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This Master’s thesis subject is communication link modeling, what means exploring and subsequent connect of blocks QPSK modulator – raised cosine filter – quadrature modulator – nonlinear amplifier – quadrature demodulator – raised cosine filter – QPSK detector. All work proceeded in simulation world VisSim 6.0, manual of this software is opened in this thesis. Individual blocks are analyzed in this scheme including description and configuration. Main theme was exploring error rate of transmission in modulator imbalance, using nonlinear amplifier TWTA or in calculations in fixed and floating point. Theoretically is examined and practically implanted method of modulator imbalance compensation. Circuits with QPSK and 16QAM modulator were analyzed. Circuits are filled in with transparent tables and graphs. In the end of this thesis is applied to generating of source codes in C language by the help of upgrade C-Code, which can be useful in practical realization on DSP.

Direct-Down Conversion (DDC) principle based transceiver architectures are of interest to meet the diverse needs of present and future wireless systems. DDC transceivers have a simple structure with fewer analog components and offer low-cost, flexible and multi-standard solutions. However, DDC transceivers have certain circuit impairments affecting their performance in wide-band, high data rate and multi-user systems. IQ imbalance is one of the problems of DDC transceivers that limits their image rejection capabilities. Compensation techniques for frequency independent IQI arising due to gain and phase mismatches of the mixers in the I/Q paths of the transceiver have been widely discussed in the literature. However for wideband multi-channel transceivers, it is becoming increasingly important to address frequency dependent IQI arising due to mismatches in the analog I/Q lowpass filters. A hardware-efficient and standard independent digital estimation and compensation technique for frequency dependent IQI is introduced which is also capable of tracking time-varying IQI changes. The technique is blind and adaptive in nature, based on the second order statistical properties of complex random signals such as properness/circularity. A detailed performance analysis of the introduced technique is executed through computer simulations for various real-time operating scenarios. A novel technique for finding the optimal number of taps required for the adaptive IQI compensation filter is proposed and the performance of this technique is validated. In addition, a metric for the measure of properness is developed and used for error power and step size analysis. / Master of Science / A wireless transceiver consists of two major building blocks namely the RF front-end and digital baseband. The front-end performs functions such as frequency conversion, filtering, and amplification. Impurities because of deep-submicron fabrication lead to non-idealities of the front-end components which limit their accuracy and affect the performance of the overall transceiver. Complex (I/Q) mixing of baseband signals is preferred over real mixing because of its inherent trait of bandwidth efficiency. The I/Q paths enabling this complex mixing in the front-end may not be exactly identical thereby disturbing the perfect orthogonality of inphase and quadrature components leading to IQ Imbalance. The resultant IQ imbalance leads to an image of the signal formed at its mirror frequencies. Imbalances arising from mixers lead to an image of constant strength whereas I/Q low-pass filter mismatches lead to an image of varying strength across the Nyquist range. In addition, temperature effects cause slow variation in IQ imbalance with time. In this thesis a hardware efficient and standard-independent technique is introduced to compensate for performance degrading IQ imbalance. The technique is blind and adaptive in nature and uses second order statistical signal properties like circularity or properness for IQ imbalance estimation. The contribution of this work, which gives a key insight into the optimal number of taps required for the adaptive compensation filter improves the state-of-the-art technique. The performance of the technique is evaluated under various scenarios of interest and a detailed analysis of the results is presented.

Specific Emitter Identification (SEI) is the association of a received signal to an emitter, and is made possible by the unique and unintentional characteristics an emitter imparts onto each transmission, known as its radio frequency (RF) fingerprint. SEI systems are of vital importance to the military for applications such as early warning systems, emitter tracking, and emitter location. More recently, cognitive radio systems have started making use of SEI systems to enforce Dynamic Spectrum Access (DSA) rules. The use of pre-determined and expert defined signal features to characterize the RF fingerprint of emitters of interest limits current state-of-the-art SEI systems in numerous ways. Recent work in RF Machine Learning (RFML) and Convolutional Neural Networks (CNNs) has shown the capability to perform signal processing tasks such as modulation classification, without the need for pre-defined expert features. Given this success, the work presented in this thesis investigates the ability to use CNNs, in place of a traditional expert-defined feature extraction process, to improve upon traditional SEI systems, by developing and analyzing two distinct approaches for performing SEI using CNNs. Neither approach assumes a priori knowledge of the emitters of interest. Further, both approaches use only raw IQ data as input, and are designed to be easily tuned or modified for new operating environments. Results show CNNs can be used to both estimate expert-defined features and to learn emitter-specific features to effectively identify emitters. / Master of Science / When a device sends a signal, it unintentionally modifies the signal due to small variations and imperfections in the device’s hardware. These modifications, which are typically called the device’s radio frequency (RF) fingerprint, are unique to each device, and, generally, are independent of the data contained within the signal. The goal of a Specific Emitter Identification (SEI) system is to use these RF fingerprints to match received signals to the devices, or emitters, which sent the given signals. SEI systems are often used for military applications, and, more recently, have been used to help make more efficient use of the highly congested RF spectrum. Traditional state-of-the-art SEI systems detect the RF fingerprint embedded in each received signal by extracting one or more features from the signal. These features have been defined by experts in the field, and are determined ahead of time, in order to best capture the RF fingerprints of the emitters the system will likely encounter. However, this use of pre-determined expert features in traditional SEI systems limits the system in a variety of ways. The work presented in this thesis investigates the ability to use Machine Learning (ML) techniques in place of the typically used expert-defined feature extraction processes, in order to improve upon traditional SEI systems. More specifically, in this thesis, two distinct approaches for performing SEI using Convolutional Neural Networks (CNNs) are developed and evaluated. These approaches are designed to have no knowledge of the emitters they may encounter and to be easily modified, unlike traditional SEI systems

<p>In this thesis, a parsimoniously parameterized digital predistorter is derived for linearization of the IQ modulation mismatch and the amplifier imperfection in the signal generator [1]. It is shown that the resulting predistorter is linear in its parameters, and thus they may be estimated by the method of least-squares. Spectrally pure signals are an indispensable requirement when the signal generator is to be used as part of a test bed. Due to the non-linear characteristic of the IQ modulator and power amplifier, distortion will be present at the output of the signal generator. The device under test was the IQ modulation mismatch and power amplifier deficiencies in the signal generator.</p><p>In [2], the dynamic range of low-cost signal generators are improved by employing model based digital pre-distortion and the designed predistorter seems to give some improvement of the dynamic range of the signal generator.</p><p>The goal of this project is to implement and verify the theory parts [1] using data program (Matlab) to improve the dynamic range of the signal generator. The design digital pre-distortion that is implemented in software so that the dynamic range of the signal generator output after predistortion is superior to that of the output prior to it. In this project, we have observed numerical<strong> </strong>problems in the proposed theory and we have found other methods to solve the problem.</p><p>The polynomial model is commonly used in power amplifier modeling and predistorter design. However, the conventional polynomial model exhibits numerical instabilities when higher order terms are included, we have used the conventional and orthogonal polynomial models. The result shows that the orthogonal polynomial model generally yield better power amplifier modeling accuracy as well as predistortion linearization performance then the conventional polynomial model.</p>

In this thesis, a parsimoniously parameterized digital predistorter is derived for linearization of the IQ modulation mismatch and the amplifier imperfection in the signal generator [1]. It is shown that the resulting predistorter is linear in its parameters, and thus they may be estimated by the method of least-squares. Spectrally pure signals are an indispensable requirement when the signal generator is to be used as part of a test bed. Due to the non-linear characteristic of the IQ modulator and power amplifier, distortion will be present at the output of the signal generator. The device under test was the IQ modulation mismatch and power amplifier deficiencies in the signal generator. In [2], the dynamic range of low-cost signal generators are improved by employing model based digital pre-distortion and the designed predistorter seems to give some improvement of the dynamic range of the signal generator. The goal of this project is to implement and verify the theory parts [1] using data program (Matlab) to improve the dynamic range of the signal generator. The design digital pre-distortion that is implemented in software so that the dynamic range of the signal generator output after predistortion is superior to that of the output prior to it. In this project, we have observed numerical problems in the proposed theory and we have found other methods to solve the problem. The polynomial model is commonly used in power amplifier modeling and predistorter design. However, the conventional polynomial model exhibits numerical instabilities when higher order terms are included, we have used the conventional and orthogonal polynomial models. The result shows that the orthogonal polynomial model generally yield better power amplifier modeling accuracy as well as predistortion linearization performance then the conventional polynomial model.

Orthogonal frequency division multiplexing (OFDM) systems with cyclic prefix (CP) can be used to protect signal from the time-variant multipath channel induced distortions. However, the presence of CP could greatly decrease the effective data rate, thus many recent research works have been focused on the multiple-input multiple-output (MIMO) OFDM systems without CP (CP-free), equipped with the space-time block codes (ST-BC). The constraint of the conventional MIMO-OFDM (without using the ST-BC) system is that the number of receive-antenna has to be greater than the transmit-antenna. In this thesis, we first consider the ST-BC MIMO-OFDM system and show that the above-mentioned constraint can be removed, such that the condition become that the receive antenna should be greater than one, that is the basic requirement for MIMO system. It is particular useful and confirm to the recently specification, e.g., 3GPP LTE (Long Term Evolution) where the system deploy the 2¡Ñ2 or 4¡Ñ4 antennas systems. This thesis also considers the effects of peak-to-average power ratio (PAPR) in the transmitter and In-phase/ Quadrature-phase (IQ) imbalance in the receiver, and solves them by using the adaptive Volterra predistorter and blind adaptive filtering approach of the nonlinear parameters estimation and compensation, along with the power measurement, respectively. After the compensator of IQ imbalance in the receiver, an equalizer under the framework of generalized sidelobe canceller (GSC) is derived for interference suppression. To further reduce the complexity of receiver implementation, the partially adaptive (PA) scheme is applied by exploiting the structural information of the signal and interference signature matrices. As demonstrated from computer simulation results, the performance of the proposed CP-free ST-BC MIMO-OFDM receiver is very similar to that obtained by the conventional CP-based ST-BC MIMO-OFDM system under either the predistortion or compensation scenario.

Due to the increasing demand of broadband capability and reconfigurability for mobile applications, there is an enormous interest to develop appropriate analog receiver front-ends. In this respect, one promising candidate group is the Six-Port-based direct conversion receiver. The presented work focuses on the investigation of Six-Port-based mobile receiver front-ends with their specific systematical signal processing. Thereby, issues of spurious interfering signals which are generated within the down conversion process of such receivers are of special interest. Based on a comprehensive description of the analog signal processing within additive frequency conversion, a reason could be identified why existing Six-Port receivers have not found any practical application in mobile communication yet – the dynamic DC-offset. With this insight compensation techniques were developed to overcome the negative influences of the dynamic DC-offset. Furthermore, this work presents novel Six-Port-based receiver architectures which, on the one hand, keep the advantages of additive mixing systems like: low power consumption, broadband capability and simplicity of implementation especially for mm-wave transmissions. On the other hand, these novel architectures comprise compensation techniques such that systematically generated spurious signals are inherently compensated in the analog part of the receiver. Moreover, the influence of impairments of phase and amplitude within the IQ-branches of a receiver was investigated. The resulting, unwanted IQ-imbalance was shown to be a mixing method (multiplicative or additive) independent spurious effect. It is suggested to compensate for IQ-imbalance in the digital part of the receiver system. This can be realized with the use of adaptive algorithms. The comparison with conventional analog receiver architectures (especially homodyne receivers) with respect to the reception of today’s and future digitally modulated transmission signals indicate the proposed Six-Port-based receiver architectures to be suitable candidates to fulfill the difficult tasks of modern mobile communication.

Due to the increasing demand of broadband capability and reconfigurability for mobile applications, there is an enormous interest to develop appropriate analog receiver front-ends. In this respect, one promising candidate group is the Six-Port-based direct conversion receiver. The presented work focuses on the investigation of Six-Port-based mobile receiver front-ends with their specific systematical signal processing. Thereby, issues of spurious interfering signals which are generated within the down conversion process of such receivers are of special interest. Based on a comprehensive description of the analog signal processing within additive frequency conversion, a reason could be identified why existing Six-Port receivers have not found any practical application in mobile communication yet – the dynamic DC-offset. With this insight compensation techniques were developed to overcome the negative influences of the dynamic DC-offset. Furthermore, this work presents novel Six-Port-based receiver architectures which, on the one hand, keep the advantages of additive mixing systems like: low power consumption, broadband capability and simplicity of implementation especially for mm-wave transmissions. On the other hand, these novel architectures comprise compensation techniques such that systematically generated spurious signals are inherently compensated in the analog part of the receiver. Moreover, the influence of impairments of phase and amplitude within the IQ-branches of a receiver was investigated. The resulting, unwanted IQ-imbalance was shown to be a mixing method (multiplicative or additive) independent spurious effect. It is suggested to compensate for IQ-imbalance in the digital part of the receiver system. This can be realized with the use of adaptive algorithms. The comparison with conventional analog receiver architectures (especially homodyne receivers) with respect to the reception of today’s and future digitally modulated transmission signals indicate the proposed Six-Port-based receiver architectures to be suitable candidates to fulfill the difficult tasks of modern mobile communication.

Les formats de modulation bidimensionnels (i.e. basés sur l’amplitude et la phase de l’onde porteuse) ont gagné depuis peu le domaine des transmissions par fibre optique grâce aux progrès conjoints de l’électronique rapide et du traitement du signal, indispensables pour réaliser les récepteurs opto-électroniques utilisant la détection cohérente des signaux optiques. Pour pallier les limites actuelles en rapidité de commutation des circuits intégrés électroniques, une voie de recherche a été ouverte il y a quelques années, consistant à utiliser des technologies optiques pour faciliter la parallélisation du traitement du signal, notamment dans l’étape d’échantillonnage ultra-rapide du signal rendu possible par des horloges optiques très performantes. Le thème principal de cette thèse concerne l’étude théorique et expérimentale de la fonction de conversion analogique-numérique (ADC) de signaux optiques par un récepteur opto-électronique cohérent, associant les étapes d’échantillonnage optique linéaire, de conversion analogique-numérique et de traitement du signal. Un prototype, utilisant une solution originale pour la source d’échantillonnage, est modélisé, réalisé et caractérisé, permettant la reconstruction temporelle de signaux optiques modulés selon divers formats : NRZ, QPSK, 16-QAM. Les limitations optiques et électroniques du système sont analysées, notamment l’impact sur la reconstruction des signaux de divers paramètres : le taux d’extinction de la source optique, les paramètres de l’ADC (bande passante BW, temps d’intégration et nombre effectif de bits ENOB). Par ailleurs, de nouveaux algorithmes de traitement du signal sont proposés dans le cadre de la transmission optique cohérente à haut débit utilisant des formats de modulation bidimensionnels (amplitude et phase) : deux solutions sont proposées pour la compensation du déséquilibre de quadrature IQ dans les transmissions mono-porteuses: une méthode originale de l’estimation du maximum du rapport signal sur bruit ainsi qu’une nouvelle structure de compensation et d’égalisation conjointes; ces deux méthodes sont validées expérimentalement et numériquement avec un signal 16-QAM. Par ailleurs, une solution améliorée de récupération de porteuse (décalage de fréquence et estimation de la phase), basée sur une décomposition harmonique circulaire de la fonction de maximum de vraisemblance logarithmique, est validée numériquement pour la première fois dans le contexte des transmissions optiques (jusqu’à une modulation de 128-QAM). Enfin les outils développés dans ce travail ont finalement permis la démonstration d’une transmission sur 100 km d’un signal QPSK à 10 Gbaud fortement limité par un bruit de phase non linéaire et régénéré optiquement à l’aide d’un limiteur de puissance préservant la phase basé sur une nanocavité de cristal photonique. / Bi-dimensional modulation formats based on amplitude and phase signal modulation, are now commonly used in optical communications thanks to breakthroughs in the field of electronic and digital signal processing (DSP) required in coherent optical receivers. Photonic solutions could compensate for nowadays limitations of electrical circuits bandwidth by facilitating the signal processing parallelization. Photonic is particularly interesting for signal sampling thanks to available stable optical clocks. The heart of the present work concerns analog-to-digital conversion (ADC) as a key element in coherent detection. A prototype of linear optical sampling using an original solution for the optical sampling source, is built and validated with the successful equivalent time reconstruction of NRZ, QPSK and 16-QAM signals. Some optical and electrical limitations of the system are experimentally and numerically analyzed, notably the extinction ratio of the optical source or the ADC parameters (bandwidth, integration time, effective number of bits ENOB). Moreover, some new DSPs tools are developed for optical transmission using bi-dimensional modulation formats (amplitude and phase). Two solutions are proposed for IQ quadrature imbalance compensation in single carrier optical coherent transmission: an original method of maximum signal-to-noise ratio estimation (MSEM) and a new structure for joint compensation and equalization; these methods are experimentally and numerically validated with 16-QAM signals. Moreover, an improved solution for carrier recovery (frequency offset and phase estimation) based on a circular harmonic expansion of a maximum loglikelihood function is studied for the first time in the context of optical telecommunications. This solution which can operate with any kind of bi-dimensional modulation format signal is numerically validated up to 128-QAM. All the DSP tools developed in this work are finally used in a demonstration of a 10 Gbaud QPSK 100 km transmission experiment, featuring a strong non-linear phase noise limitation and regenerated using a phase preserving and power limiting function based on a photonic crystal nanocavity.