Wireless networks and power distribution grids are experiencing increasing demands on their efficiency and reliability. Judicious methods for allocating scarce resources such as power and bandwidth are of paramount importance. As a result, nonlinear optimization and signal processing tools have been incorporated into the design of contemporary networks. This thesis develops schemes for efficient resource allocation (RA) in such dynamic networks, with an emphasis in stochasticity, which is accounted for in the problem formulation as well as in the algorithms and schemes to solve those problems. Stochastic optimization and decomposition techniques are investigated to develop low-complexity algorithms with specific applications in cross-layer design of wireless communications, cognitive radio (CR) networks and smart power distribution systems. The costs and constraints on the availability of network resources, together with diverse quality of service (QoS) requirements, render network design, management, and operation challenging ...

In Wireless Sensor Networks (WSN), the ability of sensor nodes to know its position is an enabler for a wide variety of applications for monitoring, control, and automation. Often, sensor data is meaningful only if its position can be determined. Many WSN are deployed indoors or in areas where Global Navigation Satellite System (GNSS) signal coverage is not available, and thus GNSS positioning cannot be guaranteed. In these scenarios, WSN may be relied upon to achieve a satisfactory degree of positioning accuracy. Typically, batteries power sensor nodes in WSN. These batteries are costly to replace. Therefore, power consumption is an important aspect, being performance and lifetime ofWSN strongly relying on the ability to reduce it. It is crucial to design effective strategies to maximize battery lifetime. Optimization of power consumption can be made at different layers. For example, at the ...

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, ...

With the rapidly growing of the customers’ data traffic demand, improving the system capacity and increasing the user throughput have become essential concerns for the future fifth-generation (5G) wireless communication network. In this context, device-to-device (D2D) communication and in-band full-duplex (FD) are proposed as potential solutions to increase the spatial spectrum utilization and the user rate in a cellular network. D2D allows two nearby devices to communicate without base station (BS) participation or with limited participation. On the other hand, FD communication enables simultaneous transmission and reception in the same frequency band. Due to the short distance property of D2D links, exploiting the FD technology in D2D communication is an excellent choice to further improve the cellular spectrum efficiency and the users’ throughput. However, practical FD transceivers add new challenges for D2D communication. For instance, the existing FD devices cannot ...

Modern society is undergoing a fundamental change in the way we interact with technology. More and more devices are becoming "smart" by gaining advanced computation capabilities and communication interfaces, from household appliances over transportation systems to large-scale networks like the power grid. Recording, processing, and exchanging digital information is thus becoming increasingly important. As a growing share of devices is nowadays mobile and hence battery-powered, a particular interest in efficient digital signal processing techniques emerges. This thesis contributes to this goal by demonstrating methods for finding efficient algebraic solutions to various applications of multi-channel digital signal processing. These may not always result in the best possible system performance. However, they often come close while being significantly simpler to describe and to implement. The simpler description facilitates a thorough analysis of their performance which is crucial to design robust and reliable ...

The modern power grid is facing major challenges in the transition to a low-carbon energy sector. The growing energy demand and environmental concerns require carefully revisiting how electricity is generated, transmitted, and consumed, with an eye to the integration of renewable energy sources. The envisioned smart grid is expected to address such issues by introducing advanced information, control, and communication technologies into the energy infrastructure. In this context, demand-side management (DSM) makes the end users responsible for improving the efficiency, reliability and sustainability of the power system: this opens up unprecedented possibilities for optimizing the energy usage and cost at different levels of the network. The design of DSM techniques has been extensively discussed in the literature in the last decade, although the performance of these methods has been scarcely investigated from the analytical point of view. In this thesis, ...

Signal processing techniques for multiple-antenna transmission can exploit the spatial dimension of the wireless channel to serve multiple users simultaneously, achieving high spectral efficiencies. Realizing such gains; however, is strongly dependent on the availability of highly accurate and up-to-date Channel State Information at the Transmitter (CSIT). This stems from the necessity to deal with multiuser interference through preprocessing; as receivers cannot coordinate in general. In wireless systems, CSIT is subject to uncertainty due to estimation and quantization errors, delays and mismatches. This thesis proposes optimized preprocessing techniques for broadcasting scenarios where a multi-antenna transmitter communicates with single-antenna receivers under CSIT uncertainties. First, we consider a scenario where the transmitter communicates an independent message to each receiver. The most popular preprocessing techniques in this setup are based on linear precoding (or beamforming). Despite their near-optimum rate performances when highly accurate CSIT ...

Wireless communications are important in our highly connected world. The amount of data being transferred in cellular networks is steadily growing, and consequently more capacity is needed. This thesis considers the problem of downlink capacity improvement from the perspective of multicell coordination. By employing multiple antennas at the transmitters and receivers of a multicell network, the inherent spatial selectivity of the users can be exploited in order to increase the capacity through linear precoding and receive filtering. For the coordination between cells, distributed algorithms are often sought due to their low implementation complexity and robustness. In this context, the thesis considers two problem domains: base station clustering and coordinated precoding. Base station clustering corresponds to grouping the cell base stations into disjoint clusters in order to reduce the coordination overhead. This is needed in intermediate-sized to large networks, where the ...

An important specificity of wireless communication channels are the rapid fluctuations of propagation coefficients. This effect is called fading and is caused by the motion of obstacles, scatterers and reflectors standing along the different paths of electromagnetic wave propagation between the transmitting and the receiving terminal. These changes in the geometry of the wireless channel prompt the attenuation coefficients and the relative phase shifts between the multiple propagation paths to vary. This suggests to model the channel coefficients (the transfer matrix) as random variables. The present thesis studies information rates for reliable transmission of information over fading channels under the realistic assumption that the receiver has only imperfect knowledge of the random fading state. While the over-idealized assumption of perfect channel-state information at the receiver (CSIR) gives rise to many simple expressions and is fairly well understood, the settings with ...

When data is transmitted over the wireless communication channel, the transmit signal experiences distortion depending on the channel¢s fading characteristics. On the one hand, this calls for efficient processing at the receiver to mitigate the detrimental effects of the channel and maximize data throughput. On the other hand, the diversity inherently present in these channels can be leveraged with appropriate transmit processing in order to increase the reliability of the transmission link. Recently, in [1] it was shown that the channel characteristics can be exploited to maximize the total data throughput in the interference channel where multiple user pairs rely on the same resource to communicate among themselves. In this PhD dissertation, we first propose novel equalizer designs for frequency selective channels. We then present new results on the diversity gain of equalizers in fading channels when appropriate precoding is ...

To enable ultra-high data rate and ubiquitous coverage in future wireless networks, new physical layer techniques are desired. Relaying is a promising technique for future wireless networks since it can boost the coverage and can provide low cost wireless backhauling solutions, as compared to traditional wired backhauling solutions via fiber and copper. Traditional one-way relaying (OWR) techniques suffer from the spectral loss due to the half-duplex (HD) operation at the relay. On one hand, two-way relaying (TWR) allows the communication partners to transmit to and/or receive from the relay simultaneously and thus uses the spectrum more efficiently than OWR. Therefore, we study two-way relays and more specifically multi-pair/multi-user TWR systems with amplify-and-forward (AF) relays. These scenarios suffer from inter-pair or inter-user interference. To deal with the interference, advanced signal processing algorithms, in other words, spatial division multiple access (SDMA) techniques, ...

Multi-antenna processing is widely adopted as one of the key enabling technologies for current and future cellular networks. Particularly, multiuser downlink beamforming (also known as space-division multiple access), in which multiple users are simultaneously served with spatial transmit beams in the same time and frequency resource, achieves high spectral efficiency with reduced energy consumption. To harvest the potential of multiuser downlink beamforming in practical systems, optimal beamformer design shall be carried out jointly with network resource allocation. Due to the specifications of cellular standards and/or implementation constraints, resource allocation in practice naturally necessitates discrete decision makings, e.g., base station (BS) association, user scheduling and admission control, adaptive modulation and coding, and codebook-based beamforming (precoding). This dissertation focuses on the joint optimization of multiuser downlink beamforming and discrete resource allocation in modern cellular networks. The problems studied in this thesis involve ...

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 ...

When the transmitter of a communication system disposes of some Channel State Information (CSI), it is possible to design linear precoders that optimally allocate the power inducing high gains either in terms of capacity or in terms of reliable communications. In practical scenarios, this channel knowledge is not perfect and thus the transmitted signal suffers from the mismatch between the CSI at the transmitter and the real channel. In that context, this thesis deals with two different, but related, topics: the design of a feasible transmitter channel tracker for time varying channels, and the design of optimal linear precoders robust to imperfect channel estimates. The first part of the thesis proposes the design of a channel tracker that provides an accurate CSI at the transmitter by means of a low capacity feedback link. Historically, those schemes have been criticized because ...

The theory of statistical signal processing finds a wide variety of applications in the fields of data communications, such as in channel estimation, equalization and symbol detection, and sensor array processing, as in beamforming, and radar systems. Indeed, a large number of these applications can be interpreted in terms of a parametric estimation problem, typically approached by a linear filtering operation acting upon a set of multidimensional observations. Moreover, in many cases, the underlying structure of the observable signals is linear in the parameter to be inferred. This dissertation is devoted to the design and evaluation of statistical signal processing methods under realistic implementation conditions encountered in practice. Traditional statistical signal processing techniques intrinsically provide a good performance under the availability of a particularly high number of observations of fixed dimension. Indeed, the original optimality conditions cannot be theoretically guaranteed ...