17 research outputs found

    Wavelet Theory

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    The wavelet is a powerful mathematical tool that plays an important role in science and technology. This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations. The editor’s personal interest is the application of wavelet transform to identify time domain changes on signals and corresponding frequency components and in improving power amplifier behavior

    Adaptive Communications for Next Generation Broadband Wireless Access Systems

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    Un dels aspectes claus en el disseny i gestió de les xarxes sense fils d'accés de banda ampla és l'ús eficient dels recursos radio. Des del punt de vista de l'operador, l'ample de banda és un bé escàs i preuat que s´ha d'explotar i gestionar de la forma més eficient possible tot garantint la qualitat del servei que es vol proporcionar. Per altra banda, des del punt de vista del usuari, la qualitat del servei ofert ha de ser comparable al de les xarxes fixes, requerint així un baix retard i una baixa pèrdua de paquets per cadascun dels fluxos de dades entre la xarxa i l'usuari. Durant els darrers anys s´han desenvolupat nombroses tècniques i algoritmes amb l'objectiu d'incrementar l'eficiència espectral. Entre aquestes tècniques destaca l'ús de múltiples antenes al transmissor i al receptor amb l'objectiu de transmetre diferents fluxos de dades simultaneament sense necessitat d'augmentar l'ample de banda. Per altra banda, la optimizació conjunta de la capa d'accés al medi i la capa física (fent ús de l'estat del canal per tal de gestionar de manera optima els recursos) també permet incrementar sensiblement l'eficiència espectral del sistema.L'objectiu d'aquesta tesi és l'estudi i desenvolupament de noves tècniques d'adaptació de l'enllaç i gestió dels recursos ràdio aplicades sobre sistemes d'accés ràdio de propera generació (Beyond 3G). Els estudis realitzats parteixen de la premissa que el transmisor coneix (parcialment) l'estat del canal i que la transmissió es realitza fent servir un esquema multiportadora amb múltiples antenes al transmisor i al receptor. En aquesta tesi es presenten dues línies d'investigació, la primera per casos d'una sola antenna a cada banda de l'enllaç, i la segona en cas de múltiples antenes. En el cas d'una sola antena al transmissor i al receptor, un nou esquema d'assignació de recursos ràdio i priorització dels paquets (scheduling) és proposat i analitzat integrant totes dues funcions sobre una mateixa entitat (cross-layer). L'esquema proposat té com a principal característica la seva baixa complexitat i que permet operar amb transmissions multimedia. Alhora, posteriors millores realitzades per l'autor sobre l'esquema proposat han permès també reduir els requeriments de senyalització i combinar de forma óptima usuaris d'alta i baixa mobilitat sobre el mateix accés ràdio, millorant encara més l'eficiència espectral del sistema. En cas d'enllaços amb múltiples antenes es proposa un nou esquema que combina la selecció del conjunt optim d'antenes transmissores amb la selecció de la codificació espai- (frequència-) temps. Finalment es donen una sèrie de recomanacions per tal de combinar totes dues línies d'investigació, així con un estat de l'art de les tècniques proposades per altres autors que combinen en part la gestió dels recursos ràdio i els esquemes de transmissió amb múltiples antenes.Uno de los aspectos claves en el diseño y gestión de las redes inalámbricas de banda ancha es el uso eficiente de los recursos radio. Desde el punto de vista del operador, el ancho de banda es un bien escaso y valioso que se debe explotar y gestionar de la forma más eficiente posible sin afectar a la calidad del servicio ofrecido. Por otro lado, desde el punto de vista del usuario, la calidad del servicio ha de ser comparable al ofrecido por las redes fijas, requiriendo así un bajo retardo y una baja tasa de perdida de paquetes para cada uno de los flujos de datos entre la red y el usuario. Durante los últimos años el número de técnicas y algoritmos que tratan de incrementar la eficiencia espectral en dichas redes es bastante amplio. Entre estas técnicas destaca el uso de múltiples antenas en el transmisor y en el receptor con el objetivo de poder transmitir simultáneamente diferentes flujos de datos sin necesidad de incrementar el ancho de banda. Por otro lado, la optimización conjunta de la capa de acceso al medio y la capa física (utilizando información de estado del canal para gestionar de manera óptima los recursos) también permite incrementar sensiblemente la eficiencia espectral del sistema.El objetivo de esta tesis es el estudio y desarrollo de nuevas técnicas de adaptación del enlace y la gestión de los recursos radio, y su posterior aplicación sobre los sistemas de acceso radio de próxima generación (Beyond 3G). Los estudios realizados parten de la premisa de que el transmisor conoce (parcialmente) el estado del canal a la vez que se considera que la transmisión se realiza sobre un sistema de transmisión multiportadora con múltiple antenas en el transmisor y el receptor. La tesis se centra sobre dos líneas de investigación, la primera para casos de una única antena en cada lado del enlace, y la segunda en caso de múltiples antenas en cada lado. Para el caso de una única antena en el transmisor y en el receptor, se ha desarrollado un nuevo esquema de asignación de los recursos radio así como de priorización de los paquetes de datos (scheduling) integrando ambas funciones sobre una misma entidad (cross-layer). El esquema propuesto tiene como principal característica su bajo coste computacional a la vez que se puede aplicar en caso de transmisiones multimedia. Posteriores mejoras realizadas por el autor sobre el esquema propuesto han permitido también reducir los requisitos de señalización así como combinar de forma óptima usuarios de alta y baja movilidad. Por otro lado, en caso de enlaces con múltiples antenas en transmisión y recepción, se presenta un nuevo esquema de adaptación en el cual se combina la selección de la(s) antena(s) transmisora(s) con la selección del esquema de codificación espacio-(frecuencia-) tiempo. Para finalizar, se dan una serie de recomendaciones con el objetivo de combinar ambas líneas de investigación, así como un estado del arte de las técnicas propuestas por otros autores que combinan en parte la gestión de los recursos radio y los esquemas de transmisión con múltiples antenas.In Broadband Wireless Access systems the efficient use of the resources is crucial from many points of views. From the operator point of view, the bandwidth is a scarce, valuable, and expensive resource which must be exploited in an efficient manner while the Quality of Service (QoS) provided to the users is guaranteed. On the other hand, a tight delay and link quality constraints are imposed on each data flow hence the user experiences the same quality as in fixed networks. During the last few years many techniques have been developed in order to increase the spectral efficiency and the throughput. Among them, the use of multiple antennas at the transmitter and the receiver (exploiting spatial multiplexing) with the joint optimization of the medium access control layer and the physical layer parameters.In this Ph.D. thesis, different adaptive techniques for B3G multicarrier wireless systems are developed and proposed focusing on the SS-MC-MA and the OFDM(A) (IEEE 802.16a/e/m standards) communication schemes. The research lines emphasize into the adaptation of the transmission having (Partial) knowledge of the Channel State Information for both; single antenna and multiple antenna links. For single antenna links, the implementation of a joint resource allocation and scheduling strategy by including adaptive modulation and coding is investigated. A low complexity resource allocation and scheduling algorithm is proposed with the objective to cope with real- and/or non-real- time requirements and constraints. A special attention is also devoted in reducing the required signalling. However, for multiple antenna links, the performance of a proposed adaptive transmit antenna selection scheme jointly with space-time block coding selection is investigated and compared with conventional structures. In this research line, mainly two optimizations criteria are proposed for spatial link adaptation, one based on the minimum error rate for fixed throughput, and the second focused on the maximisation of the rate for fixed error rate. Finally, some indications are given on how to include the spatial adaptation into the investigated and proposed resource allocation and scheduling process developed for single antenna transmission

    Sensor Signal and Information Processing II

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    In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

    Advances in Computer Recognition, Image Processing and Communications, Selected Papers from CORES 2021 and IP&C 2021

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    As almost all human activities have been moved online due to the pandemic, novel robust and efficient approaches and further research have been in higher demand in the field of computer science and telecommunication. Therefore, this (reprint) book contains 13 high-quality papers presenting advancements in theoretical and practical aspects of computer recognition, pattern recognition, image processing and machine learning (shallow and deep), including, in particular, novel implementations of these techniques in the areas of modern telecommunications and cybersecurity

    Channel estimation for SISO and MIMO OFDM communications systems.

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    Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2010.Telecommunications in the current information age is increasingly relying on the wireless link. This is because wireless communication has made possible a variety of services ranging from voice to data and now to multimedia. Consequently, demand for new wireless capacity is growing rapidly at a very alarming rate. In a bid to cope with challenges of increasing demand for higher data rate, better quality of service, and higher network capacity, there is a migration from Single Input Single Output (SISO) antenna technology to a more promising Multiple Input Multiple Output (MIMO) antenna technology. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) technique has emerged as a very popular multi-carrier modulation technique to combat the problems associated with physical properties of the wireless channels such as multipath fading, dispersion, and interference. The combination of MIMO technology with OFDM techniques, known as MIMO-OFDM Systems, is considered as a promising solution to enhance the data rate of future broadband wireless communication Systems. This thesis addresses a major area of challenge to both SISO-OFDM and MIMO-OFDM Systems; estimation of accurate channel state information (CSI) in order to make possible coherent detection of the transmitted signal at the receiver end of the system. Hence, the first novel contribution of this thesis is the development of a low complexity adaptive algorithm that is robust against both slow and fast fading channel scenarios, in comparison with other algorithms employed in literature, to implement soft iterative channel estimator for turbo equalizer-based receiver for single antenna communication Systems. Subsequently, a Fast Data Projection Method (FDPM) subspace tracking algorithm is adapted to derive Channel Impulse Response Estimator for implementation of Decision Directed Channel Estimation (DDCE) for Single Input Single Output - Orthogonal Frequency Division Multiplexing (SISO-OFDM) Systems. This is implemented in the context of a more realistic Fractionally Spaced-Channel Impulse Response (FS-CIR) channel model, as against the channel characterized by a Sample Spaced-Channel Impulse Response (SS)-CIR widely assumed by other authors. In addition, a fast convergence Variable Step Size Normalized Least Mean Square (VSSNLMS)-based predictor, with low computational complexity in comparison with others in literatures, is derived for the implementation of the CIR predictor module of the DDCE scheme. A novel iterative receiver structure for the FDPM-based Decision Directed Channel Estimation scheme is also designed for SISO-OFDM Systems. The iterative idea is based on Turbo iterative principle. It is shown that improvement in the performance can be achieved with the iterative DDCE scheme for OFDM system in comparison with the non iterative scheme. Lastly, an iterative receiver structure for FDPM-based DDCE scheme earlier designed for SISO OFDM is extended to MIMO-OFDM Systems. In addition, Variable Step Size Normalized Least Mean Square (VSSNLMS)-based channel transfer function estimator is derived in the context of MIMO Channel for the implementation of the CTF estimator module of the iterative Decision Directed Channel Estimation scheme for MIMO-OFDM Systems in place of linear minimum mean square error (MMSE) criterion. The VSSNLMS-based channel transfer function estimator is found to show improved MSE performance of about -4 MSE (dB) at SNR of 5dB in comparison with linear MMSE-based channel transfer function estimator

    Novel Estimation and Detection Techniques for 5G Networks

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    The thesis presents several detection and estimation techniques that can be incorporated into the fifth-generation (5G) networks. First, the thesis presents a novel system for orthogonal frequency division multiplexing (OFDM) to estimate the channel blindly. The system is based on modulating particular pairs of subcarriers using amplitude shift keying (ASK) and phase-shift keying (PSK) adjacent in the frequency domain, which enables the realization of a decision-directed (DD) one-shot blind channel estimator (OSBCE). The performance of the proposed estimator is evaluated in terms of the mean squared error (MSE), where an accurate analytical expression is derived and verified using Monte Carlo simulation under various channel conditions. The system has also extended to exploits the channel correlation over consecutive OFDM symbols to estimate the channel parameters blindly. Furthermore, a reliable and accurate approach has been introduced to evaluate the spectral efficiency of various communications systems. The metric takes into consideration the system dynamics, QoS requirements, and design constraints. Next, a novel efficient receiver design for wireless communication systems that incorporate OFDM transmission has been proposed. The proposed receiver does not require channel estimation or equalization to perform coherent data detection. Instead, channel estimation, equalization, and data detection are combined into a single operation, and hence, the detector performs a direct data detector (D3). The performance of the proposed D3 is thoroughly analyzed theoretically in terms of bit error rate (BER), where closed-form accurate approximations are derived for several cases of interest, and validated by Monte Carlo simulations. The computational complexity of D3 depends on the length of the sequence to be detected. Nevertheless, a significant complexity reduction can be achieved using the Viterbi algorithm (VA). Finally, the thesis proposes a low-complexity algorithm for detecting anomalies in industrial steelmaking furnaces operation. The algorithm utilizes the vibration measurements collected from several built-in sensors to compute the temporal correlation using the autocorrelation function (ACF). Furthermore, the proposed model parameters are tuned by solving multi-objective optimization using a genetic algorithm (GA). The proposed algorithm is tested using a practical dataset provided by an industrial steelmaking plant

    Novel Channel Estimation Techniques for Next Generation MIMO-OFDM Wireless Communication Systems: Design and Performance Analysis

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    During the last decade, major evolutions were introduced for Multiple Input Multiple Output (MIMO) wireless communication systems. To reap the full benefits of MIMO systems, the Base Station (BS) and user equipments require accurate Channel State Information (CSI), which can be acquired using one of the two major approaches for Channel Estimation (CE): pilot-based or blind-based CE. In this thesis, a pilot-based lower complexity channel estimator for Cell-Specific Reference Signals (C-RS) and User Equipment RS (UE-RS) in LTE-A Downlink (DL) system is proposed based on using a hybrid Wiener filter. The proposed system is a sub-optimum scheme that requires 8.8% and 74.5% of the number of computations required by the optimum system and other sub-optimum systems. Moreover, a less computationally complex CE scheme based on Fast Fourier Transform (FFT) is proposed. The presented pilot-based system is validated in end-to-end LTE-A system in terms of throughput, which confirms that the proposed system is suitable for practical implementation. Next, a new blind-based CE technique based on a hybrid OFDM symbol structure for SIMO and MIMO systems is presented. It is shown that the developed system, with enough receive antennas, performs as good as pilot-based system, with similar complexity and better spectral efficiency. Finally, new Resource Grid (RG) configurations that serve the blind-based CE scheme developed for MIMO-OFDM system are presented, with the aim to improve the Mean Squared Error (MSE) performance, while minimizing the number of required receive antennas. Results show that the proposed RG configurations provide superior MSE performance, from the perspective of the blind-based CE scheme under investigation, compared to the LTE-A RG configuration. Throughout the thesis, performances of linear receivers is presented in terms of spectral efficiency as a function of Signal-to-Noise Ratio (SNR), and number of BS antennas. CE techniques are evaluated in terms of MSE as a function of SNR for different channel condi- tions. Analytical results wherever possible and, in general, simulation results are presented

    Modelling, Simulation and Data Analysis in Acoustical Problems

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    Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years

    A Statistical Approach to the Alignment of fMRI Data

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    Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods
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