CDMA is the multiple access technique selected for the 3G mobile communications systems and it has a significant role in the research beyond 3G systems. CDMA systems over wireless channels have to cope with fading multipath propagation, which makes the channel estimation an important issue in CDMA receivers. Despite a significant amount of scientific literature on CDMA receivers, there are still open problems regarding the multipath delay and coefficient estimation in hostile environments and the design of low-complexity DSP-based channel estimators for CDMA applications. Good multipath delay estimation techniques can also find their applicability in mobile phone positioning, which is an area with many challenging questions. Additionally, theoretical measures of performance in CDMA detection in the presence of fading multipath channels have mainly been derived for ideal channel estimators. However, developing such analytical models in the presence of channel estimation ...

This thesis deals with the synchronization of one or several replicas of a known signal received in a scenario with multipath propagation and directional interference. A connecting theme along this work is the systematic application of the maximum likelihood (ML) principle together with a signal model in which the spatial signatures are unstructured and the noise term is Gaussian- distributed with an unknown correlation matrix. This last assumption is key in obtaining estimators that are capable of mitigating the disturbing signals that exhibit a certain structure, and this is achieved without resorting to the estimation of the parameters of those signals. On the other hand, the assumption of unstructured spatial signatures is interesting from a practical standpoint and facilitates the estimation problem since the estimates of these signatures can be obtained in closed form. This constitutes a first step towards ...

The multi-frequency Global Navigation Satellite System (GNSS) signals are designed to overcome the inherent performance limitations of single-frequency receivers. However, the processing of multiple frequency signals in a time-varying GNSS signal environment which are potentially affected by multipath, ionosphere scintillation, blockage, and interference is quite challenging, as each signal is influenced differently by channel effects according to its Radio Frequency (RF). In order to get the benefit of synchronously/coherently generated multiple frequency signals, advanced receiver signal processing techniques need to be developed. The aim of this research thesis is to extract the best performance benefits out of multifrequency GNSS signals in a time-varying GNSS signal environment. To accomplish this objective, it is necessary to analyze the multi-frequency signal characteristics and to investigate suitable signal processing algorithms in order to enable the best performance of each signal. The GNSS receiver position ...

Applications for the new generations of Global Navigation Satellite Systems (GNSS) are developing rapidly and attract a great interest. Both US Global Positioning System (GPS) and European Galileo signals use Direct Sequence-Code Division Multiple Access (DS-CDMA) technology, where code and frequency synchronization are important stages at the receiver. The GNSS receivers estimate jointly the code phase and the Doppler spread through a two-dimensional searching process in time-frequency plane. Since both GPS and Galileo systems will send several signals on the same carriers, a new modulation type - the Binary Offset Carrier (BOC) modulation, has been selected. The main target of this modulation is to provide a better spectral separation with the existing BPSK-modulated GPS signals, while allowing optimal usage of the available bandwidth for different GNSS signals. The BOC modulation family includes several BOC variants, such as sine BOC (SinBOC), ...

Localization, separation and tracking of acoustic sources are ancient challenges that lots of animals and human beings are doing intuitively and sometimes with an impressive accuracy. Artificial methods have been developed for various applications and conditions. The majority of those methods are centralized, meaning that all signals are processed together to produce the estimation results. The concept of distributed sensor networks is becoming more realistic as technology advances in the fields of nano-technology, micro electro-mechanic systems (MEMS) and communication. A distributed sensor network comprises scattered nodes which are autonomous, self-powered modules consisting of sensors, actuators and communication capabilities. A variety of layout and connectivity graphs are usually used. Distributed sensor networks have a broad range of applications, which can be categorized in ecology, military, environment monitoring, medical, security and surveillance. In this dissertation we develop algorithms for distributed sensor networks ...

Wireless broadband communications for users moving at vehicular speed is a cor- nerstone of future fourth generation (4G) mobile communication systems. We inves- tigate a multi-carrier (MC) code division multiple access (CDMA) system which is based on orthogonal frequency division multiplexing (OFDM). A spreading sequence is used in the frequency domain in order to distinguish individual users and to take advantage of the multipath diversity of the wireless channel. The transmission is block oriented. A block consists of OFDM pilot and OFDM data symbols. At pedestrian velocities the channel can be modelled as block fading. We ap- ply iterative multi-user detection and channel estimation. In iterative receivers soft symbols are derived from the output of an soft-input soft-output decoder. These soft symbols are used in order to reduce the interference from other users and to enhance the channel estimates. We ...

This thesis considers the development of synchronization and signal processing techniques for digital communication receivers, which is greatly influenced by the digital revolution of electronic systems. Eventhough synchronization concepts are well studied and established in the literature, there is always a need for new algorithms depending on new system requirements and new trends in receiver architecture design. The new trend of using digital receivers where the sampling of the baseband signal is performed by a free running oscillator reduces the analog components by performing most of the functions digitally, which increases the flexibility, configurability, and integrability of the receiver. Also, this new design approach contributes greatly to the software radio (SWR) concept which is the natural progression of digital radio receivers towards multimode, multistandard terminals where the radio functionalities are defined by software. The first part of this research work ...

In multiuser ultra-wideband (UWB) systems, a large number of multipath components (MPCs) are introduced by the channel. One of the main challenges for the receiver is to effectively suppress the interference with affordable complexity. In this thesis, we focus on the linear adaptive interference suppression algorithms for the direct-sequence ultrawideband (DS-UWB) systems in both time-domain and frequency-domain. In the time-domain, symbol by symbol transmission multiuser DS-UWB systems are considered. We first investigate a generic reduced-rank scheme based on the concept of joint and iterative optimization (JIO) that jointly optimizes a projection vector and a reduced-rank filter by using the minimum mean-squared error (MMSE) criterion. A low-complexity scheme, named Switched Approximations of Adaptive Basis Functions (SAABF), is proposed as a modification of the generic scheme, in which the complexity reduction is achieved by using a multi-branch framework to simplify the structure ...

Mobile communication networks of the third and future generations are designed to offer high-data rate services like video-telephony and data-transfer. The current Rake receiver architecture will create a shortage in available bandwidth offered to the users. This is not due to a shortage in spectrum but results from inefficient receiver architectures. Spectral efficiency can be increased considerably through multi-user detection techniques in the receiver algorithms. The present thesis investigates iterative re- ceivers for encoded CDMA transmission in the uplink. The iterative receiver is a suboptimal receiver algorithm with manageable complexity. It consists of an inter- ference mitigating multi-user detector, a bank of single-user decoders, and a channel estimator. Instead of deciding on the transmitted symbols right after the first decod- ing, the receiver feeds back tentative decision symbols to mitigate multiple-access interference in the next iteration. Similarly, soft decision symbols ...

Machine learning and deep learning techniques have emerged as powerful tools for addressing complex challenges across diverse domains. These methodologies are powerful because they extract patterns and insights from large and complex datasets, automate decision-making processes, and continuously improve over time. They enable us to observe and quantify patterns in data that a normal human would not be able to capture, leading to deeper insights and more accurate predictions. This dissertation presents two research papers that leverage these methodologies to tackle distinct yet interconnected problems in neuroimaging and computer vision for the quantification of human health. The first investigation, "Age prediction using resting-state functional MRI," addresses the challenge of understanding brain aging. By employing the Least Absolute Shrinkage and Selection Operator (LASSO) on resting-state functional MRI (rsfMRI) data, we identify the most predictive correlations related to brain age. Our study, ...

Code division multiple access (CDMA) techniques have been widely employed by different wireless systems with many advantages. However, the performance of these systems is limited by interference. A number of different interference suppression techniques have been proposed, including multiuser detection, beamforming, adaptive supervised and blind algorithms, and transmit processing techniques requiring a limited feedback channel. Recently, CDMA techniques have also been combined with multicarrier and multiantenna schemes to further increase the system capacity and performance. This thesis investigates the existing algorithms and structures and proposes novel interference suppression algorithms for spread spectrum systems. Firstly we investigate blind constrained constant modulus (CCM) stochastic gradient (SG) receivers with a low-complexity variable step-size mechanism for downlink direct sequence CDMA (DS-CDMA) systems. This algorithm provides better performance than existing blind schemes in non-stationary scenarios. Convergence and tracking analyses of the proposed adaptation techniques are ...

The emergence of very capable mobile terminals, e.g. smartphones or tablets, has dramatically increased the demand of wireless data traffic in recent years. Current growth forecasts elucidate that wireless communication standards will not be able to afford future traffic demands, thus many research efforts have been oriented towards increasing the efficiency of wireless networks. Wireless communications introduce many issues not present in wired systems, e.g. multipath effects or interference. Some of these issues may be tackled by the use of multiple antennas, i.e. MIMO technologies. This solution allows increasing not only the reliability and robustness of the communications, i.e. the diversity gain, but also its efficiency, i.e. the multiplexing gain or degrees of freedom (DoF). The DoF describe the slope of channel capacity at very high signal-to-noise-ratio (SNR) regime. For a point-to-point (P2P) communication, assuming that the wireless channel response ...

Localizing the bioelectric phenomena originating from the cerebral cortex and evoked by auditory and somatosensory stimuli are clear objectives to both understand how the brain works and to recognize different pathologies. Diseases such as Parkinson's, Alzheimer's, schizophrenia and epilepsy are intensively studied to find a cure or accurate diagnosis. Epilepsy is considered the disease with major prevalence within disorders with neurological origin. The recurrent and sudden incidence of seizures can lead to dangerous and possibly life-threatening situations. Since disturbance of consciousness and sudden loss of motor control often occur without any warning, the ability to predict epileptic seizures would reduce patients' anxiety, thus considerably improving quality of life and safety. The common procedure for epilepsy seizure detection is based on brain activity monitorization via electroencephalogram (EEG) data. This process consumes a lot of time, especially in the case of long ...

In direction finding (DF) applications, there are several factors affecting the estimation accuracy of the direction-of-arrivals (DOA) of unknown source locations. The major distortions in the estimation process are due to the array imperfections, model mismatches and multipath. The array imperfections usually exist in practical applications due to the nonidealities in the antenna array such as mutual coupling (MC) and gain/phase uncertainties. The model mismatches usually occur when the model of the received signal differs from the signal model used in the processing stage of the DF system. Another distortion is due to multipath signals. In the multipath scenario, the antenna array receives the transmitted signal from more than one path with different directions and the array covariance matrix is rank-deficient. In this thesis, three new methods are proposed for the problems in DF applications in the presence of array ...

Over the past years magnetic resonance spectroscopy (MRS) has been of significant importance both as a fundamental research technique in different fields, as well as a diagnostic tool in medical environments. With MRS, for example, spectroscopic information, such as the concentrations of chemical substances, can be determined non-invasively. To that end, the signals are first modeled by an appropriate model function and mathematical techniques are subsequently applied to determine the model parameters. In this thesis, signal processing algorithms are developed to quantify in-vivo and ex-vivo MRS signals. These are usually characterized by a poor signal-to-noise ratio, overlapping peaks, deviations from the model function and in some cases the presence of disturbing components (e.g. the residual water in proton spectra). The work presented in this thesis addresses a part of the total effort to provide accurate, efficient and automatic data analysis ...