Radio Frequency Identification (RFID) is a very fast emerging technology that wirelessly transmits the identity of a tag attached to an object or a person. It usually operates in a dense tag environment. My work is focused on passive Ultra High Frequency (UHF) tags whose transmission on the Medium Access Control (MAC) layer is scheduled by Framed Slotted Aloha (FSA). In this thesis, I propose the use of multiple antennas at the reader side in order to recover from collision. By exploiting the fact that a tag signal is real-valued while all other components of a received signal are complexed-valued, I have separated real and imaginary part and in that way I have achieved a recovery from a collision that contains a two times higher number of tags than the number of the receive antennas at the reader, under perfect ...

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. ...

Electrocardiography (ECG) is the standard method for assessing the state of the cardiovascular system non-invasively. In the context of magnetic resonance imaging (MRI) the ECG signal is used for cardiac monitoring and triggering, i.e., the acquisition of images synchronized to the cardiac cycle. However, ECG acquisition is impeded by the static and dynamic magnetic fields which alter the measured voltages and may reduce signal-to-noise ratio (SNR), leading to false alarms during cardiac monitoring or to image artifacts during cardiac triggering. A major source of noise is the magnetohydrodynamic (MHD) effect as it is proportional to field strength and represents a key challenge in application of ultra-high-field (UHF) MRI >=7 T. In this work, two approaches for overcoming these limitations are proposed: i) Development of a hardware and software system based on the principal of photoplethysmography imaging (PPGi) as an optical ...

In a multipath dominated environment, ultra-wideband (UWB) systems that transmit trains of subnanosecond duration pulses exhibit the desirable property of fine resolution in time of the received paths, which as a result of the impulsive form of the transmitted signal go through fewer amplitude fluctuations than those emanating from systems with narrower bandwidths. Being distributed over a large number of resolvable paths, UWB signal energy is typically collected by the rake receiver. In this thesis, achievable information rates of time-hopping M-ary pulse position modulation UWB systems using either soft- or hard-decision outputs are calculated first, where one distinguishing characteristic observed for the hard-output systems is that increasing the constellation size is advantageous only at sufficiently large values of the code rate. Next, it is shown that with time division duplex UWB systems, for which channel information is available at the ...

This thesis investigates noncoherent multi-channel ultra-wideband receivers. Noncoherent ultra-wideband receivers promise low power consumption and low processing complexity as they, in contrast to coherent receiver architectures, relinquish the need of complex carrier frequency and phase recovering. Unfortunately, their peak data rate is limited by the delay spread of the multipath radio channel. Noncoherent multi-channel receivers can break this rate limit due to their capability to demodulate multi-carrier signals. Such receivers use an analog front-end to separate the received signals into their sub-channels. In this work, the modeling and optimization of realistic front-end components is addressed and their impact on the system performance of noncoherent multi-channel ultra-wideband receivers is analyzed. With a proposed generalized mathematical framework, it is shown that there exists a variety of noncoherent multi-channel receiver types with similar system performance which differ only in their front-end filters. It ...

In recent years, inertial sensors have undergone major developments. The quality of their measurements has improved while their cost has decreased, leading to an increase in availability. They can be found in stand-alone sensor units, so-called inertial measurement units, but are nowadays also present in for instance any modern smartphone, in Wii controllers and in virtual reality headsets. The term inertial sensor refers to the combination of accelerometers and gyroscopes. These measure the external specific force and the angular velocity, respectively. Integration of their measurements provides information about the sensor’s position and orientation. However, the position and orientation estimates obtained by simple integration suffer from drift and are therefore only accurate on a short time scale. In order to improve these estimates, we combine the inertial sensors with additional sensors and models. To combine these different sources of information, also ...

Ultra-wideband (UWB) communication systems use radio signals with a bandwidth in the range of some hundred MHz to several GHz. Radio channels with dense multipath propagation achieve high multipath diversity, which can be used to improve the robustness and capacity of the communication channel. Furthermore the large bandwidth allows to transmit signals with a small power spectral density such that the interference to other radio signals will be negligible, even if they lie within the same frequency band. In this work the focus is on low-complexity receiver architectures for communication systems in presence of multiple-access interference (MAI). The main objective of this thesis is to develop and to study a framework for communications for transmitted reference (TR) UWB systems and energy detection UWB systems. First, we study the hybrid matched-filter (HMF) receiver for TR UWB systems, which employs matched filters ...

This thesis puts a focus on the analysis of key aspects of low-complexity Ultra Wideband (UWB) localizations systems. It is well known that UWB allows for highly robust and accurate ranging even in multipath intensive environments. On the other hand, the huge bandwidth leads to very challenging receiver designs and so low complexity and low power consumption are not achieveable for common receiver structures. The energy detector is a promising alternative. But in contrast to high-complexity coherent receivers, their performance is strongly dependent on the system parameters of the air interface protocol. IEEE 802.15.4a is a UWB standard with high-precision localization capability (better than 1m). The standard defines many system parameters, whose impact on the ranging and localization performance is studied in the thesis. These parameters have also a significant impact on the maximum allowed transmit energy, which limits the ...

In a future perspective, the need of mapping an unknown indoor environment, of localizing and retrieving information from objects with zero costs and efforts could be satisfied by the adoption of next 5G technologies. Thanks to the mix of mmW and massive arrays technologies, it will be possible to achieve a higher indoor localization accuracy without relying on a dedicated infrastructure for localization but exploiting that designed for communication purposes. Besides users’ localization and navigation objectives, mapping and thus, the capability of reconstructing indoor scenarios, will be an important field of research with the possibility of sharing environmental information via crowd-sourcing mechanisms between users. Finally, in the Internet of Things vision, it is expected that people, objects and devices will be interconnected to each other with the possibility of exchanging the acquired and estimated data including those regarding objects identification, ...

Indoor location has experienced a major boost in recent years. location based services (LBS), which until recently were restricted to outdoor scenarios and the use of GPS, have also been extended into buildings. From large public structures such as airports or hospitals to a multitude of industrial scenarios, LBS has become increasingly present in indoor scenarios. Of the various technologies that can be used to achieve this indoor location, the ones based on ultra- wideband (UWB) signals have become ones of the most demanded due primarily to their accuracy in position estimation. Additionally, the appearance in the market of more and more manufacturers and products has lowered the prices of these devices to levels that allow to think about their use for large deployments with a contained budget. By their nature, UWB signals are very resistant to the multi-path phenomenon, ...

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 ...

The localization and tracking of sound sources using microphone arrays is a problem that, even if it has attracted attention from the signal processing research community for decades, remains open. In recent years, deep learning models have surpassed the state-of-the-art that had been established by classic signal processing techniques, but these models still struggle with handling rooms with strong reverberations or tracking multiple sources that dynamically appear and disappear, especially when we cannot apply any criteria to classify or order them. In this thesis, we follow the ideas of the Geometric Deep Learning framework to propose new models and techniques that mean an advance of the state-of-the-art in the aforementioned scenarios. As the input of our models, we use acoustic power maps computed using the SRP-PHAT algorithm, a classic signal processing technique that allows us to estimate the acoustic energy ...

This thesis presents a new approach to the problem of localizing and tracking multiple acoustic sources using a microphone array. The use of microphone arrays offers enhancements of speech signals recorded in meeting rooms and office spaces. A common solution for speech enhancement in realistic environments with ambient noise and multi-path propagation is the application of so-called beamforming techniques, that enhance signals at the desired angle, using constructive interference, while attenuating signals coming from other directions, by destructive interference. Such beamforming algorithms require as prior knowledge the source location. Therefore, source localization and tracking algorithms are an integral part of such a system. However, conventional localization algorithms deteriorate in realistic scenarios with multiple concurrent speakers. In contrast to conventional localization algorithms, the localization algorithm presented in this thesis makes use of fundamental frequency or pitch information of speech signals in ...

Music was the first mass-market industry to be completely restructured by digital technology, and today we can have access to thousands of tracks stored locally on our smartphone and millions of tracks through cloud-based music services. Given the vast quantity of music at our fingertips, we now require novel ways of describing, indexing, searching and interacting with musical content. In this thesis we focus on a technology that opens the door to a wide range of such applications: automatically estimating the pitch sequence of the melody directly from the audio signal of a polyphonic music recording, also referred to as melody extraction. Whilst identifying the pitch of the melody is something human listeners can do quite well, doing this automatically is highly challenging. We present a novel method for melody extraction based on the tracking and characterisation of the pitch ...

Automatic ear recognition systems have seen increased interest over recent years due to multiple desirable characteristics. Ear images used in such systems can typically be extracted from profile head shots or video footage. The acquisition procedure is contactless and non-intrusive, and it also does not depend on the cooperation of the subjects. In this regard, ear recognition technology shares similarities with other image-based biometric modalities. Another appealing property of ear biometrics is its distinctiveness. Recent studies even empirically validated existing conjectures that certain features of the ear are distinct for identical twins. This fact has significant implications for security-related applications and puts ear images on a par with epigenetic biometric modalities, such as the iris. Ear images can also supplement other biometric modalities in automatic recognition systems and provide identity cues when other information is unreliable or even unavailable. In ...