In this thesis I describe the setup and design of a flexible rapid prototyping platform for RFID systems to provide an experimental verification environment for RFID systems, that allows their real-time exploration in distinct measurement setups. Furthermore, I use this system to test the feasibility of novel signal processing algorithms for RFID reader receivers, which promise a performance increase to state-of-the-art-receivers. Three different scenarios are considered: 1. In the first scenario, a single tag communicates with a single receive antenna reader. The performance of the optimal maximum likelihood sequence decoder is identified, and losses due to channel estimation and synchronisation are discussed. Due to the wide deviation from the nominal data rate in the uplink communication, especially synchronisation shows to be a critical issue. 2. In the second scenario, the single tag communicates with a multiple receive antenna RFID reader. ...

Tag localization in passive ultra-high frequency radio frequency identification (UHF RFID) has become something of a holy grail since the system was introduced. First and foremost, it promises improved accuracy for inventory systems, which have to deal with false positive reads outside the intended read zone and the consequent corruption of inventory lists. This thesis addresses the problem of passive UHF RFID tag localization, with a focus on range finding methods. It shows how typical system setups influence the propagation channel and why this creates a harsh environment for any type of localization. Based on the conclusions drawn in this channel analysis, tag localization approaches are investigated. It is shown that robust and accurate localization of state-of-the-art UHF RFID transponders is possible only in controlled environments. Wideband and ultra-wideband methods offer considerably greater robustness and accuracy in typical fields of ...

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 ...

Chapter 2 contains a short introduction to the fundamentals of compressed sensing theory, which is the larger context of this thesis. We start with introducing the key concepts of sparsity and sparse representations of signals. We discuss the central problem of compressed sensing, i.e. how to adequately recover sparse signals from a small number of measurements, as well as the multiple formulations of the reconstruction problem. A large part of the chapter is devoted to some of the most important conditions necessary and/or sufficient to guarantee accurate recovery. The aim is to introduce the reader to the basic results, without the burden of detailed proofs. In addition, we also present a few of the popular reconstruction and optimization algorithms that we use throughout the thesis. Chapter 3 presents an alternative sparsity model known as analysis sparsity, that offers similar recovery ...

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 ...

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 ...

For a large class of non-delay-critical applications (e.g., buffered video streaming or data transfer from cloud services to local devices), end-to-end throughput becomes the most crucial key performance indicator (KPI). In cellular networks, the achievable end-user throughput (the maximum throughput a user will get when attempting to download as much data as possible) is a spatiotemporal function, and its estimation poses a challenging and as-yet unsolved problem. The ability to accurately predict achievable throughput in a given location and time interval would, for example, allow mobile operators to further optimize their networks and design more personalized offers for the customers, or allow end-users with mobile broadband modems to make more informed decisions when selecting a provider. This work investigates the impact of individual parameters on the end-user achievable throughput in cellular networks and analyzes the feasibility and limitations of constructing ...

This thesis aims at contributing to overcome two of the main challenges for the deployment of highly dense wireless M2M networks in data collection scenarios for the Internet of Things: the management of massive numbers of end-devices that attempt to get access to the wireless channel; and the need to extend the network lifetime to reduce maintenance costs. In order to solve these challenges, two complementary strategies are considered. Firstly, the thesis focuses on the design, analysis and performance evaluation of random and hybrid access protocols that can handle abrupt transitions in the traffic load and minimize the energy consumption devoted to communications. And secondly, the use of energy harvesting (EH) is considered in order to provide the network with unlimited lifetime. To this end, the second part of the thesis focuses on the design and analysis of EH-aware MAC ...

The production and delivery of audio for television involve many creative and technical challenges. One of them is concerned with the level balance between the foreground speech (also referred to as dialogue) and the background elements, e.g., music, sound effects, and ambient sounds. Background elements are fundamental for the narrative and for creating an engaging atmosphere, but they can mask the dialogue, which the audience wishes to follow in a comfortable way. Very different individual factors of the people in the audience clash with the creative freedom of the content creators. As a result, service providers receive regular complaints about difficulties in understanding the dialogue because of too loud background sounds. While this has been a known issue for at least three decades, works analyzing the problem and up-to-date statics were scarce before the contributions in this work. Enabling the ...

Optimizing the performance of digital imaging systems with respect to the capture, display, storage and transmission of visual information represents one of the biggest challenges in the field of image and video processing. Taking into account the way humans perceive visual information can be greatly beneficial for this task. To achieve this, it is necessary to understand and model the human visual system, which is also the principal goal of this thesis. Computational models for different aspects of the visual system are developed, which can be used in a wide variety of image and video processing applications. The proposed models and metrics are shown to be consistent with human perception. The focus of this work is visual quality assessment. A perceptual distortion metric (PDM) for the evaluation of video quality is presented. It is based on a model of the ...

The last ten years have seen a massive growth in the number of connected wireless devices. Billions of devices are connected and managed by wireless networks. At the same time, each device needs a high throughput to support applications such as voice, real-time video, movies, and games. Demands for wireless throughput and the number of wireless devices will always increase. In addition, there is a growing concern about energy consumption of wireless communication systems. Thus, future wireless systems have to satisfy three main requirements: i) having a high throughput; ii) simultaneously serving many users; and iii) having less energy consumption. Massive multiple-input-multiple-output (MIMO) technology, where a base station (BS) equipped with very large number of antennas (collocated or distributed) serves many users in the same time-frequency resource, can meet the above requirements, and hence, it is a promising candidate technology ...

The ability to reliably and cheaply localize mobile terminals will allow users to understand and utilize the what, where and when of the surrounding physical world. Therefore, mobile terminal location information will open novel application opportunities in many areas. The mobile terminal positioning problem is categorized into three different types according to the availability of (1) initial accurate location information and (2) motion measurement data. Location estimation refers to the mobile positioning problem when both the initial location and motion measurement data are not available. If both are available, the positioning problem is referred to as position tracking. When only motion measurements are available the problem is known as global localization. These positioning problems were solved within the Bayesian filtering framework in order to work under a common theoretical context. Filter derivation and implementation algorithms are provided with emphasis on ...

The importance of power reduction of embedded systems has continuously increased in the past years. Recently, reducing power dissipation and energy consumption of a program have become optimization goals in their own right, no longer considered a side-effect of traditional performance optimizations which mainly target program execution time and/or program size. Nowadays, there is an increasing demand for developing power-optimizing compilers for embedded systems. This thesis is a step towards such important goal. In this thesis, we develop functional-level power models and investigate several software optimization techniques for embedded-processor systems. As a specific example, we consider the powerful Texas Instruments C6416T DSP processor. We analyze the power consumption contributions of the different functional units of this DSP. We assess the effect of the compiler performance optimizations on the energy and power consumption. Moreover, we explore the impact of two special ...

Device-to-Device (D2D) is one of the important proposed solutions to increase the capacity, offload the traffic, and improve the energy effciency in next generation cellular networks. D2D communication is known as a direct communication between two users without using cellular infrastructure networks. Despite of large expected bene fits in terms of capacity in D2D, the coexistence of D2D and cellular networks in the same spectrum creates new challenges in interference management and network design. To limit the interference power control schemes on cellular networks and D2D networks are typically adopted. Even though power control is introduced to limit the interference level, it does not prevent cellular and D2D users from experiencing coverage limitation when sharing the same radio resources. Therefore, the design of such networks requires the availability of suitable methods able to properly model the eff ect of interference ...

Due to significant advances made over the last few decades in the areas of (wireless) networking, communications and microprocessor fabrication, the use of sensor networks to observe physical phenomena is rapidly becoming commonplace. Over this period, many aspects of sensor networks have been explored, yet a thorough understanding of how to analyse and process the vast amounts of sensor data collected remains an open area of research. This work, therefore, aims to provide theoretical, as well as practical, advances this area. In particular, we consider the problem of inferring certain underlying properties of the monitored phenomena, from our sensor measurements. Within mathematics, this is commonly formulated as an inverse problem; whereas in signal processing, it appears as a (multidimensional) sampling and reconstruction problem. Indeed it is well known that inverse problems are notoriously ill-posed and very demanding to solve; meanwhile ...