Diss. Univ. Linz, 2008.

GNU Radio and OSSIE (Open-Source SCA (Software communication architecture) Implementation-Embedded) are two open source software toolkits for SDR (Software Defined Radio) developments, both of them can be supported by USRP (Universal Software Radio Peripheral). In order to compare the performance of these two toolkits, an FM receiver over GNU Radio and OSSIE are tested in my thesis, test results are showed in Chapter 4 and Chapter 5. Results showed that the FM receiver over GNU Radio has better performance, due to the OSSIE is lack of synchronization between USRP interface and the modulation /demodulation components. Based on this, the SISO (Single Input Single Output) communication system over GNU Radio is designed to transmit and receive sound or image files between two USRP equipped with RFX2400 transceiver at 2.45G frequency. Now, GNU Radio and OSSIE are widely used for academic research, but the future work based on GNU Radio and OSSIE can be designed to support MIMO, sensor network, and real time users etc.

Σε αυτή τη διπλωματική εργασία υλοποιήθηκε ένας LDPC αποκωδικοποιητής που χρησιμοποιεί τις βασικές αρχές της turbo αποκωδικοποίησης, εισάγοντας στα χαρακτηριστικά της αποκωδικοποίησης του το διάγραμμα trellis. O maximum a posteriori probability (MAP) αλγόριθμος χρησιμοποιείται σαν μια γέφυρα μεταξύ των LDPC και Turbo κωδικών. Οι LDPC κώδικες αντιμετωπίζονται ως μια αλυσιδωτή σύνδεση n υπέρ κωδικών, όπου ο κάθε υπέρ κώδικας έχει πλέον μια πιο απλή δομή trellis ώστε ο MAP αλγόριθμος να μπορεί να εφαρμοστεί. / In this thesis an LDPC decoder is implemented using the principles of turbo decoding, introducing the characteristics of the decoding of the trellis diagram . The maximum a posteriori probability (MAP) algorithm is used as a bridge between the LDPC and Turbo codes. The LDPC codes are treated as concatenated n supercodes, where each code has a simple trellis structure so that the MAP algorithm can be implemented.

<p> In this thesis we develop several approaches to the problem of blind channel equalization based on second-order statistics (808). We consider the single-input singleoutput (8180) system with minimum phase channel where the received signal is sampled at the symbol rate (T-spaced equalizer). We formulate the equalizer design criterion as a simple convex optimization problem, where the equalizer can be obtained efficiently avoiding the local minima problem. </p> <p> We also extend the problem to the single-input multiple-output (8IMO) systems where the received signal is sampled at an integer multiple of the symbol rate. We formulate the problem as a convex optimization problem using the features existing in the channel matrix structure. The problem can be solved efficiently to obtain the equalizer where a global minima is guaranteed. Moreover, we modify this formulation and deduce a closed form solution to the equalizer. Although both methods are sensitive to the channel order as well as existing subspace methods, they perform better than the subspace methods when the channel matrix is close to being singular. Furthermore, we propose an efficient direct minimum mean square error (MM8E) approach to estimate the equalizer. The method does not rely on the channel order and utilizes the channel matrix structure in SIMO systems. Therefore, it outperforms existing algorithms including the previously proposed methods. However, due to the large amount of computations involved in this method we present a new algorithm that belongs to the same class with moderate computational complexity and acceptable performance loss with respect to the latter algorithm. </p> / Thesis / Master of Applied Science (MASc)

A Identificação de Sistemas é uma das técnicas utilizadas para se obter a representação matemática de um sistema. Diversos métodos podem ser aplicados para se obter um modelo matemático através da identificação de sistemas, entre eles o método de identificação assintótico, também chamado de ASYM (Zhu, 1998). Este trabalho propõe aplicar o método de identificação assintótico em sistemas SISO para a obtenção de modelo de sistemas ditos caixa-preta e avaliar o seu desempenho buscando também o melhor detalhamento do método. Os modelos obtidos foram avaliados de acordo com sua nota calculada através do método ASYM, através da comparação do índice de ajuste fit para autovalidação e validação cruzada e pela variância dos parâmetros dos modelos. O método ASYM é exaustivamente testado para sua avaliação. Entre os testes realizados neste trabalho destacam-se dois experimentos tipo Monte-Carlo com mais de quinhentas identificações e a aplicação do método em uma planta real. Os testes comprovaram a viabilidade da aplicação do método assintótico na identificação de sistemas SISO do tipo caixa-preta com excelente desempenho para estruturas ARMAX. / System Identification is one of the techniques used to obtain the mathematical representation of a system. Several methods can be applied to obtain a mathematical model by the system identification, including the asymptotic method, also called ASYM (Zhu, 1998). This work proposes to apply the ASYM method for SISO systems identification, then obtain models of black-box systems called \"black box\" and evaluate its performance and show details of the method. The models obtained were evaluated according to their grade calculated using the ASYM method, by comparing the fit adjustment index, self-validation and cross validation and the variance of model parameters. The asymptotic method has been extensively tested to be evaluated. Among the tests in this work, two stand out such Monte Carlo experiments with more than five hundred identifications and a real plant identification. The tests proved the feasibility of applying the asymptotic method in the \"black box\" SISO systems identification with excellent performance for ARMAX structures.

A Identificação de Sistemas é uma das técnicas utilizadas para se obter a representação matemática de um sistema. Diversos métodos podem ser aplicados para se obter um modelo matemático através da identificação de sistemas, entre eles o método de identificação assintótico, também chamado de ASYM (Zhu, 1998). Este trabalho propõe aplicar o método de identificação assintótico em sistemas SISO para a obtenção de modelo de sistemas ditos caixa-preta e avaliar o seu desempenho buscando também o melhor detalhamento do método. Os modelos obtidos foram avaliados de acordo com sua nota calculada através do método ASYM, através da comparação do índice de ajuste fit para autovalidação e validação cruzada e pela variância dos parâmetros dos modelos. O método ASYM é exaustivamente testado para sua avaliação. Entre os testes realizados neste trabalho destacam-se dois experimentos tipo Monte-Carlo com mais de quinhentas identificações e a aplicação do método em uma planta real. Os testes comprovaram a viabilidade da aplicação do método assintótico na identificação de sistemas SISO do tipo caixa-preta com excelente desempenho para estruturas ARMAX. / System Identification is one of the techniques used to obtain the mathematical representation of a system. Several methods can be applied to obtain a mathematical model by the system identification, including the asymptotic method, also called ASYM (Zhu, 1998). This work proposes to apply the ASYM method for SISO systems identification, then obtain models of black-box systems called \"black box\" and evaluate its performance and show details of the method. The models obtained were evaluated according to their grade calculated using the ASYM method, by comparing the fit adjustment index, self-validation and cross validation and the variance of model parameters. The asymptotic method has been extensively tested to be evaluated. Among the tests in this work, two stand out such Monte Carlo experiments with more than five hundred identifications and a real plant identification. The tests proved the feasibility of applying the asymptotic method in the \"black box\" SISO systems identification with excellent performance for ARMAX structures.

<p>In the 3G standards, wireless communication system can support 2 Mb/s. With this data rate, multimedia communication is realized on handset. However, it is expected that new applications will require even higher data rates in future. In order to fulfil the growing requirement of high data rate, 100 Mb/s is considered as the aim of 4G standards. Such high data rate will result in very large power consumption, which is unacceptable considering the current battery capability. Therefore, reducing the power consumption of turbo decoders becomes a major issue to be solved. This report explores new techniques for implementing low power, small area and high throughput turbo decoders.</p>

In the 3G standards, wireless communication system can support 2 Mb/s. With this data rate, multimedia communication is realized on handset. However, it is expected that new applications will require even higher data rates in future. In order to fulfil the growing requirement of high data rate, 100 Mb/s is considered as the aim of 4G standards. Such high data rate will result in very large power consumption, which is unacceptable considering the current battery capability. Therefore, reducing the power consumption of turbo decoders becomes a major issue to be solved. This report explores new techniques for implementing low power, small area and high throughput turbo decoders.

Le système OFDM (Orthogonal Frequency Division Multiplexing) utilise plusieurs sous-porteuses pour transmettre de l’information. Comparé à un schéma mono-porteuse, la modulation multi-porteuses OFDM permet d’obtenir facilement des réglages optimaux (au sens de la capacité de Shannon) pour une transmission à haut débit sur un canal sélectif en fréquence. En ce sens, on peut alors garantir une transmission fiable et une meilleure gestion de l'énergie utilisée. Lors de la transmission avec une modulation OFDM, les sous-porteuses utilisent des canaux différents qui n’ont pas forcement la même atténuation. Allouer le même niveau de puissance à chaque sous-porteuse ne garantit pas une capacité optimale dans une liaison point à point. Une allocation dynamique de la puissance (c’est-à-dire attribuer différents niveaux de puissance aux sous-porteuses en fonction du canal) donne de meilleures performances. Par contre, dans une situation de diffusion (broadcast), l’émetteur ne connaît pas les canaux vers tous les utilisateurs, et la meilleure stratégie consiste à émettre avec la même puissance sur toutes les sous-porteuses. Cette thèse a pour objectif d’explorer les situations intermédiaires, et de proposer les outils d’allocation de puissance appropriés. Cette situation intermédiaire est appelée « multicast », ou « multidiffusion » : l’émetteur envoie les signaux vers un nombre fini (pas trop grand) d’utilisateurs, dont il connaît les paramètres de canaux, et il peut adapter son émission à cette connaissance des canaux. On est donc dans une situation intermédiaire entre le « point à point » et la « diffusion ». L’objectif final de ce travail est d’évaluer le gain apporté par la connaissance des canaux en situation de multicast par rapport à la même communication effectuée comme si on était en diffusion. Bien évidemment, quand le nombre de destinataires est très grand, les gains seront négligeables, car le signal rencontre un nombre très élevé de canaux, et une allocation de puissance uniforme sera quasi optimale. Quand le nombre est très faible, on sera proche du point à point et les gains devraient être sensibles. Nous proposons des outils pour quantifier ces améliorations dans les cas de systèmes ayant une antenne à l'émission et une antenne à la réception, dit SISO (Single Input Single Output) et de systèmes avec plusieurs antennes, dits MIMO (Multiple Input Multiple Output). Les étapes nécessaires pour réaliser ce travail sont : 1) En supposant une connaissance préalable de l’état des canaux (entre station de base et terminaux), mettre en œuvre les outils de la théorie de l'information pour effectuer l’allocation de puissance et évaluer les capacités des systèmes étudiés. 2) Pour le système multi-utilisateur SISO-OFDM, nous proposons un algorithme d'allocation de puissance sur chaque sous porteuse dans une situation de multicast. 3) Pour le système multi-utilisateur MIMO-OFDM, nous proposons un algorithme qui exploite les caractéristiques du précodage "zero forcing". L'objectif est alors de partager la puissance disponible entre toutes les sous-porteuses et toutes les antennes. 4) Enfin, dans une dernière étape nous nous intéressons à une conception efficace de la situation de diffusion, afin de déterminer à l’aide d’outils de géométrie stochastique quelle zone peut être couverte afin qu’un pourcentage donné d’utilisateurs reçoivent une quantité d’information déterminée à l’avance. Ceci permet de déterminer la zone de couverture sans mettre en œuvre des simulations intensives. La combinaison de ces outils permet un choix efficace des situations qui relèvent de la « diffusion », du « multicast » et du « point à point ». / The OFDM (Orthogonal Frequency Division Multiplexing) system uses multiple sub-carriers for data transmission. Compared to the single-carrier scheme, the OFDM technique allows optimal settings for high data rate transmission over a frequency selective channel (from the Shannon’s capacity point of view). We can, by this way, ensure reliable communication and efficient energy use. When we use OFDM, the sub-carriers use different channels with different attenuations as well. The equal power allocation on each sub-carrier does not ensure an optimal capacity in a peer to peer link. Dynamic power allocation (i.e., assign different amount of power to subcarriers according to the channel) gives better results, assuming that the channel state information is available at the transmitter. Nevertheless, the transmitter does not know the channels to all users when broadcast transmission are used, and the best strategy is to transmit with the same power on all subcarriers. This thesis aims to explore the intermediate situations, and propose appropriate power allocation tools. This intermediate situation is called "multicast": the transmitter, which knows the channel parameters, sends signals to a finite number of users, and it can adapt the transmission using this knowledge. It is an intermediate position between the "peer to peer" and the "broadcast. The goal of this work is to evaluate the gain brought by the knowledge of the channel state information in multicast situation beside the broadcast situation. Obviously, when the number of receivers is very large, the gain will not be appreciable because the signal found on its path a very large number of channels, and a uniform power allocation is near optimal. When the number of users is very low, we will be close to the peer to peer transmission and gains should be more appreciable. We propose some tools to quantify these improvements in the case where the systems have one antenna at the transmitter and the receiver, this case named SISO (Single Input Single Output). We also propose those tools on systems with multiple antennas, called MIMO (Multiple Input Multiple Output). The steps required to do this work are: 1) Assuming that the channel state information of the users are known at the base station, we implement tools, using information theory, to perform power allocation and evaluate the capacities of the systems under study. 2) For multi-user SISO-OFDM scheme, we propose a power allocation algorithm on each subcarrier on multicast situation. 3) For multi-user MIMO-OFDM, we propose an algorithm that exploits the characteristics of the "zero forcing" precoding. The objective is to share the available power among all subcarriers and all antennas. 4) Finally, in a last step we focus on an efficient design of the broadcast situation. We use tools from stochastic geometry to determine which area can be covered, with the aim that a percentage of users can receive a predetermined amount of information. This determines the coverage area without implementing long period simulations. The combination of these tools allows an effective choice between the situations that fall under the "broadcast", "multicast" and "peer to peer" transmissions.

Kalba yra natūralus žmonių bendravimo būdas. Teksto-į-šneką (TTS) problemos atsiranda įvairiose srityse: elektroninių laiškų skaitymas balsu, teksto iš elektroninių knygų skaitymas balsu, paslaugos kalbos sutrikimų turintiems žmonėms. Kalbos sintezatoriaus kūrimas yra be galo sudėtingas uždavinys. Įvairių šalių mokslininkai bando automatizuoti kalbos sintezę. Siekiant išspręsti lietuvių kalbos sintezės problemą, būtina kurti naujus lietuvių kalbos garsų matematinius modelius. Disertacijos tyrimo objektas yra dinaminiai lietuviškos šnekos balsių ir pusbalsių fonemų modeliai. Pasiūlyti balsių ir pusbalsių fonemų dinaminiai modeliai gali būti panaudoti kuriant formantinį kalbos sintezatorių. Garsams aprašyti pasiūlyta modeliavimo sistema pagrįsta balsių ir pusbalsių fonemų matematiniu modeliu bei pagrindinio tono ir įėjimų nustatymo automatine procedūra. Fonemos signalas yra gaunamas kai daugelio-įėjimų ir vieno-išėjimo (MISO) sistemos išėjimas. MISO sistema susideda iš lygiagrečiai sujungtų vieno-įėjimo ir vieno-išėjimo (SISO) sistemų, kurių įėjimų amplitudes kinta laike. Disertacijoje du sintezės metodai sukurti: harmoninis ir formantinis. Eksperimentiniai rezultatai parodė, kad balsiai ir pusbalsiai sintezuoti minėta sistema skamba pakankamai natūraliai. / Speech is the most natural way of human communication. Text-to-speech (TTS) problem arises in various applications: reading email aloud, reading text from e-book aloud, services for the people with speech disorders. Construction of speech synthesizer is a very complex task. Researchers are trying to automate speech synthesis. In order to solve the problem of Lithuanian speech synthesis, it is necessary to develop mathematical models for Lithuanian speech sounds. The research object of the dissertation is Lithuanian vowel and semivowel phoneme models. The proposed vowel and semivowel phoneme models can be used for developing a TTS formant synthesizer. Lithuanian vowel and semivowel phoneme modelling framework based on a vowel and semivowel phoneme mathematical model and an automatic procedure of estimation of the vowel phoneme fundamental frequency and input determining is proposed. Using this framework, the phoneme signal is described as the output of a linear multiple-input and single-output (MISO) system. The MISO system is a parallel connection of single-input and single-output (SISO) systems whose input impulse amplitudes vary in time. Within this framework two synthesis methods are proposed: harmonic and formant. Simulation has revealed that that the proposed framework gives sufficiently good vowel and semivowel synthesis quality.