Spectrum shaping and its application: spread-spectrum clock generator and circuits for ultra wide band

Electromagnetic spectrum can be identified as a resource for the designer, as well as for the manufacturer, from two complementary points of view: first, because it is a good in great demand by many different kind of applications; second, because despite its scarce availability, it may be advantageous to use more spectrum than necessary. This is the case of Spread-Spectrum Systems, those systems in which the transmitted signal is spread over a wide frequency band, much wider, in fact, than the minimum bandwidth required to transmit the information being sent. Part I of this dissertation deals with Spread-Spectrum Clock Generators (SSCG) aiming at reducing Electro Magnetic Interference (EMI) of clock signals in integrated circuits (IC) design. In particular, the modulation of the clock and the consequent spreading of its spectrum are obtained through a random modulating signal outputted by a chaotic map, i.e. a discrete-time dynamical system showing chaotic behavior. The advantages offered by this kind of modulation are highlighted. Three different prototypes of chaos-based SSCG are presented in all their aspects: design, simulation, and post-fabrication measurements. The third one, operating at a frequency equal to 3GHz, aims at being applied to Serial ATA, standard de facto for fast data transmission to and from Hard Disk Drives. The most extreme example of spread-spectrum signalling is the emerging ultra-wideband (UWB) technology, which proposes the use of large sections of the radio spectrum at low amplitudes to transmit high-bandwidth digital data. In part II of the dissertation, two UWB applications are presented, both dealing with the advantages as well as with the challenges of a wide-band system, namely: a chaos-based sequence generation method for reducing Multiple Access Interference (MAI) in Direct Sequence UWB Wireless-Sensor-Networks (WSNs), and design and simulations of a Low-Noise Amplifier (LNA) for impulse radio UWB. This latter topic was studied during a study-abroad period in collaboration with Delft University of Technology, Delft, Netherlands.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Non Invasive Tools for Early Detection of Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic.

Head to head comparison of optical coherence tomography, intravascular ultrasound echogenicity and virtual histology for the detection of changes in polymeric struts over time: insights from the ABSORB trial

To analyse and to compare the changes in the various optical coherence tomography (OCT), echogenicity and intravascular ultrasound virtual histology (VH) of the everolimus-eluting bioresorbable scaffold (ABSORB) degradation parameters during the first 12 months after ABSORB implantation. In the ABSORB study, changes in the appearance of the ABSORB scaffold were monitored over time using various intracoronary imaging modalities. The scaffold struts exhibited a progressive change in their black core area by OCT, in their ultrasound derived grey level intensity quantified by echogenicity, and in their backscattering ultrasound signal, identified as "pseudo dense-calcium" (DC) by VH.

Compressed sensing based cyclic feature spectrum sensing for cognitive radios

Spectrum sensing is currently one of the most challenging design problems in cognitive radio. A robust spectrum sensing technique is important in allowing implementation of a practical dynamic spectrum access in noisy and interference uncertain environments. In addition, it is desired to minimize the sensing time, while meeting the stringent cognitive radio application requirements. To cope with this challenge, cyclic spectrum sensing techniques have been proposed. However, such techniques require very high sampling rates in the wideband regime and thus are costly in hardware implementation and power consumption. In this thesis the concept of compressed sensing is applied to circumvent this problem by utilizing the sparsity of the two-dimensional cyclic spectrum. Compressive sampling is used to reduce the sampling rate and a recovery method is developed for re- constructing the sparse cyclic spectrum from the compressed samples. The reconstruction solution used, exploits the sparsity structure in the two-dimensional cyclic spectrum do-main which is different from conventional compressed sensing techniques for vector-form sparse signals. The entire wideband cyclic spectrum is reconstructed from sub-Nyquist-rate samples for simultaneous detection of multiple signal sources. After the cyclic spectrum recovery two methods are proposed to make spectral occupancy decisions from the recovered cyclic spectrum: a band-by-band multi-cycle detector which works for all modulation schemes, and a fast and simple thresholding method that works for Binary Phase Shift Keying (BPSK) signals only. In addition a method for recovering the power spectrum of stationary signals is developed as a special case. Simulation results demonstrate that the proposed spectrum sensing algorithms can significantly reduce sampling rate without sacrifcing performance. The robustness of the algorithms to the noise uncertainty of the wireless channel is also shown.

A new method to monitor visual field defects caused by photoreceptor degeneration by quantitative optical coherence tomography

PURPOSE: To correlate the dimension of the visual field (VF) tested by Goldman kinetic perimetry with the extent of visibility of the highly reflective layer between inner and outer segments of photoreceptors (IOS) seen in optical coherence tomography (OCT) images in patients with retinitis pigmentosa (RP). METHODS: In a retrospectively designed cross-sectional study, 18 eyes of 18 patients with RP were examined with OCT and Goldmann perimetry using test target I4e and compared with 18 eyes of 18 control subjects. A-scans of raw scan data of Stratus OCT images (Carl Zeiss Meditec, AG, Oberkochen, Germany) were quantitatively analyzed for the presence of the signal generated by the highly reflective layer between the IOS in OCT images. Starting in the fovea, the distance to which this signal was detectable was measured. Visual fields were analyzed by measuring the distance from the center point to isopter I4e. OCT and visual field data were analyzed in a clockwise fashion every 30 degrees , and corresponding measures were correlated. RESULTS: In corresponding alignments, the distance from the center point to isopter I4e and the distance to which the highly reflective signal from the IOS can be detected correlate significantly (r = 0.75, P < 0.0001). The greater the distance in VF, the greater the distance measured in OCT. CONCLUSIONS: The authors hypothesize that the retinal structure from which the highly reflective layer between the IOS emanates is of critical importance for visual and photoreceptor function. Further research is warranted to determine whether this may be useful as an objective marker of progression of retinal degeneration in patients with RP.

Photonics Crystals: The Future of Microwave Signal Processing

The ability of cryogenic photonic crystals to carry out high performance microwave signal processing operations has been developed into systems that can: rapidly record broadband microwave spectra with fine resolution and high dynamic range; search for patterns in 40 gigabits per second data streams; and communicate via spread- spectrum signals that are well below the noise floor. The basic concepts of the technology and its many applications, along with an overview of university-industry partnerships and the growing photonics industry in Bozeman, will be presented.

Automatic estimation of noise parameters in Fourier-domain optical coherence tomography cross sectional images using statistical information

We present an application and sample independent method for the automatic discrimination of noise and signal in optical coherence tomography Bscans. The proposed algorithm models the observed noise probabilistically and allows for a dynamic determination of image noise parameters and the choice of appropriate image rendering parameters. This overcomes the observer variability and the need for a priori information about the content of sample images, both of which are challenging to estimate systematically with current systems. As such, our approach has the advantage of automatically determining crucial parameters for evaluating rendered image quality in a systematic and task independent way. We tested our algorithm on data from four different biological and nonbiological samples (index finger, lemon slices, sticky tape, and detector cards) acquired with three different experimental spectral domain optical coherence tomography (OCT) measurement systems including a swept source OCT. The results are compared to parameters determined manually by four experienced OCT users. Overall, our algorithm works reliably regardless of which system and sample are used and estimates noise parameters in all cases within the confidence interval of those found by observers.

Time-Resolved Ultra–High Resolution Optical Coherence Tomography for Real-Time Monitoring of Selective Retina Therapy

Purpose: Selective retina therapy (SRT) is a novel treatment for retinal pathologies, solely targeting the retinal pigment epithelium (RPE). During SRT, the detection of an immediate tissue reaction is challenging as tissue effects remain limited to intracellular RPE photodisruption. Time-resolved ultra-high axial resolution optical coherence tomography (OCT) is thus evaluated for the monitoring of dynamic optical changes at and around the RPE during SRT. Methods: An experimental OCT system with an ultra-high axial resolution of 1.78 µm was combined with an SRT system and time-resolved OCT M-scans of the target area were recorded from four patients undergoing SRT. OCT scans were analyzed and OCT morphology was correlated with findings in fluorescein angiography, fundus photography and cross-sectional OCT. Results: In cases where the irradiation caused RPE damage proven by fluorescein angiography, the lesions were well discernible in time-resolved OCT images but remained invisible in fundus photography and cross-sectional OCT acquired after treatment. If RPE damage was introduced, all applied SRT pulses led to detectable signal changes in the time-resolved OCT images. The extent of optical signal variation seen in the OCT data appeared to scale with the applied SRT pulse energy. Conclusion: The first clinical results proved that successful SRT irradiation induces detectable changes in the OCT M-scan signal while it remains invisible in conventional ophthalmoscopic imaging. Thus, real-time high-resolution OCT is a promising modality to monitor and analyze tissue effects introduced by selective retina therapy and may be used to guide SRT in an automatic feedback mode.

Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude.

This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89%, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP(LF)(HR) ) oscillations and cardiorespiratory coherence (MP(LF)(Coher)), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

Expanded Clinical Spectrum of Multiple Evanescent White Dot Syndrome with Multimodal Imaging

PURPOSE: To evaluate and characterize multiple evanescent white dot syndrome abnormalities with modern multimodal imaging modalities. METHODS: This retrospective cohort study evaluated fundus photography, fluorescein angiography, indocyanine green angiography, optical coherence tomography, enhanced depth imaging optical coherence tomography, short-wavelength autofluorescence, and near-infrared autofluorescence. RESULTS: Thirty-four multiple evanescent white dot syndrome patients with mean age of 28.7 years were studied (range, 14-49 years). Twenty-six patients were women, and eight were men. Initial mean visual acuity was 0.41 logMAR. Final mean visual acuity was 0.03 logMAR. Fluorescein angiography shows a variable number of mid retinal early fluorescent dots distributed in a wreathlike pattern, which correlate to fundus photography, fundus autofluorescence, and indocyanine green angiography. Indocyanine green angiography imaging shows the dots and also hypofluorescent, deeper, and larger spots, which are occasionally confluent, demonstrating a large plaque of deep retinal hypofluorescence. Optical coherence tomography imaging shows multifocal debris centered at and around the ellipsoid layer, corresponding to the location of spots seen with photography, indocyanine green angiography, and fluorescein angiography. Protrusions of the hyperreflectant material from the ellipsoid layer toward the outer nuclear layer correspond to the location of dots seen with photography, indocyanine green angiography, and fluorescein angiography. CONCLUSION: Multimodal imaging analysis of the retina in patients with multiple evanescent white dot syndrome shows additional features that may help in the diagnosis of the disease and in further understanding its etiology. Multiple evanescent white dot syndrome is predominantly a disease of the outer retina, centered at the ellipsoid zone, but also involving the interdigitation zone and the outer nuclear layer.

NOVEL PHANTOMS AND POST-PROCESSING FOR DIFFUSION SPECTRUM IMAGING

High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.

Mach-Zehnder interferometer based on all-fiber multimode interference device for DPSK signal demodulation

Differential Phase Shift Keying (DPSK) modulation format has been shown as a robust solution for next-generation optical transmission systems. One key device enabling such systems is the delay interferometer, converting the signal phase information into intensity modulation to be detected by the photodiodes. Usually, Mach-Zehnder interferometer (MZI) is used for demodulating DPSK signals. In this paper, we developed an MZI which is based on all-fiber Multimode Interference (MI) structure: a multimode fiber (MMF) located between two single-mode fibers (SMF) without any transition zones. The standard MZI is not very stable since the two beams go through two different paths before they recombine. In our design the two arms of the MZI are in the same fiber, which will make it less temperature-sensitive than the standard MZI. Performance of such MZI will be analyzed from transmission spectrum. Finally such all-fiber MI-based MZI (MI-MZI) is used to demodulate 10 Gbps DPSK signals. The demodulated signals are analyzed from eye diagram and bit error rate (BER).

Optical signal impairment study of cascaded optical filters in 40 Gbps DQPSK and 100 Gbps PM-DQPSK systems

Optical filters are crucial elements in optical communications. The influence of cascaded filters in the optical signal will affect the communications quality seriously. In this paper we will study and simulate the optical signal impairment caused by different kinds of filters which include Butterworth, Bessel, Fiber Bragg Grating (FBG) and Fabry-Perot (FP). Optical signal impairment is analyzed from an Eye Opening Penalty (EOP) and optical spectrum point of view. The simulation results show that when the center frequency of all filters aligns with the laser’s frequency, the Butterworth has the smallest influence to the signal while the F-P has the biggest. With a -1dB EOP, the amount of cascaded Butterworth optical filters with a bandwidth of 50 GHz is 18 in 40 Gbps NRZ-DQPSK systems and 12 in 100 Gbps PMNRZ- DQPSK systems. The value is reduced to 9 and 6 respectively for Febry-Perot optical filters. In the situation of frequency misalignment, the impairment caused by filters is more serious. Our research shows that with a frequency deviation of 5 GHz, only 12 and 9 Butterworth optical filters can be cascaded in 40 Gbps NRZ-DQPSK and 100 Gbps PM-NRZ-DQPSK systems respectively. We also study the signal impairment caused by different orders of the Butterworth filter model. Our study shows that although the higher-order has a smaller clipping effect in the transmission spectrum, it will introduce a more serious phase ripple which seriously affects the signal. Simulation result shows that the 2nd order Butterworth filter has the best performance.

Analysis of signal impairment and crosstalk penalty induced by different types of optical filters in 100 Gbps PM-DQPSK based systems

Optical filters are crucial elements in optical communication networks. Their influence toward the optical signal will affect the communication quality seriously. In this paper we will study and simulate the optical signal impairment and crosstalk penalty caused by different kinds of filters, which include Butterworth, Bessel, Fiber Bragg Grating (FBG) and Fabry-Perot (F-P). Signal impairment from filter concatenation effect and crosstalk penalty from out-band and in-band are analyzed from Q-penalty, eye opening penalty (EOP) and optical spectrum. The simulation results show that signal impairment and crosstalk penalty induced by the Butterworth filter is the minimum among these four types of filters. Signal impairment caused by filter concatenation effect shows that when center frequency of all filters is aligned perfectly with the laser's frequency, 12 50-GHz Butterworth filters can be cascaded, with 1-dB EOP. This value is reduced to 9 when the center frequency is misaligned with 5 GHz. In the 50-GHz channel spacing DWDM networks, total Q-penalty induced by a pair of Butterworth filters based demultiplexer and multiplexer is lower than 0.5 dB when the filter bandwidth is in the range of 42-46 GHz.