In this thesis, we study the cognitive algorithm in digital television (DTV) bands for Wireless Regional Area Network (WRAN) signals. The WRAN standards are specified by the IEEE 802.22 Working Group. The principle of the proposed algorithm in this thesis is to recognize the band state by analyzing the transmitted signals in DTV bands. The received signals could be 4 possible options: 1.Noise 2.ATSC signal plus noise 3.WRAN signal plus noise 4.ATSC signal plus WRAN signal and noise. This thesis proposed an algorithm to cognize the WRAN signals, and the proposed schedule is 1.Cognitive algorithm for sensing ATSC signal 2.Cognitive algorithm for sensing WRAN signal. According to the result of this schedule, we will get the information of the band status. Later, WRAN will make use of cognitive radio technology we developed in the thesis, together with other cognitive information (such as channel capacity, system parameters, etc.), to sustain the WRAN signal transmission by making some adjustments of system parameters or the required bandwidth.

Spectral coexistence and cooperative spectrum sharing techniques are vital to the continued development and proliferation of wireless communications systems. Government directives indicate that certain frequency bands which once were reserved for radar-only applications must now support wireless broadband systems. The effect of co-site interference upon detection techniques for wireless broadband systems is evaluated. Cyclostationary feature based detection methods are evaluated against gaussian noise and interfering radar signals. Alternative decision algorithms utilizing support vector machines are proposed and evaluated and compared against traditional general likelihood ratio test algorithms. Recommendations for certain algorithms and observation window lengths to maximize e ectiveness and minimize computational complexity are developed. / Office of Naval Research grant N00014-12-1-0062 and contract N00014-12-C-0702 / Master of Science

Dans cette thèse, nous nous sommes intéressés aux méthodes de séparation de mélanges convolutifs de signaux cyclostationnaires, et particulièrement de signaux issus de systèmes de communications numériques. Les résultats de ces travaux concernent principalement les méthodes de séparation basées sur la minimisation d'un critère du type CMA avec une approche par déflation. Dans la première partie de ce manuscrit nous nous sommes concentrés sur les mélanges de sources non-circulaires à l'ordre 2, notamment des sources BPSK ou CPM d'indice 1/2. Nous avons montré que dans le cas où les sources ont des caractéristiques différentes (en terme de débit et de résidu de porteuse) la minimisation du critère du module constant couplée avec une approche par déflation permet d'extraire les sources du mélange sans connaître leurs fréquences cycliques ni leurs fréquences cycliques non conjuguées. Dans le cas opposé, où les sources partagent les mêmes fréquences cycliques et les mêmes fréquences cycliques non conjuguées, nous avons prouvé l'existence de minima locaux non-séparants du critère du CMA. Nous avons aussi montré que le critère du CMA converge dans un grand nombre de cas vers ces points et que par conséquent la séparation de sources n'est pas toujours réalisée pour ce type de mélanges. Nous avons ensuite proposé un nouveau critère basé sur le critère du CMA qui, couplé avec une approche par déflation, assure l'extraction des sources dans ces situations. Ce nouveau critère ne nécessite pas la connaissance des fréquences cycliques des signaux mais nécessite quand même la connaissance des fréquences cycliques non-conjuguées les plus significatives. Nous avons proposé une méthode assez grossière d'estimation de ces fréquences et nous avons montré que, avec les fréquences cycliques non-conjuguées significatives ainsi estimées, l'algorithme proposé fonctionne correctement et qu'il est capable d'extraire les sources des mélanges pour lesquels le critère du CMA échoue. Dans la deuxième partie de ce manuscript, nous nous sommes intéressés aux séparateurs dérivés du principe du maximum de vraisemblance. Nous avons d'abord étudié des mélanges instantanés des signaux cyclostationnaires et circulaires à l'ordre 2. Dans ce contexte, nous avons mis en évidence des estimateurs basés sur le principe du maximum de vraisemblance et nous avons présenté une méthode pour les implanter. Nous avons ensuite étudié les propriétés asymptotiques de ces estimateurs et nous avons montré que, dans des conditions idéales (absence du bruit), ces estimateurs permettent d'améliorer les performances du critère du CMA. Toujours dans ces conditions, nous avons montré que les estimateurs dérivés du critère du maximum de vraisemblance permettent dans certains cas d'estimer la source ayant la bande passante la plus petite avec une erreur plus petite que les méthodes usuelles. Ces résultats ne sont malheureusement plus vrais dans un context plus réaliste comme en présence de bruit. Nous avons généralisé les idées développées dans le cas de mélanges instantanés au cas de mélanges convolutifs mais pour ce type de mélanges, nous n'avons pas constaté d'amélioration des performances du critère du CMA même dans le cas non-bruité. Bien qu'en pratique cette étude n'apporte pas de grandes contributions, elle a néanmoins un intérêt théorique certain / This thesis addresses the problem of blind separation of convolutive mixtures of cyclostationnary, linearly modulated signals. We mainly focus on signals issued from digital communications systems. Our work involves separating methods based on the minimisation of a criterion (like the constant modulus) combined with a deflation approach. In the first part of the manuscript we considered convolutive mixtures of non second order circular signals such as BPSK and $1/2$ index CPM modulations. We have proven that if the transmission sources all have different baud rates and offset frequencies, minimizing the constant modulus criterion and using a deflation approach successfully achieves the extraction of the original signals from the mixture without prior knowledge of the signal cyclic and non conjugate cyclic frequencies. This result is no longer obtained if all the transmission sources have the same baud rate and frequency offset. We have proven that in this case the CMA criterion has non separating local minima and that the minimisation algorithm very often converges to these spurious points. This means that in a non-negligible number of cases separation is not achieved for this type of mixtures. We therefore propose a new criterion based on the CMA which combined with a deflation approach ensures the extraction of source signals from this particular type of mixtures. This new criterion does not need prior knowledge of the cyclic frequencies but does need information on the most significant non conjugate cyclic frequencies of the signals. We also propose an estimation method for these frequencies and we show that our new algorithm works correctly with the estimated non conjugate cyclic frequencies and that it is capable to extract all the source signals from those types of mixtures for which the CMA fails.The second part of this manuscript focuses on a class of Maximum Likelihood derived separators. We are only considering second order circularly modulated signals. We first studied the case of instantaneous mixtures and then extended our results to convolutive mixtures. For the instantaneous mixtures, we have developed Maximum Likelihood based estimators and presented an implementation method for them. We have then studied their asymptotic properties and we have shown that, in the absence of noise, these estimators improve the performance of the CMA algorithm. Under the same assumptions we have shown that the Maximum Likelihood based estimators allow, in some cases, to extract the signal with the largest bandwidth with a lower error than the one obtained when using other well known separating methods. This results however are no longer true in more realistic contexts such as the presence of noise. We have extended this study to the convolutive mixtures of signals but in this case we have not seen an important improvement on the performances achieved by the CMA algorithm, not even in the absence of noise. Even though this study does not have practical applications, it has nevertheless a certain theoretical significance

Thesis (Ph. D.)--Oregon State University, . / Printout. Includes bibliographical references (leaves 137-140). Also available on the World Wide Web.

by Wan Shan. / "June, 2003." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

No description available.

We propose to develop new non-data aided (NDA) digital feedforward symbol timing estimators for linear and nonlinear modulations, with a view to reducing the sampling rate of the estimators. The proposed estimators rely on the fact that sufficient statistics exist for a signal sampled at the Nyquist rate. We propose an ad hoc extension to the timing estimator based on the log nonlinearity which performs better than existing estimators at this rate when the operating signal-to-noise ratio (SNR) and the excess bandwidth are low. We propose another alternative estimator for operating at the Nyquist rate that has reduced self-noise at high SNR for large rolloff factors. This can be viewed as an extension of the timing estimator based on the square law nonlinearity. For continuous phase modulations (CPM), we propose two novel estimators that can operate at the symbol rate for MSK type signals. Among the class of NDA feedforward timing estimators we are not aware of any other estimator that can function at symbol rate for this type of signals. We also propose several new estimators for the MSK modulation scheme which operate with reduced sampling rate and are robust to carrier frequency offset and phase offset.

A special class of nonstationary processes with periodically varying statistics, called cyclostationary (CS), is investigated. These processes are encountered in many engineering problems involving rotating machinery such as turbines, propellers, helicopter rotors, and diesel engines. We analyze a cyclostationary process model in order to show its advantages compared to a traditional stationary process model and present a methodology for calculating the statistics of the response of a linear system subjected to CS excitations. We demonstrate that a CS model estimates the statistics of the response of a linear dynamic system subjected to CS excitations more accurately by considering (1) a vehicle traveling on a rough road and (2) a propeller rotating in the wake of a ship in the presence of turbulence. In the case of the vehicle, the road consists of concrete plates of fixed length. We model the road excitation using a CS process and calculate the standard deviation (root mean square) of the vehicle response. In the case of the ship propeller, we calculate the hydrodynamic forces acting on the propeller using the vortex panel method and the vortex theory of propeller. Considering the randomness in the axial and the tangential components of velocity, we calculate the mean and the covariance of the forces. This analysis shows that the hydrodynamic forces acting on the propeller are CS processes. Then we perform finite element analysis of the propeller and calculate the mean and the standard deviation of the blade response. We do the parametric analysis to demonstrate the effects of some physical quantities such as the standard deviation, the correlation coefficient, the decorrelation time, and the scale of turbulence of the axial and the tangential components of the wake velocity on the standard deviation of the blade deflection. We found that the CS model yields the time-wise variation of the statistics of the excitation and the response (e.g., the root mean square) and their peaks correctly. This is important information for the calculation of probability of failure of the propeller. A traditional stationary model cannot provide this information. / Master of Science

This thesis addresses the problem of identifying the modal properties of a system based only on measurements of the system responses. This situation is frequently encountered in structural dynamics and is particularly relevant for systems where the in-service excitation is not artificially reproducible. The inherent non-linearities in these systems mean that the modal properties estimated using traditional input/output techniques will be different to those exhibited in operation. A common example from the literature is an aircraft in flight where the modal properties are heavily influenced by the operating point, i.e. the combination of load, speed, altitude etc., at which the aircraft is travelling. The process of identifying the modal properties of systems in-service is called Operational Modal Analysis (OMA). Not knowing the input complicates the analysis. Most of the techniques in the literature overcome the lack of knowledge about the unmeasured excitations by assuming they are both spatially and frequentially white, i.e. of equal magnitude and with a flat autospectrum. This thesis presents a new technique for OMA which relaxes these constraints, requiring only that the system is excited by a so called cyclostationary input with a unique cyclic frequency, and that the log spectrum of the second order component of this input is frequentially smooth, as will be explained. Such systems include vehicles with internal combustion engines as the vibration from such an engine exhibits cyclostationary statistics. In this thesis, the technique is applied to a laboratory test rig and a passenger train both using an artificial input, and to a race car using the engine as the excitation. By combining cyclostationary signal processing and the concept of the cepstrum, the technique identifies the resonances and anti-resonances in the transfer functions between each response and the cyclostationary source. These resonances and antiresonances can be used to regenerate Frequency Response Functions (FRFs) and it is shown how the unknown scaling of the system can be recovered by employing finite element model updating in conjunction with this regeneration. In addition, the contribution made to model updating by the anti-resonances is also investigated. Finally, the potential of OMA to inform a model updating process is demonstrated using an experimental case study on a diesel railcar.

No description available.