Multi-input multi-output (MIMO) wireless networks and distributed MIMO relaying wireless networks have attracted significant attention in current generation of wireless communication networks, and will play a key role in the next generation of wireless net- works. The improvement of network capacity, data rate and reliability can be achieved at the cost of increasing computational complexity of employing space-time coding (STC) and distributed STC (DSTC) in MIMO and distributed MIMO relaying networks, respectively. Efficient designs and algorithms to achieve high diversity and coding gains with low computational complexity in encoding and decoding of STC and DSTC schemes are essential. In this thesis, DSTC designs with high diversity and coding gains and efficient detection and code matrices optimization algorithms in cooperative MIMO networks are proposed. Firstly, adaptive power allocation (PA) algorithms with different criteria for a coop- erative MIMO network equipped with ...

In multi-user (MU) downlink beamforming, a high spectral efficiency along with a low transmit power is achieved by separating multiple users in space rather than in time or frequency using spatially selective transmit beams. For streaming media applications, multi-group multicast (MGM) downlink beamforming is a promising approach to exploit the broadcasting property of the wireless medium to transmit the same information to a group of users. To limit inter-group interference, the individual streams intended for different multicast groups are spatially separated using MGM downlink beamforming. Spatially selective downlink beamforming requires the employment of an array of multiple antennas at the base station (BS). The hardware costs associated with the use of multiple antennas may be prohibitive in practice. A way to avoid the expensive employment of multiple antennas at the BS is to exploit user cooperation in wireless networks where ...

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 ...

In recent years, there has been a proliferation of wireless devices for individual use to the point of being ubiquitous. Recent trends have been incorporating many of these devices (or nodes) together, which acquire signals and work in unison over wireless channels, in order to accomplish a predefined task. This type of cooperative sensing and communication between devices form the basis of a so-called wireless sensor network (WSN). Due to the ever increasing processing power of these nodes, WSNs are being assigned more complicated and computationally demanding tasks. Recent research has started to exploit this increased processing power in order for the WSNs to perform tasks pertaining to audio signal acquisition and processing forming so-called wireless acoustic sensor networks (WASNs). Audio signal processing poses new and unique problems when compared to traditional sensing applications as the signals observed often have ...

Wireless sensor networks (WSNs) paved the way for accessing data previously unavailable by deploying sensors in various locations in space, each collecting local measurements of a target source signal. By exploiting the information resulting from the multitude of signals measured at the different sensors of the network, various tasks can be achieved, such as denoising or dimensionality reduction which can in turn be used, e.g., for source localization or detecting seizures from electroencephalography measurements. Spatial filtering consists of linearly combining the signals measured at each sensor of the network such that the resulting filtered signal is optimal in some sense. This technique is widely used in biomedical signal processing, wireless communication, and acoustics, among other fields. In spatial filtering tasks, the aim is to exploit the correlation between the signals of all sensors in the network, therefore requiring access to ...

In recent years, we have assisted to the dawn of many wireless and wireline communication technologies that have adopted multi-carrier modulation (MCM) at the physical layer. The basic idea ofMCMs is to transmit a high rate data stream by dividing it into low rate streams that are used to generate low rate signals each modulated at a given carrier frequency. The use ofMCMs allows for dividing the frequency selective channel into a set of narrow-band sub-channels. Consequently, the transmitted signal experiences, in each sub-channel, a quasi flat frequency response, so that, the equalization task simplifies to a sub-channel filtering. In addition to the simplification of the equalization task, there are several benefits deriving from the use of MCMs that, in general, depend upon the considered transmission medium. The most important ones are the low complexity digital implementation, and the possibility ...

In recent years, there has been a proliferation of wireless devices for individual use to the point of being ubiquitous. Recent trends have been incorporating many of these devices (or nodes) together, which acquire signals and work in unison over wireless channels, in order to accomplish a predefined task. This type of cooperative sensing and communication between devices form the basis of a so-called wireless sensor network (WSN). Due to the ever increasing processing power of these nodes, WSNs are being assigned more complicated and computationally demanding tasks. Recent research has started to exploit this increased processing power in order for the WSNs to perform tasks pertaining to audio signal acquisition and processing forming so-called wireless acoustic sensor networks (WASNs). Audio signal processing poses new and unique problems when compared to traditional sensing applications as the signals observed often have ...

Recent technological advances in analogue and digital electronics as well as in hardware miniaturization have taken wireless sensing devices to another level by introducing low-power communication protocols, improved digital signal processing capabilities and compact sensors. When these devices perform a certain pre-defined signal processing task such as the estimation or detection of phenomena of interest, a cooperative scheme through wireless connections can significantly enhance the overall performance, especially in adverse conditions. The resulting network consisting of such connected devices (or nodes) is referred to as a wireless sensor network (WSN). In acoustical applications (e.g., speech enhancement) a variant of WSNs, called wireless acoustic sensor networks (WASNs) can be employed in which the sensing unit at each node consists of a single microphone or a microphone array. The nodes of such a WASN can then cooperate to perform a multi-channel acoustic ...

In the modern world, we are increasingly surrounded by computation devices with communication links and one or more microphones. Such devices are, for example, smartphones, tablets, laptops or hearing aids. These devices can work together as nodes in an acoustic sensor network (ASN). Such networks are a growing platform that opens the possibility for many practical applications. ASN based speech enhancement, source localization, and event detection can be applied for teleconferencing, camera control, automation, or assisted living. For this kind of applications, the awareness of auditory objects and their spatial positioning are key properties. In order to provide these two kinds of information, novel methods have been developed in this thesis. Information on the type of auditory objects is provided by a novel real-time sound classification method. Information on the position of human speakers is provided by a novel localization ...

This dissertation deals with the distributed processing techniques for parameter estimation and efficient data-gathering in wireless communication and sensor networks. The estimation problem consists in inferring a set of parameters from temporal and spatial noisy observations collected by different nodes that monitor an area or field. The objective is to derive an estimate that is as accurate as the one that would be obtained if each node had access to the information across the entire network. With the aim of enabling an energy aware and low-complexity distributed implementation of the estimation task, several useful optimization techniques that generally yield linear estimators were derived in the literature. Up to now, most of the works considered that the nodes are interested in estimating the same vector of global parameters. This scenario can be viewed as a special case of a more general ...

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 ...

MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) CHANNELS constitute a unified way of modeling a wide range of different physical communication channels, which can then be handled with a compact and elegant vector-matrix notation. The two paradigmatic examples are wireless multi-antenna channels and wireline Digital Subscriber Line (DSL) channels. Research in antenna arrays (also known as smart antennas) dates back to the 1960s. However, the use of multiples antennas at both the transmitter and the receiver, which can be naturally modeled as a MIMO channel, has been recently shown to offer a significant potential increase in capacity. DSL has gained popularity as a broadband access technology capable of reliably delivering high data rates over telephone subscriber lines. A DSL system can be modeled as a communication through a MIMO channel by considering all the copper twisted pairs within a binder as a whole rather ...

The wireless communication industry has experienced rapid growth in recent years, and digital cellular systems are currently designed to provide high data rates at high terminal speeds. High data rates give rise to intersymbol interference (ISI) due to so-called multipath fading. Such an ISI channel is called frequency selective. On the other hand, due to terminal mobility and/or receiver frequency offset the received signal is subject to frequency shifts (Doppler shifts). Doppler shift induces time-selectivity characteristics. The Doppler effect in conjunction with ISI gives rise to a so-called doubly selective channel (frequency- and time-selective). In addition to the channel effects, the analog front-end may suffer from an imbalance between the I and Q branch amplitudes and phases as well as from carrier frequency offset. These analog front-end imperfections then result in an additional and significant degradation in system performance, especially ...

Currently, the telecommunications market has brought changes to the design of the old model of the telecommunications network. The emergence of new technologies for higher speed access was inevitable in order to meet the requirements of the appearance of the multimedia services (VoD, online gaming etc.). The latest technologies for broadband access over telephone pairs are Digital Subscriber Lines or DSL. This set of xDSL technologies allow the transfer of binary high speed over telephone twisted pair by using a suitable type of line codes. They allow a flow of high-speed information both asymmetrical and symmetrical over the telephone loop. This thesis presents the state of the art of Dynamic Spectrum Management (DSM) technologies suggested to improve the performance of DSL systems and proposes a new approach to this issue. The main contributions of this thesis includes extended bandwidth channel ...

This thesis proposes different methods to reduce the computational complexity as well as increasing the adaptation rate of adaptive broadband beamformers. This is performed exemplarily for the generalised sidelobe canceller (GSC) structure. The GSC is an alternative implementation of the linearly constrained minimum variance beamformer, which can utilise well-known adaptive filtering algorithms, such as the least mean square (LMS) or the recursive least squares (RLS) to perform unconstrained adaptive optimisation. A direct DFT implementation, by which broadband signals are decomposed into frequency bins and processed by independent narrowband beamforming algorithms, is thought to be computationally optimum. However, this setup fail to converge to the time domain minimum mean square error (MMSE) if signal components are not aligned to frequency bins, resulting in a large worst case error. To mitigate this problem of the so-called independent frequency bin (IFB) processor, overlap-save ...