Multiple-input multiple-output (MIMO) systems will be applied in wireless communications in order to increase the performance, spectral efficiency, and reliability. Theoretically, the channel capacity of those systems grows linearly with the number of transmit and receive antennas. An important performance metric beneath capacity is the normalised mean square error (MSE) under the assumption of optimal linear reception. Clearly, both performance measures depend on the properties of the MIMO channel as well as on the considered system approach, e.g. on the type of channel state information which is available at the transmitter. It has been shown that even partial CSI at the transmitter can increase the performance. In this thesis, we analyse the performance and design optimal transmit strategies of singleand multiuser MIMO systems with respect to the statistical properties of the fading channel and under different types of CSI at ...

Receiver synchronisation can be a major problem in a mobile radio environment where the communication channel is subject to rapid changes. Communication in spread spectrum systems is impossible unless the received spreading waveform and receiver-generated replica of the spreading waveform are initially synchronised in both phase and frequency. Phase and frequency synchronisation is usually accomplished by performing a two-dimensional search in the time/frequency ambiguity area. Generally, this process must be accomplished at very low SNRs, as quickly as possible, using the minimum amount of hardware. This thesis looks into techniques for improving spread spectrum receiver synchronisation in terms of the mean acquisition time. In particular, the thesis is focused on receiver structures that provide and/or use a priori information in order to minimise the mean acquisition time. The first part of this work is applicable to synchronisation scenarios involving LEO ...

Direct-sequence code-divisionmultiple-access (DS-CDMA) and multiple-input multiple-output (MIMO) wireless networks form the physical layer of the current generation of mobile networks and are anticipated to play a key role in the next generation of mobile networks. The improvements in capacity, data-rates and robustness that these networks provide come at the cost of increasingly complex interference suppression and resource allocation. Consequently, efficient approaches to these tasks are essential if the current rate of progression in mobile technology is to be sustained. In this thesis, linear minimum mean-square error (MMSE) techniques for interference suppression and resource allocation in DS-CDMA and cooperative MIMO networks are considered and a set of novel and efficient algorithms proposed. Firstly, set-membership (SM) reduced-rank techniques for interference suppression in DS-CDMA systems are investigated. The principals of SM filtering are applied to the adaptation of the projection matrix and reduced-rank ...

5G-and-beyond communication systems are expected to be in a heterogeneous form of multiple-antenna cellular base stations (BSs) overlaid with small cells. The fully-digital BS structures can incur significant power consumption and hardware complexity. Moreover, the wireless BSs for small cells usually have strict size constraints, which incur additional hardware effects such as mutual coupling (MC). Consequently, the transmission techniques designed for future wireless communication systems should respect the hardware structures at the BSs. For this reason, in this thesis we extend generic downlink precoding to more advanced hardware-informed transmission techniques for a variety of BS structures. This thesis firstly extends the vector perturbation (VP) precoding to multiple-modulation scenarios, where existing VP-based techniques are sub-optimal. Subsequently, this thesis focuses on the downlink transmission designs for hardware effects in the form of MC, limited number of radio frequency (RF) chains, and low-precision ...

Distributed signal or information processing using Internet of Things (IoT), facilitates real-time monitoring of signals, for example, environmental pollutants, health indicators, and electric energy consumption in a smart city. Despite the promising capabilities of IoTs, these distributed deployments often face the challenge of data privacy and communication rate constraints. In traditional machine learning, training data is moved to a data center, which requires massive data movement from distributed IoT devices to a third-party location, thus raising concerns over privacy and inefficient use of communication resources. Moreover, the growing network size, model size, and data volume combined lead to unusual complexity in the design of optimization algorithms beyond the compute capability of a single device. This necessitates novel system architectures to ensure stable and secure operations of such networks. Federated learning (FL) architecture, a novel distributed learning paradigm introduced by McMahan ...

The development of a fully unsupervised algorithm to achieve image segmentation is the central theme of this dissertation. Existing literature falls short of such a goal providing many algorithms capable of solving a subset of this highly challenging problem. Unsupervised segmentation is the process of identifying and locating the constituent regions of an observed image, while having no prior knowledge of the number of regions. The problem can be formulated in a Bayesian framework and through the use of an assumed model unsupervised segmentation can be posed as a problem of optimisation. This is the approach pursued throughout this dissertation. Throughout the literature, the commonly adopted model is an hierarchical image model whose underlying components are various forms of Markov Random Fields Gaussian. Markov Random Field models are used to model the textural content of the observed images regions, while ...

Making decisions and predictions from noisy observations are two important and challenging problems in many areas of society. Some examples of applications are recommendation systems for online shopping and streaming services, connecting genes with certain diseases and modelling climate change. In this thesis, we make use of Bayesian statistics to construct probabilistic models given prior information and historical data, which can be used for decision support and predictions. The main obstacle with this approach is that it often results in mathematical problems lacking analytical solutions. To cope with this, we make use of statistical simulation algorithms known as Monte Carlo methods to approximate the intractable solution. These methods enjoy well-understood statistical properties but are often computational prohibitive to employ. The main contribution of this thesis is the exploration of different strategies for accelerating inference methods based on sequential Monte Carlo ...

The overriding aim of this thesis is to investigate the benefits of focusing time-frequency analysis on particular regions of the time-frequency plane. The thesis examines aspects of such a regionalisation in the analysis of both deterministic signals and stochastic processes. The majority of deterministic energetic time-frequency representations are non-parametric indicating the distribution of the energy of a signal in the time-frequency plane but providing no further information about the time-frequency structure. This thesis develops a semi-parametric time-frequency model to simultaneously describe the time-frequency energetic structure of a signal and provide an indication of its time-frequency complexity. The model aims to identify ‘timefrequency components’ within the signal to indicate how their energy is distributed in the time-frequency plane and thereby to probabilistically associate every location in the plane with each identified component. The thesis investigates a number of applications of the ...

Nowadays, the design of embedded systems is confronted with the combination of complex signal processing algorithms on the one hand and a variety of computational intensive multimedia applications on the other hand, while time to product launch has been extremely reduced. Especially in the wireless domain those challenges are stacked with tough requirements on power consumption and chip size. Unfortunately, design productivity did not undergo a similar progression and therefore fails to cope with the heterogeneity of modern hardware architectures. Until now, electronic design automation do not provide for complete coverage of the design ow. In particular crucial design tasks as high level characterisation of algorithms, oating-point to xed-point conversion, automated hardware/software partitioning, and automated virtual prototyping are not suciently supported or completely absent. In recent years a consistent design framework named Open Tool Integration Environment (OTIE) has been established ...

Multiple-input multiple output (MIMO) systems deploy multiple antennas at either end of a communication link and can provide significant benefits compared to traditional single antenna systems, such as increased data rates through spatial multiplexing gain, and/or improved link reliability through diversity techniques. Recently, the natural extension of utilising multiple antennas in relay networks, known as MIMO relaying, has attracted significant research attention due to the fact that the benefits of MIMO can be coupled with extended network coverage through the use of relaying devices. This thesis concentrates on the design and analysis of different aspects of MIMO relay systems communicating over frequency selective channels with the use of orthogonal frequency division multiplexing (OFDM). The first focus of this thesis is on the development of training based channel estimation algorithms for two-hop MIMO OFDM relaying. In the first phase of channel ...

Les réseaux 6G (en anglais 6G, sixth generation) prévus présentent de nombreux défis et opportunités pour améliorer les débits de données, l’EE (en anglais EE, Energy Efficiency), la couverture mondiale, la fiabilité et la latence. Ces systèmes utilisent des technologies innovantes telles que les RIS (en anglais RIS, Reconfigurable Intelligent Surfaces), le MIMO (en anglais MIMO, Multiple Input Multiple Output) et les communications THz (en anglais THz, Terahertz Communications). Les canaux sans fil intelligents et adaptables proposés par la technologie RIS permettent un contrôle dynamique de la propagation du signal en manipulant l’environnement sans fil. Il est possible d’améliorer considérablement les performances du système en optimisant le déploiement et l’utilisation des systèmes de communication assistés par RIS. L’EE est un indicateur clé de performance, et la technologie RIS présente des perspectives prometteuses pour l’améliorer grâce à une consommation d’énergie réduite ...

Broadband wireless communication is a very fast growing communication area. Multicarrier modulation techniques like Orthogonal Frequency Division Multiplexing (OFDM), Biorthogonal Frequency Division Multiplexing (BFDM), Pulse Shaping (PS) and Multi-Carrier Spread Spectrum (MCSS) have recently been introduced as robust techniques against intersymbol interference (ISI) and noise, compared to single carrier communication systems over fast fading multipath communication channels. Therefore, multicarrier modulation techniques have been considered as a candidate for new generation, high data rate broadband wireless communication systems and have been adopted as the related standards. Several examples are the European digital audio broadcasting (DAB) and digital video broadcasting (DVB), the IEEE standands for wireless local area networks (WLAN), 802.11a, and wireless metropolitan area networks (WMAN), 802.16a. However, Doppler frequency shifts, phase offset, local oscillator frequency shifts, and multi-path fading severely degrade the performance of multicarrier communication systems. For fast-varying channels, ...

In this thesis, we consider the problem of decentralized estimation under communication constraints in the context of Collaborative Signal and Information Processing. Motivated by sensor network applications, a high volume of data collected at distinct locations and possibly in diverse modalities together with the spatially distributed nature and the resource limitations of the underlying system are of concern. Designing processing schemes which match the constraints imposed by the system while providing a reasonable accuracy has been a major challenge in which we are particularly interested in the tradeoff between the estimation performance and the utilization of communications subject to energy and bandwidth constraints. One remarkable approach for decentralized inference in sensor networks is to exploit graphical models together with message passing algorithms. In this framework, after the so-called information graph of the problem is constructed, it is mapped onto the ...

The fourth and fifth generation wireless communication systems (4G and 5G) use a physical layer (PHY) based on multicarrier modulations for data transmission using high bandwidth. This type of modulations has shown to provide high spectral efficiency while allowing low complexity radio channel equalization. These systems use OFDMA as a mechanism for distributing the available radio resources among different users. This allocation is done by assigning a subset of subcarriers to each user in a given instant of time. This provides great flexibility to the system that allows it to adapt to both the quality of service requirements of users and the radio channel state. The media access layer (MAC) of these systems is in charge of configuring the multiple OFDMA PHY layer parameters, in addition to managing the data flows of each user, transforming the higher layer packets into ...

An intelligent antenna is actually composed of a series of elementary antennas (linear, circular, etc.) who’s received signals are balanced and combined by using a technique of adaptation in order to control and improve the reception or the transmission. The objective of our study is to look further into the knowledge of the methods of formation of the beams and to elaborate a digital technique of synthesis for the formation of ways and the cancellation of interfering which answers the specifications imposed by the system adaptive by using the networks of neurons. The work of thesis consisted of a contribution to the optimization of the lobe of radiation for an intelligent antenna. In a first stage, two complementary approaches were developed to implement the technique of forming of the lobe, one based on an algorithm of optimization which calculates the ...