Design of sequences with good correlation properties

This thesis is dedicated to exploring sequences with good correlation properties. Periodic sequences with desirable correlation properties have numerous applications in communications. Ideally, one would like to have a set of sequences whose out-of-phase auto-correlation magnitudes and cross-correlation magnitudes are very small, preferably zero. However, theoretical bounds show that the maximum magnitudes of auto-correlation and cross-correlation of a sequence set are mutually constrained, i.e., if a set of sequences possesses good auto-correlation properties, then the cross-correlation properties are not good and vice versa. The design of sequence sets that achieve those theoretical bounds is therefore of great interest. In addition, instead of pursuing the least possible correlation values within an entire period, it is also interesting to investigate families of sequences with ideal correlation in a smaller zone around the origin. Such sequences are referred to as sequences with zero correlation zone or ZCZ sequences, which have been extensively studied due to their applications in 4G LTE and 5G NR systems, as well as quasi-synchronous code-division multiple-access communication systems. Paper I and a part of Paper II aim to construct sequence sets with low correlation within a whole period. Paper I presents a construction of sequence sets that meets the Sarwate bound. The construction builds a connection between generalised Frank sequences and combinatorial objects, circular Florentine arrays. The size of the sequence sets is determined by the existence of circular Florentine arrays of some order. Paper II further connects circular Florentine arrays to a unified construction of perfect polyphase sequences, which include generalised Frank sequences as a special case. The size of a sequence set that meets the Sarwate bound, depends on a divisor of the period of the employed sequences, as well as the existence of circular Florentine arrays. Paper III-VI and a part of Paper II are devoted to ZCZ sequences. Papers II and III propose infinite families of optimal ZCZ sequence sets with respect to some bound, which are used to eliminate interference within a single cell in a cellular network. Papers V, VI and a part of Paper II focus on constructions of multiple optimal ZCZ sequence sets with favorable inter-set cross-correlation, which can be used in multi-user communication environments to minimize inter-cell interference. In particular, Paper~II employs circular Florentine arrays and improves the number of the optimal ZCZ sequence sets with optimal inter-set cross-correlation property in some cases.Doktorgradsavhandlin

New Constructions of Zero-Correlation Zone Sequences

In this paper, we propose three classes of systematic approaches for constructing zero correlation zone (ZCZ) sequence families. In most cases, these approaches are capable of generating sequence families that achieve the upper bounds on the family size ($K$) and the ZCZ width ($T$) for a given sequence period ($N$). Our approaches can produce various binary and polyphase ZCZ families with desired parameters $(N,K,T)$ and alphabet size. They also provide additional tradeoffs amongst the above four system parameters and are less constrained by the alphabet size. Furthermore, the constructed families have nested-like property that can be either decomposed or combined to constitute smaller or larger ZCZ sequence sets. We make detailed comparisons with related works and present some extended properties. For each approach, we provide examples to numerically illustrate the proposed construction procedure.Comment: 37 pages, submitted to IEEE Transactions on Information Theor

Chip and Signature Interleaving in DS CDMA Systems

Siirretty Doriast

Performance Advantages of Maximum Likelihood Methods in PRBS-Modulated Time-of-flight Energy Loss Spectroscopy

This thesis describes the design, experimental performance, and theoretical simulation of a novel time-of-flight analyzer that was integrated into a high resolution electron energy loss spectrometer (TOF-HREELS). First we examined the use of an interleaved comb chopper for chopping a continuous electron beam. Both static and dynamic behaviors were simulated theoretically and measured experimentally, with very good agreement. The finite penetration of the field beyond the plane of the chopper leads to non-ideal chopper response, which is characterized in terms of an energy corruption effect and a lead or lag in the time at which the beam responds to the chopper potential. Second we considered the recovery of spectra from pseudo-random binary sequence (PRBS) modulated TOF-HREELS data. The effects of the Poisson noise distribution and the non-ideal behavior of the interleaved comb chopper were simulated. We showed, for the first time, that maximum likelihood methods can be combined with PRBS modulation to achieve resolution enhancement, while properly accounting for the Poisson noise distribution and artifacts introduced by the chopper. Our results indicate that meV resolution, similar to that of modern high resolution electron energy loss spectrometers, can be achieved with a dramatic performance advantage over conventional, serial detection analyzers. To demonstrate the capabilities of the TOF-HREELS instrument, we made measurements on a highly oriented thin film polytetrafluoroethylene (PTFE) sample. We demonstrated that the TOF-HREELS can achieve a throughput advantage of a factor of 85 compared to the conventional HREELS instrument. Comparisons were made between the experimental results and theoretical simulations. We discuss various factors which affect inversion of PRBS modulated Time of Flight (TOF) data with the Lucy algorithm. Using simulations, we conclude that the convolution assumption was good under the conditions of our experiment. The chopper rise time, Poisson noise, and artifacts of the chopper response are evaluated. Finally, we conclude that the maximum likelihood algorithms are able to gain a multiplex advantage in PRBS modulation, despite the Poisson noise in the detector

Advanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems

Fault detection, control, and forecasting have a vital role in renewable energy systems (Photovoltaics (PV) and wind turbines (WTs)) to improve their productivity, ef?ciency, and safety, and to avoid expensive maintenance. For instance, the main crucial and challenging issue in solar and wind energy production is the volatility of intermittent power generation due mainly to weather conditions. This fact usually limits the integration of PV systems and WTs into the power grid. Hence, accurately forecasting power generation in PV and WTs is of great importance for daily/hourly efficient management of power grid production, delivery, and storage, as well as for decision-making on the energy market. Also, accurate and prompt fault detection and diagnosis strategies are required to improve efficiencies of renewable energy systems, avoid the high cost of maintenance, and reduce risks of fire hazards, which could affect both personnel and installed equipment. This book intends to provide the reader with advanced statistical modeling, forecasting, and fault detection techniques in renewable energy systems

A model study of strong correlations in Hund metals

For a long time strong electronic correlations in metals have mainly been associated with Mottness, the proximity to a Mott metal-insulator transition (MIT), where large Coulomb interactions induce the localization of charges. However, triggered by the discovery of the iron-based superconductors about ten years ago, it was realized that multi-orbital materials with only moderate Coulomb but sizeable Hund’s rule interactions – so-called Hund metals – allow for a distinct screening mechanism towards strong correlations: Hundness. Here, Hund’s rule constrains the spin rather than the charge dynamics. This discovery led to a vividly debated fundamental issue in the field of strongly correlated condensed matter systems, which is the main topic of the present thesis: what is the origin of strong correlations in the normal phase of Hund metals, Mottness or Hundness? And what are their decisive fingerprints? The goal of this dissertation is twofold. First, we present and advance our method: the numerical renormalization group (NRG) as viable real-frequency multi-band impurity solver for dynamical mean-field theory (DMFT), a common approach to tackle strongly correlated systems. Second, we apply DMFT+NRG to shed light on the Hund-metal problem raised above. In the first part of this thesis we present our state-of-the-art NRG solver, which offers direct access to data with unprecedented real-frequency spectral resolution at arbitrarily low energies and temperatures in contrast to commonly used Quantum Monte Carlo solvers. It is based on matrix product states and exploits non-abelian symmetries to reduce numerical costs. In the case of orbital symmetry, this allows us to treat multi-band models with more than two bands, and thus to tackle the Hund-metal problem for the first time with NRG. For multi-band models without orbital symmetry, an “interleaved” scheme of NRG (iNRG) was recently developed, dramatically increasing the numerical efficiency. Remarkably, the accuracy of iNRG is comparable to standard NRG, as we reveal in a detailed study. This finding establishes iNRG as a promising DMFT solver for material-specific model simulations. In the second part of this thesis we study a minimal toy model for Hund metals with DMFT+NRG, the orbital-symmetric three-band Hubbard-Hund model (3HHM) close to a lattice filling of 1/3. Our major insight is “spin-orbital separation” (SOS), a Hund’s-ruleinduced two-stage Kondo-type screening process, in which orbital screening occurs at much higher energies than spin screening. In Hund metals, i.e. far from a MIT phase boundary, SOS thus causes large electron masses by strongly reducing the coherence scale below which a Fermi liquid is formed. Further, it opens up a broad incoherent and strongly particle-hole asymmetric intermediate energy regime that reaches up to bare excitation scales. This SOS regime shows fractional power-law behavior and is characterized by resilient “Hund quasiparticles” with itinerant orbital degrees of freedom coupled non-trivially to quasi-free large spins. At zero temperature, the local density of states exhibits a two-tier quasiparticle peak on top of a broad incoherent background. In contrast, in Mott-correlated metals, i.e. close to the MIT phase boundary, the SOS regime becomes negligibly small and the Hubbard bands are well separated. These findings lead to distinct signatures of Hundness and Mottness in the temperature dependence of ARPES spectra, static local susceptibilities, resistivity, thermopower and entropy, many of which were also found in realistic simulations of the archetypal Hund- and Mott-correlated materials, Sr2RuO4 and V2O3. In summary, we provide evidence that and elucidate how Hundness evokes strong correlation effects in Hund metals. This might help to better interpret experimental results and guide superconducting theories

Biophysical modeling of a cochlear implant system: progress on closed-loop design using a novel patient-specific evaluation platform

The modern cochlear implant is one of the most successful neural stimulation devices, which partially mimics the workings of the auditory periphery. In the last few decades it has created a paradigm shift in hearing restoration of the deaf population, which has led to more than 324,000 cochlear implant users today. Despite its great success there is great disparity in patient outcomes without clear understanding of the aetiology of this variance in implant performance. Furthermore speech recognition in adverse conditions or music appreciation is still not attainable with today's commercial technology. This motivates the research for the next generation of cochlear implants that takes advantage of recent developments in electronics, neuroscience, nanotechnology, micro-mechanics, polymer chemistry and molecular biology to deliver high fidelity sound. The main difficulties in determining the root of the problem in the cases where the cochlear implant does not perform well are two fold: first there is not a clear paradigm on how the electrical stimulation is perceived as sound by the brain, and second there is limited understanding on the plasticity effects, or learning, of the brain in response to electrical stimulation. These significant knowledge limitations impede the design of novel cochlear implant technologies, as the technical specifications that can lead to better performing implants remain undefined. The motivation of the work presented in this thesis is to compare and contrast the cochlear implant neural stimulation with the operation of the physiological healthy auditory periphery up to the level of the auditory nerve. As such design of novel cochlear implant systems can become feasible by gaining insight on the question `how well does a specific cochlear implant system approximate the healthy auditory periphery?' circumventing the necessity of complete understanding of the brain's comprehension of patterned electrical stimulation delivered from a generic cochlear implant device. A computational model, termed Digital Cochlea Stimulation and Evaluation Tool (‘DiCoStET’) has been developed to provide an objective estimate of cochlear implant performance based on neuronal activation measures, such as vector strength and average activation. A patient-specific cochlea 3D geometry is generated using a model derived by a single anatomical measurement from a patient, using non-invasive high resolution computed tomography (HRCT), and anatomically invariant human metrics and relations. Human measurements of the neuron route within the inner ear enable an innervation pattern to be modelled which joins the space from the organ of Corti to the spiral ganglion subsequently descending into the auditory nerve bundle. An electrode is inserted in the cochlea at a depth that is determined by the user of the tool. The geometric relation between the stimulation sites on the electrode and the spiral ganglion are used to estimate an activating function that will be unique for the specific patient's cochlear shape and electrode placement. This `transfer function', so to speak, between electrode and spiral ganglion serves as a `digital patient' for validating novel cochlear implant systems. The novel computational tool is intended for use by bioengineers, surgeons, audiologists and neuroscientists alike. In addition to ‘DiCoStET’ a second computational model is presented in this thesis aiming at enhancing the understanding of the physiological mechanisms of hearing, specifically the workings of the auditory synapse. The purpose of this model is to provide insight on the sound encoding mechanisms of the synapse. A hypothetical mechanism is suggested in the release of neurotransmitter vesicles that permits the auditory synapse to encode temporal patterns of sound separately from sound intensity. DiCoStET was used to examine the performance of two different types of filters used for spectral analysis in the cochlear implant system, the Gammatone type filter and the Butterworth type filter. The model outputs suggest that the Gammatone type filter performs better than the Butterworth type filter. Furthermore two stimulation strategies, the Continuous Interleaved Stimulation (CIS) and Asynchronous Interleaved Stimulation (AIS) have been compared. The estimated neuronal stimulation spatiotemporal patterns for each strategy suggest that the overall stimulation pattern is not greatly affected by the temporal sequence change. However the finer detail of neuronal activation is different between the two strategies, and when compared to healthy neuronal activation patterns the conjecture is made that the sequential stimulation of CIS hinders the transmission of sound fine structure information to the brain. The effect of the two models developed is the feasibility of collaborative work emanating from various disciplines; especially electrical engineering, auditory physiology and neuroscience for the development of novel cochlear implant systems. This is achieved by using the concept of a `digital patient' whose artificial neuronal activation is compared to a healthy scenario in a computationally efficient manner to allow practical simulation times.Open Acces

Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

Applications of microprocessors in digital high frequency radio communications

This thesis describes the application of VLSI devices to channel evaluation and communication techniques over ionospheric radio paths. Digital signal processing techniques using microprocessors and charge coupled devices are described in detail. A novel method for observing interference and fading patterns on HF channels is described. Error control coding schemes and digital modulation techniques are combined in a design for an adaptive modem for use over HF radio links. Results of narrow-band interference measurements, error patterns and coding performance are presented