The third generation of mobile systems brought higher data rates that allow for provisioning of multimedia services containing also video. The real-time services like video call, conferencing, and streaming are particularly challenging for mobile communication systems due to the wireless channel quality variations. The mechanism for video compression utilizes a hybrid of temporal and spatial prediction, transform coding and variable length coding. The combination of these methods provides high compression gain, but at the same time makes the encoded stream more prone to errors. In this thesis, techniques for error resilient transmission of video streaming over wireless mobile networks are investigated. Focus is given to the recent H.264/AVC standard, although the ma jority of the proposed method apply to other video coding standards, too. The first part is dedicated to exploiting the residual redundancy of the received video stream at ...

The abundance of large and heterogeneous systems is rendering contemporary data more pervasive, intricate, and with a non-regular structure. With classical techniques facing troubles to deal with the irregular (non-Euclidean) domain where the signals are defined, a popular approach at the heart of graph signal processing (GSP) is to: (i) represent the underlying support via a graph and (ii) exploit the topology of this graph to process the signals at hand. In addition to the irregular structure of the signals, another critical limitation is that the observed data is prone to the presence of perturbations, which, in the context of GSP, may affect not only the observed signals but also the topology of the supporting graph. Ignoring the presence of perturbations, along with the couplings between the errors in the signal and the errors in their support, can drastically hinder ...

The widespread use of mobile internet and smart applications has led to an explosive growth in mobile data traffic. With the rise of smart homes, smart buildings, and smart cities, this demand is ever growing since future communication systems will require the integration of multiple networks serving diverse sectors, domains and applications, such as multimedia, virtual or augmented reality, machine-to-machine (M2M) communication / the Internet of things (IoT), automotive applications, and many more. Therefore, in the future, the communication systems will not only be required to provide Gbps wireless connectivity but also fulfill other requirements such as low latency and massive machine type connectivity while ensuring the quality of service. Without significant technological advances to increase the system capacity, the existing telecommunications infrastructure will be unable to support these multi-dimensional requirements. This poses an important demand for suitable waveforms with ...

Error control coding is an essential part of modern communications systems. LDPC codes have been demonstrated to offer performance near the fundamental limits of channels corrupted by random noise. Optimal maximum likelihood decoding of LDPC codes is too complex to be practically useful even at short block lengths and so a graph-based message passing decoder known as the belief propagation algorithm is used instead. In fact, on graphs without closed paths known as cycles the iterative message passing decoding is known to be optimal and may converge in a single iteration, although identifying the message update schedule which allows single-iteration convergence is not trivial. At finite block lengths graphs without cycles have poor minimum distance properties and perform poorly even under optimal decoding. LDPC codes with large block length have been demonstrated to offer performance close to that predicted for ...

This work considers a Broadcast Channel (BC) system, where the transmitter is equipped with multiple antennas and each user at the receiver side could have one or more antennas. Depending on the number of antennas at the receiver side, such a system is known as Multiple-User Multiple-Input Single-Output (MU-MISO), for single antenna users, or Multiple-UserMultiple-InputMultiple-Output (MU-MIMO), for several antenna users. This model is suitable for current wireless communication systems. Regarding the direction of the data flow, we differentiate between downlink channel or BC, and uplink channel or Multiple Access Channel (MAC). In the BC the signals are sent from the Base Station (BS) to the users, whereas the information from the users is sent to the BS in the MAC. In this work we focus on the BC where the BS applies linear precoding taking advantage of multiple antennas. The ...

Multiple antennas at the base station side can be used to enhance the spectral efficiency and energy efficiency of the next generation wireless technologies. Indeed, massive multi-input multi-output (MIMO) is seen as one promising technology to bring the aforementioned benefits for fifth generation wireless standard, commonly known as 5G New Radio (5G NR). In this monograph, we will explore a wide range of potential topics in multi-user MIMO (MU-MIMO) relevant to 5G NR, • Sum rate maximizing beamforming (BF) design and robustness to partial channel state information at the transmitter (CSIT) • Asymptotic analysis of the various BF techniques in massiveMIMO and • Bayesian channel estimationmethods using sparse Bayesian learning. While massive MIMO has the aforementioned benefits, it makes the acquisition of the channel state information at the transmitter (CSIT) very challenging. Since it requires large amount of uplink (UL) ...

In this thesis, smoothness of sampled real-world signals is exploited through the application of polynomial predictive filters. The principal reason for employing the polynomial signal model is principally twofold: firstly, assuming that the sampling rate is adequate, all real-world signals exhibit piecewise polynomial-like behavior, and secondly, polynomial-based signal processing is computationally efficient. By definition, polynomial predictive filters provide estimates of future values of polynomial-like signals. Thus, the potential applications of this research include a vast number of different delay sensitive operations on measurements like temperature, position, velocity, or power, especially in control engineering field. The polynomial-based predictive signal processing is a well-known technique, but polynomial-predictive filters have had severe drawbacks, which have hindered their application; their white noise attenuation is generally low, or they exhibit considerable passband gain peaks, rendering them unattractive for most applications. It has been possible to ...

The evolution of electronic devices has made a tremendous progress within the last 50 years, thus today's world they can be found nearly everywhere, such as cell phones, camcorders, antiblock-brakes. The design of such complex system, that consists of hardware and software has to cope with several obstacles like for example high system complexity and increasing economical demands like shortened time-to-market. Those barriers get especially visible in the wireless domain. Here, design productivity lacks behind the possible computational complexity famously described with Moore's law. The importance to cope efficently with these problems of system designing has been highlighted by the International Technology Roadmap for Semiconductors. This thesis examines one of the design tasks namely design space exploration. Since the description of systems raises constantly its level of abstraction which causes a higher ability for exploring design variants the automatic derivation ...

Wireless communications have gone through an exponential growth in the last several years and it is forecast that this growth will be sustained for the coming decades. This ever-increasing demand for radio resources is now facing one of its main limitations: inter-user interference, arising from the fact of multiple users accessing the propagation medium simultaneously which limits the total amount of data that can be reliably communicated through the wireless links. Traditionally, interference has been dealt with by allocating disjoint channel resources to distinct users. However, the advent of a novel interference coordination technique known as interference alignment (IA) brought to the forefront the promise of a much larger spectral efficiency. This dissertation revolves around the idea of linear interference alignment for a network consisting of several mutually interfering transmitter-receiver pairs, which is com-monly known as interference channel. In particular, ...

The demand for precious radio spectrum is continuously increasing while the available radio frequency resource has become scarce due to spectrum segmentation and the dedicated frequency allocation of standardized wireless systems. This scarcity has led to the concept of cognitive radio communication which comprises a variety of techniques capable of allowing the coexistence of licensed and unlicensed systems over the same spectrum. In this context, this thesis focuses on interweave and underlay cognitive radio paradigms which are widely considered as important enablers for realising cognitive radio technology. In the interweave paradigm, an unlicensed user explores the spectral holes by means of some spectrum awareness methods and utilizes the available spectral availabilities opportunistically while in the underlay paradigm, an unlicensed user is allowed to coexist with the licensed user only if sufficient protection to the licensed user can be guaranteed. Starting ...

Standard signal processing techniques are implicitly based on the assumption that the signal lies on a regular, homogeneous domain. In practice, however, many signals lie on an irregular or inhomogeneous domain. An application area where data are naturally defined on an irregular or inhomogeneous domain is human brain neuroimaging. The goal in neuroimaging is to map the structure and function of the brain using imaging techniques. In particular, functional magnetic resonance imaging (fMRI) is a technique that is conventionally used in non-invasive probing of human brain function. This doctoral dissertation deals with the development of signal processing schemes that adapt to the domain of the signal. It consists of four papers that in different ways deal with exploiting knowledge of the signal domain to enhance the processing of signals. In each paper, special focus is given to the analysis of ...

Interaction between the Medium Access Control (MAC)-layer and the physical-layer routines is one of the basic concepts of modern wireless networks. Physical-layer dependent resource allocation and scheduling guarantee efficient network utilization. Accordingly, classical link-level analyses, focusing only on the physical-layer are not sufficient anymore for optimum transceiver structure and algorithm development. This thesis presents the development and application of a system-level description suitable for the downlink of Multiple-Input Multiple-Output (MIMO) enhanced High-Speed Downlink Packet Access (HSDPA), with particular focus on the Double Transmit Antenna Array (D-TxAA) transmission mode. The system-level model allows for investigating and evaluating transmission systems and algorithms in the context of cellular networks. Two separate models are proposed to obtain a complete system-level description: (i) a link-quality model, analytically describing the MIMO HSDPA link quality in a so-called equivalent fading parameter structure, and (ii) a link-performance model, ...

The discovery of novel gene regulatory processes improves the understanding of cell phenotypic responses to external stimuli for many biological applications, such as medicine, environment or biotechnologies. To this purpose, transcriptomic data are generated and analyzed from DNA microarrays or more recently RNAseq experiments. They consist in genetic expression level sequences obtained for all genes of a studied organism placed in different living conditions. From these data, gene regulation mechanisms can be recovered by revealing topological links encoded in graphs. In regulatory graphs, nodes correspond to genes. A link between two nodes is identified if a regulation relationship exists between the two corresponding genes. Such networks are called Gene Regulatory Networks (GRNs). Their construction as well as their analysis remain challenging despite the large number of available inference methods. In this thesis, we propose to address this network inference problem ...

Automatic face recognition has attracted a lot of attention not only because of the large number of practical applications where human identification is needed but also due to the technical challenges involved in this problem: large variability in facial appearance, non-linearity of face manifolds and high dimensionality are some the most critical handicaps. In order to deal with the above mentioned challenges, there are two possible strategies: the first is to construct a “good” feature space in which the manifolds become simpler (more linear and more convex). This scheme usually comprises two levels of processing: (1) normalize images geometrically and photometrically and (2) extract features that are stable with respect to these variations (such as those based on Gabor filters). The second strategy is to use classification structures that are able to deal with non-linearities and to generalize properly. To ...

Today, adaptive algorithms represent one of the most frequently used computational tools for the processing of digital speech signals. This work investigates and analyzes the properties of adaptive algorithms in speech communication applications where rigorous conditions apply, such as noise and echo cancelation. Like other theses in this field do, it tries to tackle the ever-lasting problem of computational complexity vs. rate of convergence. It introduces some new adaptive methods that stem from the existing algorithms as well as a novel concept which has been entitled Optimal Step-Size (OSS). In the first part of the thesis we investigate some well-known, widely used adaptive techniques such as the Normalized Least Mean Squares (NLMS) and the Recursive Least Mean Squares (RLS). In spite of the fact that the NLMS and the RLS belong to the "simplest" principles, as far as complexity is ...