de sources cyclostationnaires d’entrée peuvent être séparées basées sur des statistiques cyclostationnarité à l’ordre deux. Pour la séparation aveugle de sources en mélanges convolutifs, nous présentons un algorithme en deux étapes basées sur une approche dans le domaine temporel pour récupérer les signaux source. Les simulations numériques sont utilisés dans cette thèse pour démontrer l’efficacité de nos approches proposées, et de comparer les performances avec leurs méthodes précédentes / Blind source separation problem aims to recover a set of statistically independent source signals from a set of sensor observations. These observations can be modeled as an instantaneous or convolutive mixture of the same sources. In this dissertation, the source signals are assumed to be cyclostationary where their cycle frequencies may be known or unknown a priori. First, we establish relations between the spectrum, power spectrum of a source signal and its component, then we propose two novel algorithms to estimate its cycle frequencies. Next, for blind separation of instantaneous mixtures of sources, we present four algorithms based on orthogonal (or non-orthogonal) approximate diagonalization of the multiple cyclic temporal moment matrices, and the matrix pencil approach to extract the source signal. We also introduce and prove a new identifiability condition to show which kind of input cyclostationary sources can be separated based on second-order cyclostationarity statistics. For blind separation of convolutive mixtures of sources signal or blind deconvolution of FIR MIMO systems, we present a two-steps algorithm based on time domain approach for recovering the source signals. Numerical simulations are used throughout this thesis to demonstrate the effectiveness of our proposed approaches, and compare theirs performances with previous methods

This thesis studies the design and implementation of a linear minimum mean-square error (LMMSE) receiver in asynchronous bandlimited direct-sequence code-division multiple-access (DS-CDMA) systems that employ long-code pseudo-noise (PN) sequences and operate in multipath environments. The receiver is shown to be capable of multiple-access interference (MAI) suppression and multipath diversity combining without the knowledge of other users' signature sequences. It outperforms any other linear receiver by maximizing output signal-to-noise ratio (SNR) with the aid of a new chip filter which exploits the cyclostationarity of the received signal and combines all paths of the desired user that fall within its supported time span. This work is motivated by the shortcomings of existing LMMSE receivers which are either incompatible with long-code CDMA or constrained by limitations in the system model. The design methodology is based on the concept of linear/conjugate linear (LCL) filtering and satisfying the orthogonality conditions to achieve the LMMSE filter response. Moreover, the proposed LMMSE receiver addresses two drawbacks of the coherent Rake receiver, the industry's current solution for multipath reception. First, unlike the Rake receiver which uses the chip-matched filter (CMF) and treats interference as additive white Gaussian noise (AWGN), the LMMSE receiver suppresses interference by replacing the CMF with a new chip pulse filter. Second, in contrast to the Rake receiver which only processes a subset of strongest paths of the desired user, the LMMSE receiver harnesses the energy of all paths of the desired user that fall within its time support, at no additional complexity. The performance of the proposed LMMSE receiver is analyzed and compared with that of the coherent Rake receiver with probability of bit error, <i>Pe</i>, as the figure of merit. The analysis is based on the accurate improved Gaussian approximation (IGA) technique. Closed form conditional <i>Pe</i> expressions for both the LMMSE and Rake receivers are derived. Furthermore, it is shown that if quadriphase random spreading, moderate to large spreading factors, and pulses with small excess bandwidth are used, the widely-used standard Gaussian Approximation (SGA) technique becomes accurate even for low regions of <i>Pe</i>. Under the examined scenarios tailored towards current narrowband system settings, the LMMSE receiver achieves 60% gain in capacity (1. 8 dB in output SNR) over the selective Rake receiver. A third of the gain is due to interference suppression capability of the receiver while the rest is credited to its ability to collect the energy of the desired user diversified to many paths. Future wideband systems will yield an ever larger gain. Adaptive implementations of the LMMSE receiver are proposed to rid the receiver from dependence on the knowledge of multipath parameters. The adaptive receiver is based on a fractionally-spaced equalizer (FSE) whose taps are updated by an adaptive algorithm. Training-based, pilot-channel-aided (PCA), and blind algorithms are developed to make the receiver applicable to both forward and reverse links, with or without the presence of pilot signals. The blind algorithms are modified versions of the constant modulus algorithm (CMA) which has not been previously studied for long-code CDMA systems. Extensive simulation results are presented to illustrate the convergence behavior of the proposed algorithms and quantify their performance loss under various levels of MAI. Computational complexities of the algorithms are also discussed. These three criteria (performance loss, convergence rate, and computational complexity) determine the proper choice of an adaptive algorithm with respect to the requirements of the specific application in mind.

This thesis studies the design and implementation of a linear minimum mean-square error (LMMSE) receiver in asynchronous bandlimited direct-sequence code-division multiple-access (DS-CDMA) systems that employ long-code pseudo-noise (PN) sequences and operate in multipath environments. The receiver is shown to be capable of multiple-access interference (MAI) suppression and multipath diversity combining without the knowledge of other users' signature sequences. It outperforms any other linear receiver by maximizing output signal-to-noise ratio (SNR) with the aid of a new chip filter which exploits the cyclostationarity of the received signal and combines all paths of the desired user that fall within its supported time span. This work is motivated by the shortcomings of existing LMMSE receivers which are either incompatible with long-code CDMA or constrained by limitations in the system model. The design methodology is based on the concept of linear/conjugate linear (LCL) filtering and satisfying the orthogonality conditions to achieve the LMMSE filter response. Moreover, the proposed LMMSE receiver addresses two drawbacks of the coherent Rake receiver, the industry's current solution for multipath reception. First, unlike the Rake receiver which uses the chip-matched filter (CMF) and treats interference as additive white Gaussian noise (AWGN), the LMMSE receiver suppresses interference by replacing the CMF with a new chip pulse filter. Second, in contrast to the Rake receiver which only processes a subset of strongest paths of the desired user, the LMMSE receiver harnesses the energy of all paths of the desired user that fall within its time support, at no additional complexity. The performance of the proposed LMMSE receiver is analyzed and compared with that of the coherent Rake receiver with probability of bit error, <i>Pe</i>, as the figure of merit. The analysis is based on the accurate improved Gaussian approximation (IGA) technique. Closed form conditional <i>Pe</i> expressions for both the LMMSE and Rake receivers are derived. Furthermore, it is shown that if quadriphase random spreading, moderate to large spreading factors, and pulses with small excess bandwidth are used, the widely-used standard Gaussian Approximation (SGA) technique becomes accurate even for low regions of <i>Pe</i>. Under the examined scenarios tailored towards current narrowband system settings, the LMMSE receiver achieves 60% gain in capacity (1. 8 dB in output SNR) over the selective Rake receiver. A third of the gain is due to interference suppression capability of the receiver while the rest is credited to its ability to collect the energy of the desired user diversified to many paths. Future wideband systems will yield an ever larger gain. Adaptive implementations of the LMMSE receiver are proposed to rid the receiver from dependence on the knowledge of multipath parameters. The adaptive receiver is based on a fractionally-spaced equalizer (FSE) whose taps are updated by an adaptive algorithm. Training-based, pilot-channel-aided (PCA), and blind algorithms are developed to make the receiver applicable to both forward and reverse links, with or without the presence of pilot signals. The blind algorithms are modified versions of the constant modulus algorithm (CMA) which has not been previously studied for long-code CDMA systems. Extensive simulation results are presented to illustrate the convergence behavior of the proposed algorithms and quantify their performance loss under various levels of MAI. Computational complexities of the algorithms are also discussed. These three criteria (performance loss, convergence rate, and computational complexity) determine the proper choice of an adaptive algorithm with respect to the requirements of the specific application in mind.

Made available in DSpace on 2014-12-17T14:56:19Z (GMT). No. of bitstreams: 1 ArthurDLL_DISSERT.pdf: 2517302 bytes, checksum: c3d693c770dc1c58bad5f378aba6d268 (MD5) Previous issue date: 2014-06-28 / The increasing demand for high performance wireless communication systems has shown the inefficiency of the current model of fixed allocation of the radio spectrum. In this context, cognitive radio appears as a more efficient alternative, by providing opportunistic spectrum access, with the maximum bandwidth possible. To ensure these requirements, it is necessary that the transmitter identify opportunities for transmission and the receiver recognizes the parameters defined for the communication signal. The techniques that use cyclostationary analysis can be applied to problems in either spectrum sensing and modulation classification, even in low signal-to-noise ratio (SNR) environments. However, despite the robustness, one of the main disadvantages of cyclostationarity is the high computational cost for calculating its functions. This work proposes efficient architectures for obtaining cyclostationary features to be employed in either spectrum sensing and automatic modulation classification (AMC). In the context of spectrum sensing, a parallelized algorithm for extracting cyclostationary features of communication signals is presented. The performance of this features extractor parallelization is evaluated by speedup and parallel eficiency metrics. The architecture for spectrum sensing is analyzed for several configuration of false alarm probability, SNR levels and observation time for BPSK and QPSK modulations. In the context of AMC, the reduced alpha-profile is proposed as as a cyclostationary signature calculated for a reduced cyclic frequencies set. This signature is validated by a modulation classification architecture based on pattern matching. The architecture for AMC is investigated for correct classification rates of AM, BPSK, QPSK, MSK and FSK modulations, considering several scenarios of observation length and SNR levels. The numerical results of performance obtained in this work show the eficiency of the proposed architectures / O aumento da demanda por sistemas de comunica??o sem fio de alto desempenho tem evidenciado a inefici?ncia do atual modelo de aloca??o fixa do espectro de r?dio. Nesse contexto, o r?dio cognitivo surge como uma alternativa mais eficiente, ao proporcionar o acesso oportunista ao espectro, com a maior largura de banda poss?vel. Para garantir esses requisitos, ? necess?rio que o transmissor identifique as oportunidades de transmiss?o e que o receptor reconhe?a os par?metros definidos para o sinal de comunica??o. As t?cnicas que utilizam a an?lise cicloestacion?ria podem ser aplicadas tanto em problemas de sensoriamento espectral, quanto na classifica??o de modula??es, mesmo em ambientes de baixa rela??o sinal-ru?do (SNR). Entretanto, apesar da robustez, uma das principais desvantagens da cicloestacionariedade est? no elevado custo computacional para o c?lculo das suas fun??es. Este trabalho prop?e arquiteturas eficientes de obten??o de caracter?sticas cicloestacion?rias para serem empregadas no sensoriamento espectral e na classifica??o autom?tica de modula??es (AMC). No contexto do sensoriamento espectral, um algoritmo paralelizado para extrair as caracter?sticas cicloestacion?rias de sinais de comunica??o ? apresentado. O desempenho da paraleliza??o desse extrator de caracter?sticas ? avaliado atrav?s das m?tricas de speedup e efici?ncia paralela. A arquitetura de sensoriamento espectral ? analisada para diversas configura??es de probabilidades de falso alarme, n?veis de SNR e tempo de observa??o das modula??es BPSK e QPSK. No contexto da AMC, o perfil-alfa reduzido ? proposto como uma assinatura cicloestacion?ria calculada para um conjunto reduzido de frequ?ncia c?clicas. Essa assinatura ? validada por meio de uma arquitetura de classifica??o baseada no casamento de padr?es. A arquitetura para AMC ? investigada para as taxas de acerto obtidas para as modula??es AM, BPSK, QPSK, MSK e FSK, considerando diversos cen?rios de tempo de observa??o e n?veis de SNR. Os resultados num?ricos de desempenho obtidos neste trabalho demonstram a efici?ncia das arquiteturas propostas