629 research outputs found

    Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

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    The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

    Optical Wireless Communications Using Intelligent Walls

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    This chapter is devoted to discussing the integration of intelligent reflecting surfaces (IRSs), or intelligent walls, in optical wireless communication (OWC) systems. IRS technology is a revolutionary concept that enables communication systems to harness the surrounding environment to control the propagation of light signals. Based on this, specific key performance indicators could be achieved by altering the electromagnetic response of the IRSs. In the following, we discuss the background theory and applications of IRSs and present a case study for an IRS-assisted indoor light-fidelity (LiFi) system. We then highlight some of the challenges related to this emerging concept and elaborate on future research directions

    Advanced Filter Solutions for High-performance Millimetre and Submillimetre-wave Systems

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    This thesis is devoted to the investigation of advanced filter design solutions for high-performance millimetre and submillimetre-wave systems. Each of the proposed design solutions are enabled using waveguide-based technologies with the aim of advancing future generations of satellite communications, radar, and remote sensing. As trends for frequency allocations move to higher and higher frequency bands, engineers are faced with increasingly complex challenges such as the degradation of component performance, the inability to correctively tune the performance, or scenarios that all together make circuits infeasible. In light of these challenges, this work seeks to advance the current literature on filter design and proposes many unique design solutions for overcoming manufacturing and accuracy limitations, reducing the transmission losses, and reducing the overall design complexity. Each of the proposed filter solutions that are presented in this thesis are based on either a novel structural design or a novel technology. Each of the proposed designs are presented with functional prototypes as a means of verifying the theory. In the majority of cases, prototypes have been manufactured using high-precision computer numerical control (CNC) milling, and in several articles, exploratory activities with the use of alternative technologies such as stereolithography (SLA) 3D-printing and deep-reactive ion etching (DRIE) are presented. Prior to the presentation of the filter designs, an overview on the design and synthesis of millimetre-wave filters and diplexers is provided and serves as a foundation for the coupling matrix descriptions of symmetric and asymmetric resonator designs throughout this work

    Twenty-five years of sensor array and multichannel signal processing: a review of progress to date and potential research directions

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    In this article, a general introduction to the area of sensor array and multichannel signal processing is provided, including associated activities of the IEEE Signal Processing Society (SPS) Sensor Array and Multichannel (SAM) Technical Committee (TC). The main technological advances in five SAM subareas made in the past 25 years are then presented in detail, including beamforming, direction-of-arrival (DOA) estimation, sensor location optimization, target/source localization based on sensor arrays, and multiple-input multiple-output (MIMO) arrays. Six recent developments are also provided at the end to indicate possible promising directions for future SAM research, which are graph signal processing (GSP) for sensor networks; tensor-based array signal processing, quaternion-valued array signal processing, 1-bit and noncoherent sensor array signal processing, machine learning and artificial intelligence (AI) for sensor arrays; and array signal processing for next-generation communication systems

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Echo Particle Image/Tracking Velocimetry: Technical Development and In Vivo Applications in Cardiovascular and Cerebrovascular Flows

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    Contrast-enhanced ultrasound (CEUS) imaging utilizes intravascular echogenic microbubbles (1-5ÎĽm in diameter) to visualize the blood flow in various organs. In this dissertation, we develop and implement techniques for analyzing the motions of microbubbles to quantify cardiovascular and cerebrovascular flows. Obtaining accurate bubble center locations from noisy CEUS images is a primary challenge. Since the bubble trace is typically modeled as a point scatter convolved with a point spread function (PSF), techniques including blind deconvolution, supervised, and self-supervised learning are introduced and calibrated for identifying the PSF and locating the bubble center. The enhanced CEUS images enable echo particle image velocimetry (echo-PIV) for characterizing 2D cardiovascular flows, and the global-optimized Kalman filter-based echo particle tracking velocimetry (echo-PTV) for determining bubble trajectories which are subsequently used for mapping the cerebral and ocular microcirculation at a spatial resolution of 20ÎĽm. These techniques are applied to two applications. First, echo-PIV is used for monitoring the aortic root flow in an adult pig undergoing veno-arterial extracorporeal membrane oxygenation (VA-ECMO), a life support technology whose parameters can be optimized based on the aortic root hemodynamics. Phase-averaged and instantaneous flow fields show that, for the pig with severe myocardial ischemia, the cardiac ejection velocity, velocity-time integral, and mean arterial pressure (MAP) reach their peak at an ECMO flow rate of 3.0L/min, indicating an optimal flow rate that provides adequate support. Second, we investigate non-invasive methods for estimating intracranial pressure (ICP), a critical parameter for hydrocephalus patients that cannot be invasively measured safely. Echo-PTV is used to map cerebral and ocular microcirculation of pediatric hydrocephalus porcine models for inferring ICP. Results show that accounting for pulse pressure, highly correlated relationships between ICP and cortical microcirculation density are obtained with correlation coefficients beyond 0.85. For cerebral ischemia, nondimensionalized cortical micro-perfusion decreases by an order of magnitude when the ICP exceeds 50% of MAP. Moreover, retinal microcirculation also shows a highly correlated relationship with ICP when accounting for pulse pressure. These findings suggest that CEUS-based microcirculation measurement is a plausible noninvasive method for evaluating the ICP and detecting brain ischemia

    BDS GNSS for Earth Observation

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    For millennia, human communities have wondered about the possibility of observing phenomena in their surroundings, and in particular those affecting the Earth on which they live. More generally, it can be conceptually defined as Earth observation (EO) and is the collection of information about the biological, chemical and physical systems of planet Earth. It can be undertaken through sensors in direct contact with the ground or airborne platforms (such as weather balloons and stations) or remote-sensing technologies. However, the definition of EO has only become significant in the last 50 years, since it has been possible to send artificial satellites out of Earth’s orbit. Referring strictly to civil applications, satellites of this type were initially designed to provide satellite images; later, their purpose expanded to include the study of information on land characteristics, growing vegetation, crops, and environmental pollution. The data collected are used for several purposes, including the identification of natural resources and the production of accurate cartography. Satellite observations can cover the land, the atmosphere, and the oceans. Remote-sensing satellites may be equipped with passive instrumentation such as infrared or cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the Earth’s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and Medium Earth Orbit (MEO), thus covering the entire Earth’s surface in a certain scan time (properly called ’temporal resolution’), i.e., in a certain number of orbits around the Earth. The first remote-sensing satellites were the American NASA/USGS Landsat Program; subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing satellite), RapidEye, the French SPOT (Satellite Pour l’Observation de laTerre), and the Canadian RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the Chinese BuFeng-1 and Fengyun-3 series. Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers worldwide for a multitude of Earth monitoring and exploration applications. On the other hand, over the past 40 years, GNSSs have become an essential part of many human activities. As is widely noted, there are currently four fully operational GNSSs; two of these were developed for military purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation Satellite System (IRNSS/NavIC), will become available in the next few years, which will have enormous potential for scientific applications and geomatics professionals. In addition to their traditional role of providing global positioning, navigation, and timing (PNT) information, GNSS navigation signals are now being used in new and innovative ways. Across the globe, new fields of scientific study are opening up to examine how signals can provide information about the characteristics of the atmosphere and even the surfaces from which they are reflected before being collected by a receiver. EO researchers monitor global environmental systems using in situ and remote monitoring tools. Their findings provide tools to support decision makers in various areas of interest, from security to the natural environment. GNSS signals are considered an important new source of information because they are a free, real-time, and globally available resource for the EO community

    Efficient Covariance Matrix Reconstruction with Iterative Spatial Spectrum Sampling

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    This work presents a cost-effective technique for designing robust adaptive beamforming algorithms based on efficient covariance matrix reconstruction with iterative spatial power spectrum (CMR-ISPS). The proposed CMR-ISPS approach reconstructs the interference-plus-noise covariance (INC) matrix based on a simplified maximum entropy power spectral density function that can be used to shape the directional response of the beamformer. Firstly, we estimate the directions of arrival (DoAs) of the interfering sources with the available snapshots. We then develop an algorithm to reconstruct the INC matrix using a weighted sum of outer products of steering vectors whose coefficients can be estimated in the vicinity of the DoAs of the interferences which lie in a small angular sector. We also devise a cost-effective adaptive algorithm based on conjugate gradient techniques to update the beamforming weights and a method to obtain estimates of the signal of interest (SOI) steering vector from the spatial power spectrum. The proposed CMR-ISPS beamformer can suppress interferers close to the direction of the SOI by producing notches in the directional response of the array with sufficient depths. Simulation results are provided to confirm the validity of the proposed method and make a comparison to existing approachesComment: 14 pages, 8 figure
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