Efficient and Robust Signal Detection Algorithms for the Communication Applications

Signal detection and estimation has been prevalent in signal processing and communications for many years. The relevant studies deal with the processing of information-bearing signals for the purpose of information extraction. Nevertheless, new robust and efficient signal detection and estimation techniques are still in demand since there emerge more and more practical applications which rely on them. In this dissertation work, we proposed several novel signal detection schemes for wireless communications applications, such as source localization algorithm, spectrum sensing method, and normality test. The associated theories and practice in robustness, computational complexity, and overall system performance evaluation are also provided

On the Inversion of High Energy Proton

Inversion of the K-fold stochastic autoconvolution integral equation is an elementary nonlinear problem, yet there are no de facto methods to solve it with finite statistics. To fix this problem, we introduce a novel inverse algorithm based on a combination of minimization of relative entropy, the Fast Fourier Transform and a recursive version of Efron's bootstrap. This gives us power to obtain new perspectives on non-perturbative high energy QCD, such as probing the ab initio principles underlying the approximately negative binomial distributions of observed charged particle final state multiplicities, related to multiparton interactions, the fluctuating structure and profile of proton and diffraction. As a proof-of-concept, we apply the algorithm to ALICE proton-proton charged particle multiplicity measurements done at different center-of-mass energies and fiducial pseudorapidity intervals at the LHC, available on HEPData. A strong double peak structure emerges from the inversion, barely visible without it.Comment: 29 pages, 10 figures, v2: extended analysis (re-projection ratios, 2D

Detecting non-Gaussian gravitational wave backgrounds: a unified framework

We describe a novel approach to the detection and parameter estimation of a non\textendash Gaussian stochastic background of gravitational waves. The method is based on the determination of relevant statistical parameters using importance sampling. We show that it is possible to improve the Gaussian detection statistics, by simulating realizations of the expected signal for a given model. While computationally expensive, our method improves the detection performance, leveraging the prior knowledge on the expected signal, and can be used in a natural way to extract physical information about the background. We present the basic principles of our approach, characterize the detection statistic performances in a simplified context and discuss possible applications to the detection of some astrophysical foregrounds. We argue that the proposed approach, complementarily to the ones available in literature might be used to detect suitable astrophysical foregrounds by currently operating and future gravitational wave detectors.Comment: 12 Pages, 4 Figures, Supplemental material (published on 24 March 2023

Asymptotic approximations to the error probability for detecting Gaussian signals.

Massachusetts Institute of Technology. Dept. of Electrical Engineering. Thesis. 1968. Sc.D.Vita.Bibliography: leaves 213-220.Sc.D

Advancing spaceborne tools for the characterization of planetary ionospheres and circumstellar environments

This work explores remote sensing of planetary atmospheres and their circumstellar surroundings. The terrestrial ionosphere is a highly variable space plasma embedded in the thermosphere. Generated by solar radiation and predominantly composed of oxygen ions at high altitudes, the ionosphere is dynamically and chemically coupled to the neutral atmosphere. Variations in ionospheric plasma density impact radio astronomy and communications. Inverting observations of 83.4 nm photons resonantly scattered by singly ionized oxygen holds promise for remotely sensing the ionospheric plasma density. This hypothesis was tested by comparing 83.4 nm limb profiles recorded by the Remote Atmospheric and Ionospheric Detection System aboard the International Space Station to a forward model driven by coincident plasma densities measured independently via ground-based incoherent scatter radar. A comparison study of two separate radar overflights with different limb profile morphologies found agreement between the forward model and measured limb profiles. A new implementation of Chapman parameter retrieval via Markov chain Monte Carlo techniques quantifies the precision of the plasma densities inferred from 83.4 nm emission profiles. This first study demonstrates the utility of 83.4 nm emission for ionospheric remote sensing. Future visible and ultraviolet spectroscopy will characterize the composition of exoplanet atmospheres; therefore, the second study advances technologies for the direct imaging and spectroscopy of exoplanets. Such spectroscopy requires the development of new technologies to separate relatively dim exoplanet light from parent star light. High-contrast observations at short wavelengths require spaceborne telescopes to circumvent atmospheric aberrations. The Planet Imaging Concept Testbed Using a Rocket Experiment (PICTURE) team designed a suborbital sounding rocket payload to demonstrate visible light high-contrast imaging with a visible nulling coronagraph. Laboratory operations of the PICTURE coronagraph achieved the high-contrast imaging sensitivity necessary to test for the predicted warm circumstellar belt around Epsilon Eridani. Interferometric wavefront measurements of calibration target Beta Orionis recorded during the second test flight in November 2015 demonstrate the first active wavefront sensing with a piezoelectric mirror stage and activation of a micromachine deformable mirror in space. These two studies advance our ``close-to-home'' knowledge of atmospheres and move exoplanetary studies closer to detailed measurements of atmospheres outside our solar system

Deconvolution and quantitation of severely overlapped chromatographic peaks using high performance liquid chromatography with multi-channel electrochemical detection.

The chemometric approaches employing two-dimensional time-response information were a bit more reliable in providing accurate outcomes. Each of the PCR, PLS, and SIMPLS approaches accurately predicted with 95% certainty the Epi and Dopa levels in 11 out of 20 cases.Our hypothesis was that a simple deconvolution in the potential-response domain at a carefully selected time following injection would yield sufficiently accurate determination of the two analytes to 95% confidence levels using the Student's t-test. Our simple potential-response approach was thus compared to standard and commonly employed alternative approaches.For each method investigated, we determined a mean and standard deviation for the calculated/predicted levels of both Epi and Dopa for each of the five separate mixtures. For the determinations involving only the two standard dimensions of information (i.e., time-response), this procedure was repeated for each of the four electrochemical channels separately. For the chemometric approaches using information from all the dimensions, only one such determination was available for each mixture. Likewise, the simple initially described procedure using potential-response time was only capable of providing a single outcome (mean +/- s.d.) for each of Epi and Dopa for each of the five mixtures. Finally, the individual means were compared to the known standard values in all cases using Student's t-test to determine if the means were the same as the standards at the 95% confidence level.Finally, the initially proposed single analysis of the data using the potential-response domain and Cramer's Rule for deconvolution proved to be much easier and more accurate than any of the alternatives listed above. In particular, this approach accurately predicted the content of both Epi and Dopa in all of the five mixtures examined at the 95% confidence level. At the same time, the deconvolution using matrix algebra was and is substantially simpler than any of the other alternatives examined. (Abstract shortened by UMI.)We wanted to create a simple technique that provided a high degree of accuracy in the deconvolution of two chromatographic peaks which were severely overlapped in the usual time-response domain and substantially overlapped in the potential-response domain. The two compounds we selected for investigation which fulfilled these initial criteria were epinephrine (Epi) and L-3,4-dihydroxyphenylalanine (Dopa)

Analysis of Gaussian Quadratic Forms with Application to Statistical Channel Modeling

Finalmente, en el contexto de modelado de canal, la metodología de análisis de variables propuesta permite obtener dos nuevas generalizaciones del conocido modelo de desvanecimiento kappa-mu shadowed. Estas dos nuevas distribuciones, nombradas Beckmann fluctuante y kappa-mu shadowed correlado, incluyen como casos particulares a la gran mayoría de distribuciones de desvanecimientos usadas en la literatura, abarcando desde los modelos clásicos de Rayleigh y Rice hasta otros más generales y complejos como el Beckmann y el kappa-mu. Para ambas distribuciones, se presenta su caracterización estadística de primer orden, i.e., función generadora de momentos (MGF), PDF y CDF; así como los estadísticos de segundo orden del modelo Beckmann fluctuante. Fecha de lectura de Tesis Doctoral: 24 Enero 2020En esta tesis se presenta una nueva aproximación a la distribución de de formas cuadráticas gaussianas (FCGs) no centrales tanto en variables reales como complejas. Para ello, se propone un nuevo método de análisis de variables aleatorias que, en lugar de centrarse en el estudio de la variable en cuestión, se basa en la caracterización estadística de una secuencia de variables aleatorias auxiliares convenientemente definida. Como consecuencia, las expresiones obtenidas, con independencia del grado de precisión adquirido, siempre representan una distribución válida, siendo ésta su principal ventaja. Aplicando este método, se obtienen simples expresiones recursivas para la función densidad de probabilidad (PDF) y la función de distribución (CDF) de las FCGs reales definidas positivas. En el caso de las formas complejas, esta nueva forma de análisis conduce a aproximaciones para los estadísticos de primer orden en términos de funciones elementales (exponenciales y potencias), siendo más convenientes para cálculos posteriores que otras soluciones disponibles en la literatura. La tratabilidad matemática se ejemplifica mediante el análisis de sistemas de combinación por razón máxima (MRC) sobre canales Rice correlados, proporcionando aproximaciones cerradas para la probabilidad de outage y la probabilidad de error de bit

Subcycle tomography of quantum light

Quantum light is considered to be one of the key resources of the coming second quantum revolution expected to give rise to groundbreaking technologies and applications. If the spatio-temporal and polarization structure of modes is known, the properties of quantum light are well understood. This information provides the basis for contemporary quantum optics and its applications in quantum communication and metrology. However, thinking about quantum light at the most fundamental timescale, namely the oscillation cycle of a mode or the inverse frequency of an involved photon, we realize that the corresponding picture has been missing until now. For instance, how to comprehend and characterize a single photon at this timescale? To fill this gap, we demonstrate theoretically how local quantum measurements allow to reconstruct and visualize a quantum field under study at subcycle scales, even when its temporal mode structure is a priori unknown. In particular, generation and tomography of ultrabroadband squeezed states as well as photon-subtracted states derived from them are described, incorporating also single-photon states. Our results set a cornerstone in the emerging chapter of quantum physics termed time-domain quantum optics. We expect this development to elicit new spectroscopic concepts for approaching e.g. fundamental correlations and entanglement in the dynamics of quantum matter, overcoming the temporal limitation set by the oscillation cycles of both light and elementary excitations.Comment: 43 pages, 15 figure

CMB B -mode non-Gaussianity:Optimal bispectrum estimator and Fisher forecasts

Upcoming cosmic microwave background (CMB) data can be used to explore harmonic 3-point functions that involve the B-mode component of the CMB polarization signal. We focus on bispectra describing the non-Gaussian correlation of the B-mode field and the CMB temperature anisotropies (T) and/or E-mode polarization, i.e. , , and . Such bispectra probe violations of the tensor consistency relation: the model-independent behavior of cosmological correlation functions that involve a large-wavelength tensor mode (gravitational wave). An observed violation of the tensor consistency relation would exclude a large number of inflation models. We describe a generalization of the Komatsu-Spergel-Wandelt (KSW) bispectrum estimator that allows statistical inference on this type of primordial non-Gaussianity with data of the CMB temperature and polarization anisotropies. The generalized estimator shares its statistical properties with the existing KSW estimator and retains the favorable numerical scaling with angular resolution. In this paper we derive the estimator and present a set of Fisher forecasts. We show how the forecasts scale with various experimental parameters such as lower and upper angular band-limit, relevant for e.g. the upcoming ground-based Simons Observatory experiment and proposed LiteBIRD satellite experiment. We comment on possible contaminants due to secondary cosmological and astrophysical sources.Comment: 40 pages, 7 figure