Design and implementation of a downlink MC-CDMA receiver

Cette thèse présente une étude d'un système complet de transmission en liaison descendante utilisant la technologie multi-porteuse avec l'accès multiple par division de code (Multi-Carrier Code Division Multiple Access, MC-CDMA). L'étude inclut la synchronisation et l'estimation du canal pour un système MC-CDMA en liaison descendante ainsi que l'implémentation sur puce FPGA d'un récepteur MC-CDMA en liaison descendante en bande de base. Le MC-CDMA est une combinaison de la technique de multiplexage par fréquence orthogonale (Orthogonal Frequency Division Multiplexing, OFDM) et de l'accès multiple par répartition de code (CDMA), et ce dans le but d'intégrer les deux technologies. Le système MC-CDMA est conçu pour fonctionner à l'intérieur de la contrainte d'une bande de fréquence de 5 MHz pour les modèles de canaux intérieur/extérieur pédestre et véhiculaire tel que décrit par le "Third Genaration Partnership Project" (3GPP). La composante OFDM du système MC-CDMA a été simulée en utilisant le logiciel MATLAB dans le but d'obtenir des paramètres de base. Des codes orthogonaux à facteur d'étalement variable (OVSF) de longueur 8 ont été choisis comme codes d'étalement pour notre système MC-CDMA. Ceci permet de supporter des taux de transmission maximum jusquà 20.6 Mbps et 22.875 Mbps (données non codées, pleine charge de 8 utilisateurs) pour les canaux intérieur/extérieur pédestre et véhiculaire, respectivement. Une étude analytique des expressions de taux d'erreur binaire pour le MC-CDMA dans un canal multivoies de Rayleigh a été réalisée dans le but d'évaluer rapidement et de façon précise les performances. Des techniques d'estimation de canal basées sur les décisions antérieures ont été étudiées afin d'améliorer encore plus les performances de taux d'erreur binaire du système MC-CDMA en liaison descendante. L'estimateur de canal basé sur les décisions antérieures et utilisant le critère de l'erreur quadratique minimale linéaire avec une matrice' de corrélation du canal de taille 64 x 64 a été choisi comme étant un bon compromis entre la performance et la complexité pour une implementation sur puce FPGA. Une nouvelle séquence d'apprentissage a été conçue pour le récepteur dans la configuration intérieur/extérieur pédestre dans le but d'estimer de façon grossière le temps de synchronisation et le décalage fréquentiel fractionnaire de la porteuse dans le domaine du temps. Les estimations fines du temps de synchronisation et du décalage fréquentiel de la porteuse ont été effectués dans le domaine des fréquences à l'aide de sous-porteuses pilotes. Un récepteur en liaison descendante MC-CDMA complet pour le canal intérieur /extérieur pédestre avec les synchronisations en temps et en fréquence en boucle fermée a été simulé avant de procéder à l'implémentation matérielle. Le récepteur en liaison descendante en bande de base pour le canal intérieur/extérieur pédestre a été implémenté sur un système de développement fabriqué par la compagnie Nallatech et utilisant le circuit XtremeDSP de Xilinx. Un transmetteur compatible avec le système de réception a également été réalisé. Des tests fonctionnels du récepteur ont été effectués dans un environnement sans fil statique de laboratoire. Un environnement de test plus dynamique, incluant la mobilité du transmetteur, du récepteur ou des éléments dispersifs, aurait été souhaitable, mais n'a pu être réalisé étant donné les difficultés logistiques inhérentes. Les taux d'erreur binaire mesurés avec différents nombres d'usagers actifs et différentes modulations sont proches des simulations sur ordinateurs pour un canal avec bruit blanc gaussien additif

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs in space communications, radio navigation, radio science, and ground-based radio and radar astronomy. It reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standardization activities at the Jet Propulsion Laboratory for space data and information systems

Filtering techniques for mitigating microwave oven interference on 802.11b wireless local area networks

Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 165-169).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.With the increasing popularity and assimilation of wireless devices into the everyday lives of people, the issue of their feasibility for coexisting with other radio frequency (RF) devices arises. Particularly strong interferers for the IEEE 802.11b standard are microwave ovens, since both operate at 2.4 GHz. The interference mitigation techniques all exploit the differences between the interference and the signal, since the former is sinusoidal in nature while the latter can be viewed as noise. The first mitigation filter operates in the frequency domain and filters the received signal's Fast Fourier Transform (FFT) sequence by detecting and removing peak sinusoidal components over the flat 3- dB bandwidth of the signal. The second is a Least Mean Square (LMS) Adaptive filter that produces an estimate of the interference through a recursive approximation method and subtracts it out from the received signal. The third and last is the Adaptive Notch Filter (ANF) which implements a lattice structure and has a time-varying notch frequency parameter that converges to and tracks the frequency of the interference in the received signal. The three filters are shown to produce improvements in the bit error rate (BER) and frame error rate (FER) performance of the receiver under various relative strengths of the signal with respect to the interference.by Lorenzo M. Lorilla.M.Eng.and S.B

DEVELOPMENT AND EVALUATION OF AN ENHANCED WEIGHTED FREQUENCY FOURIER LINEAR COMBINER ALGORITHM USING BANDWIDTH INFORMATION IN JOYSTICK OPERATION

Driving an electric powered wheelchair with a joystick is a complex task for the user who has a pathological tremor. Most powered wheelchairs use simple filtering algorithms to reduce the effects of tremor. These algorithms work well in most situations, but fall short in others. This study addresses the problems associated with pathological tremor associated with Cerebral Palsy (CP). The purpose of this study is to know more about the characteristics of CP tremor with time-frequency analysis and to improve joystick control with other advanced filtering algorithms.We used three estimated parameters, instantaneous frequency (IF), instantaneous bandwidth (IB), and instantaneous power (IP), from a time-frequency distribution (TFD), to characterize CP tremor and to tune a notch filter for canceling CP tremor noise from a joystick signal in an off-line experiment. From the off-line experiment, we showed that our CP tremor suppression system performed better with the information of IF, IB, and IP. We also conducted an on-line experiment in which we introduced two tremor suppression algorithms. One is Weighted-frequency Fourier Linear Combiner (WFLC), which estimates a tremor frequency and its weight, and the other is our modified WFLC, which adjusts a notch width with respect to the bandwidth of CP tremor additionally. We implemented both algorithms on the virtual wheelchair driving test along with a commonly used low-pass filter. We recruited ten subjects who have CP tremor and tested them in a virtual wheelchair driving environment. We observed that CP tremors in the joystick signal were suppressed greatly by the new filtering algorithms. We learned that the time-delay of a low-pass filter caused serious performance degradation of wheelchair driving and observed that most subjects performed better with new filtering methods than with a low-pass filter. Furthermore, since our modified WFLC algorithm was able to reduce more CP tremor noise than WFLC, we learned that it is important to consider the bandwidth information of CP tremor when designing a tremor suppression system

A Compressive Phase-Locked Loop

We develop a new method for tracking narrowband signals acquired through compressive sensing, called the compressive sensing phase-locked loop (CS-PLL). The CS-PLL enables one to track oscillating signals in very large bandwidths using a small number of measurements. Not only does the CS-PLL potentially operate below the Nyquist rate, it can extract phase and frequency information without the computational complexity normally associated with compressive sensing signal re-construction. The CS-PLL has a wide variety of applications, including but not limited to communications, phase tracking, robust control, sensing, and FM demodulation. In particular we emphasize the advantages of using this system in wideband surveillence systems. Our design modifies classical PLL designs to operate with CS-based sampling systems. Performance results are shown for PLLs operating on both real and complex data. In addition to explaining general performance tradeoffs, implementations using several different CS sampling systems are explored

Nonlinear adaptive estimation with application to sinusoidal identification

Parameter estimation of a sinusoidal signal in real-time is encountered in applications in numerous areas of engineering. Parameters of interest are usually amplitude, frequency and phase wherein frequency tracking is the fundamental task in sinusoidal estimation. This thesis deals with the problem of identifying a signal that comprises n (n ≥ 1) harmonics from a measurement possibly affected by structured and unstructured disturbances. The structured perturbations are modeled as a time-polynomial so as to represent, for example, bias and drift phenomena typically present in applications, whereas the unstructured disturbances are characterized as bounded perturbation. Several approaches upon different theoretical tools are presented in this thesis, and classified into two main categories: asymptotic and non-asymptotic methodologies, depending on the qualitative characteristics of the convergence behavior over time. The first part of the thesis is devoted to the asymptotic estimators, which typically consist in a pre-filtering module for generating a number of auxiliary signals, independent of the structured perturbations. These auxiliary signals can be used either directly or indirectly to estimate—in an adaptive way—the frequency, the amplitude and the phase of the sinusoidal signals. More specifically, the direct approach is based on a simple gradient method, which ensures Input-to-State Stability of the estimation error with respect to the bounded-unstructured disturbances. The indirect method exploits a specific adaptive observer scheme equipped with a switching criterion allowing to properly address in a stable way the poor excitation scenarios. It is shown that the adaptive observer method can be applied for estimating multi-frequencies through an augmented but unified framework, which is a crucial advantage with respect to direct approaches. The estimators’ stability properties are also analyzed by Input-to-State-Stability (ISS) arguments. In the second part we present a non-asymptotic estimation methodology characterized by a distinctive feature that permits finite-time convergence of the estimates. Resorting to the Volterra integral operators with suitably designed kernels, the measured signal is processed, yielding a set of auxiliary signals, in which the influence of the unknown initial conditions is annihilated. A sliding mode-based adaptation law, fed by the aforementioned auxiliary signals, is proposed for deadbeat estimation of the frequency and amplitude, which are dealt with in a step-by-step manner. The worst case behavior of the proposed algorithm in the presence of bounded perturbation is studied by ISS tools. The practical characteristics of all estimation techniques are evaluated and compared with other existing techniques by extensive simulations and experimental trials.Open Acces

Statistical and Graph-Based Signal Processing: Fundamental Results and Application to Cardiac Electrophysiology

The goal of cardiac electrophysiology is to obtain information about the mechanism, function, and performance of the electrical activities of the heart, the identification of deviation from normal pattern and the design of treatments. Offering a better insight into cardiac arrhythmias comprehension and management, signal processing can help the physician to enhance the treatment strategies, in particular in case of atrial fibrillation (AF), a very common atrial arrhythmia which is associated to significant morbidities, such as increased risk of mortality, heart failure, and thromboembolic events. Catheter ablation of AF is a therapeutic technique which uses radiofrequency energy to destroy atrial tissue involved in the arrhythmia sustenance, typically aiming at the electrical disconnection of the of the pulmonary veins triggers. However, recurrence rate is still very high, showing that the very complex and heterogeneous nature of AF still represents a challenging problem. Leveraging the tools of non-stationary and statistical signal processing, the first part of our work has a twofold focus: firstly, we compare the performance of two different ablation technologies, based on contact force sensing or remote magnetic controlled, using signal-based criteria as surrogates for lesion assessment. Furthermore, we investigate the role of ablation parameters in lesion formation using the late-gadolinium enhanced magnetic resonance imaging. Secondly, we hypothesized that in human atria the frequency content of the bipolar signal is directly related to the local conduction velocity (CV), a key parameter characterizing the substrate abnormality and influencing atrial arrhythmias. Comparing the degree of spectral compression among signals recorded at different points of the endocardial surface in response to decreasing pacing rate, our experimental data demonstrate a significant correlation between CV and the corresponding spectral centroids. However, complex spatio-temporal propagation pattern characterizing AF spurred the need for new signals acquisition and processing methods. Multi-electrode catheters allow whole-chamber panoramic mapping of electrical activity but produce an amount of data which need to be preprocessed and analyzed to provide clinically relevant support to the physician. Graph signal processing has shown its potential on a variety of applications involving high-dimensional data on irregular domains and complex network. Nevertheless, though state-of-the-art graph-based methods have been successful for many tasks, so far they predominantly ignore the time-dimension of data. To address this shortcoming, in the second part of this dissertation, we put forth a Time-Vertex Signal Processing Framework, as a particular case of the multi-dimensional graph signal processing. Linking together the time-domain signal processing techniques with the tools of GSP, the Time-Vertex Signal Processing facilitates the analysis of graph structured data which also evolve in time. We motivate our framework leveraging the notion of partial differential equations on graphs. We introduce joint operators, such as time-vertex localization and we present a novel approach to significantly improve the accuracy of fast joint filtering. We also illustrate how to build time-vertex dictionaries, providing conditions for efficient invertibility and examples of constructions. The experimental results on a variety of datasets suggest that the proposed tools can bring significant benefits in various signal processing and learning tasks involving time-series on graphs. We close the gap between the two parts illustrating the application of graph and time-vertex signal processing to the challenging case of multi-channels intracardiac signals

Radio frequency interference detection and mitigation techniques for navigation and Earth observation

Radio-Frequency Interference (RFI) signals are undesired signals that degrade or disrupt the performance of a wireless receiver. RFI signals can be troublesome for any receiver, but they are especially threatening for applications that use very low power signals. This is the case of applications that rely on the Global Navigation Satellite Systems (GNSS), or passive microwave remote sensing applications such as Microwave Radiometry (MWR) and GNSS-Reflectometry (GNSS-R). In order to solve the problem of RFI, RFI-countermeasures are under development. This PhD thesis is devoted to the design, implementation and test of innovative RFI-countermeasures in the fields of MWR and GNSS. In the part devoted to RFI-countermeasures for MWR applications, first, this PhD thesis completes the development of the MERITXELL instrument. The MERITXELL is a multi-frequency total-power radiometer conceived to be an outstanding platform to perform detection, characterization, and localization of RFI signals at the most common MWR imaging bands up to 92 GHz. Moreover, a novel RFI mitigation technique is proposed for MWR: the Multiresolution Fourier Transform (MFT). An assessment of the performance of the MFT has been carried out by comparison with other time-frequency mitigation techniques. According to the results, the MFT technique is a good trade-off solution among all other techniques since it can mitigate efficiently all kinds of RFI signals under evaluation. In the part devoted to RFI-countermeasures for GNSS and GNSS-R applications, first, a system for RFI detection and localization at GNSS bands is proposed. This system is able to detect RFI signals at the L1 band with a sensitivity of -108 dBm at full-band, and of -135 dBm for continuous wave and chirp-like signals when using the averaged spectrum technique. Besides, the Generalized Spectral Separation Coefficient (GSSC) is proposed as a figure of merit to evaluate the Signal-to-Noise Ratio (SNR) degradation in the Delay-Doppler Maps (DDMs) due to the external RFI effect. Furthermore, the FENIX system has been conceived as an innovative system for RFI detection and mitigation and anti-jamming for GNSS and GNSS-R applications. FENIX uses the MFT blanking as a pre-correlation excision tool to perform the mitigation. In addition, FENIX has been designed to be cross-GNSS compatible and RFI-independent. The principles of operation of the MFT blanking algorithm are assessed and compared with other techniques for GNSS signals. Its performance as a mitigation tool is proven using GNSS-R data samples from a real airborne campaign. After that, the main building blocks of the patented architecture of FENIX have been described. The FENIX architecture has been implemented in three real-time prototypes. Moreover, a simulator named FENIX-Sim allows for testing its performance under different jamming scenarios. The real-time performance of FENIX prototype has been tested using different setups. First, a customized VNA has been built in order to measure the transfer function of FENIX in the presence of several representative RFI/jamming signals. The results show how the power transfer function adapts itself to mitigate the RFI/jamming signal. Moreover, several real-time tests with GNSS receivers have been performed using GPS L1 C/A, GPS L2C, and Galileo E1OS. The results show that FENIX provides an extra resilience against RFI and jamming signals up to 30 dB. Furthermore, FENIX is tested using a real GNSS timing setup. Under nominal conditions, when no RFI/jamming signal is present, a small additional jitter on the order of 2-4 ns is introduced in the system. Besides, a maximum bias of 45 ns has been measured under strong jamming conditions (-30 dBm), which is acceptable for current timing systems requiring accuracy levels of 100 ns. Finally, the design of a backup system for GNSS in tracking applications that require high reliability against RFI and jamming attacks is proposed.Les interferències de radiofreqüència (RFI) són senyals no desitjades que degraden o interrompen el funcionament dels receptors sense fils. Les RFI poden suposar un problema per qualsevol receptor, però són especialment amenaçadores per les a aplicacions que fan servir senyals de molt baixa potència. Aquest és el cas de les aplicacions que depenen dels sistemes mundials de navegació per satèl·lit (GNSS) o de les aplicacions de teledetecció passiva de microones, com la radiometria de microones (MWR) i la reflectometria GNSS (GNSS-R). Per combatre aquest problema, sistemes anti-RFI s'estan desenvolupament actualment. Aquesta tesi doctoral està dedicada al disseny, la implementació i el test de sistemes anti-RFI innovadors en els camps de MWR i GNSS. A la part dedicada als sistemes anti-RFI en MWR, aquesta tesi doctoral completa el desenvolupament de l'instrument MERITXELL. El MERITXELL és un radiòmetre multifreqüència concebut com una plataforma excepcional per la detecció, caracterització i localització de RFI a les bandes de MWR més utilitzades per sota dels 92 GHz. A més a més, es proposa una nova tècnica de mitigació de RFI per MWR: la Transformada de Fourier amb Multiresolució (MFT). El funcionament de la MFT s'ha comparat amb el d'altres tècniques de mitigació en els dominis del temps i la freqüència. D'acord amb els resultats obtinguts, la MFT és una bona solució de compromís entre les altres tècniques, ja que pot mitigar de manera eficient tots els tipus de senyals RFI considerats. A la part dedicada als sistemes anti-RFI en GNSS i GNSS-R, primer es proposa un sistema per a la detecció i localització de RFI a les bandes GNSS. Aquest sistema és capaç de detectar senyals RFI a la banda L1 amb una sensibilitat de -108 dBm a tota la banda, i de -135 dBm per a senyals d'ona contínua i chirp fen un mitjana de l'espectre. A més a més, el Coeficient de Separació Espectral Generalitzada (GSSC) es proposa com una mesura per avaluar la degradació de la relació senyal a soroll (SNR) en els Mapes de Delay-Doppler (DDM) a causa del impacte de les RFI. La major contribució d'aquesta tesi doctoral és el sistema FENIX. FENIX és un sistema innovador de detecció i mitigació de RFI i inhibidors de freqüència per aplicacions GNSS i GNSS-R. FENIX utilitza la MFT per eliminar la interferència abans del procés de correlació amb el codi GNSS independentment del tipus de RFI. L'algoritme de mitigació de FENIX s'ha avaluat i comparat amb altres tècniques i els principals components de la seva arquitectura patentada es descriuen. Finalment, un simulador anomenat FENIX-Sim permet avaluar el seu rendiment en diferents escenaris d'interferència. El funcionament en temps real del prototip FENIX ha estat provat utilitzant diferents mètodes. En primer lloc, s'ha creat un analitzador de xarxes per a mesurar la funció de transferència del FENIX en presència de diverses RFI representatives. Els resultats mostren com la funció de transferència s'adapta per mitigar el senyal interferent. A més a més, s'han realitzat diferents proves en temps real amb receptors GNSS compatibles amb els senyals GPS L1 C/A, GPS L2C i Galileo E1OS. Els resultats mostren que FENIX proporciona una resistència addicional contra les RFI i els senyals dels inhibidors de freqüència de fins a 30 dB. A més a més, FENIX s'ha provat amb un sistema comercial de temporització basat en GNSS. En condicions nominals, sense RFI, FENIX introdueix un petit error addicional de tan sols 2-4 ns. Per contra, el biaix màxim mesurat en condicions d'alta interferència (-30 dBm) és de 45 ns, el qual és acceptable per als sistemes de temporització actuals que requereixen nivells de precisió d'uns 100 ns. Finalment, es proposa el disseny d'un sistema robust de seguiment, complementari als GNSS, per a aplicacions que requereixen alta fiabilitat contra RFI.Postprint (published version