The proliferation of technologies like Internet of Things (IoT) and Industrial IoT (IIoT) has led to rapid growth in the number of connected devices and the volume of data associated with IoT applications. It is expected that more than 125 billion IoT devices will be connected to the Internet by 2030. With the plethora of wireless IoT devices, we are moving towards the connected world which is the guiding principle for the IoT. The next generation of IoT network should be capable of interconnecting heterogeneous IoT sensor or devices for effective Device-to-Device (D2D), Machine-to-Machine (M2M) communications as well as facilitating various IoT services and applications. Therefore, the next generation of IoT networks is expected to meet the capacity demand of such a network of billions of IoT devices. The current underlying wireless network is based on Orthogonal Multiple Access (OMA) ...

Over the last few years multimedia and data-based services experienced a non-stopping growth. Unlike before, people do not use the services only from a static location, but they are continuously on the move between different scenarios, using their mobile devices to access data-based services. In parallel, commuter traffic from rural areas is also rising, since most of work places are in and around cities. During transportation, people intensively employ mobile devices to work, access to social networks, or as an entertainment means. Internet access is required for most of these services. Currently, GSM for Railways (GSM-R), which is based on the Global System for Mobile Communications (GSM), is the most widely used communication system between trains and the elements involved in operation, control, and intercommunication within the railway infrastructure. However, GSM-R is not well suited for supporting advanced services such ...

The fourth and fifth generation wireless communication systems (4G and 5G) use a physical layer (PHY) based on multicarrier modulations for data transmission using high bandwidth. This type of modulations has shown to provide high spectral efficiency while allowing low complexity radio channel equalization. These systems use OFDMA as a mechanism for distributing the available radio resources among different users. This allocation is done by assigning a subset of subcarriers to each user in a given instant of time. This provides great flexibility to the system that allows it to adapt to both the quality of service requirements of users and the radio channel state. The media access layer (MAC) of these systems is in charge of configuring the multiple OFDMA PHY layer parameters, in addition to managing the data flows of each user, transforming the higher layer packets into ...

While 5G wireless systems offer significant enhancements to their 4G counterparts in terms of bandwidth, connectivity, latency, etc. they are unable to meet the requirements of the applications envisioned for the next decade. The demands of applications such as super-smart city, autonomous vehicles, smart health-care, etc. are much greater than what 5G systems can afford. This means that we cannot yet expect the widespread realization of IoT/IoE and have to wait for 6G to finally fulfill this long-awaited promise. As an enabler and a key player for the success of IoT/IoE, WPCN has been the center of attention in the past decade and attracted a large number of journal and conference publications. Despite the extensive efforts in this area, WPCN still lacks the required performance for being seamlessly fitted into the next generation IoT/IoE environments. The main objective of this ...

Data acquisition is a necessary first step in digital signal processing applications such as radar, wireless communications and array processing. Traditionally, this process is performed by uniformly sampling signals at a frequency above the Nyquist rate and converting the resulting samples into digital numeric values through high-resolution amplitude quantization. While the traditional approach to data acquisition is straightforward and extremely well-proven, it may be either impractical or impossible in many modern applications due to the existing fundamental trade-off between sampling rate, amplitude quantization precision, implementation costs, and usage of physical resources, e.g. bandwidth and power consumption. Motivated by this fact, system designers have recently proposed exploiting sparse and few-bit quantized sampling instead of the traditional way of data acquisition in order to reduce implementation costs and usage of physical resources in such applications. However, before transition from the tradition data ...

Distributed signal or information processing using Internet of Things (IoT), facilitates real-time monitoring of signals, for example, environmental pollutants, health indicators, and electric energy consumption in a smart city. Despite the promising capabilities of IoTs, these distributed deployments often face the challenge of data privacy and communication rate constraints. In traditional machine learning, training data is moved to a data center, which requires massive data movement from distributed IoT devices to a third-party location, thus raising concerns over privacy and inefficient use of communication resources. Moreover, the growing network size, model size, and data volume combined lead to unusual complexity in the design of optimization algorithms beyond the compute capability of a single device. This necessitates novel system architectures to ensure stable and secure operations of such networks. Federated learning (FL) architecture, a novel distributed learning paradigm introduced by McMahan ...

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, ...

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. ...

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 ...

Global Navigation Satellite Systems (GNSS) signals are broadly used for positioning, navigation and timing (PNT) in many different applications and use cases. Although different PNT technologies are available, GNSS is expected to be a key player in the derivation of positioning and timing for many future applications, including those in the context of the Internet of Things (IoT) or autonomous vehicles, since it has the important advantage of being open access and worldwide available. Indeed, GNSS is performing very well in mild propagation conditions, achieving position and time synchronization accuracies down to the cm and ns levels, respectively. Nevertheless, the exploitation of GNSS in harsh propagation conditions typical of urban and indoor scenarios is very challenging, resulting in position errors of up to tens or even hundreds of meters, and timing accuracies of hundreds of ns. This thesis deals with ...

This thesis delves into the detection and localization aspects of distributed Wireless Sensor Networks (WSNs). Specifically, the research concentrates on WSNs in which sensors autonomously carry out detection tasks and transmit their decisions to a fusion center (FC). The FC’s role is to make a comprehensive decision about the presence of a specific event of interest and estimate its potential location. Given its broad significance, the thesis specializes in applying WSNs for industrial monitoring, particularly in the process and energy industry. Three distinct approaches are explored in this thesis: (i) per-sample/batch detection, (ii) quickest detection, and (iii) sequential detection. Each framework proposes a set of detection and associated localization rules. A primary objective of this work is to develop detection and localization strategies that leverage existing information about the monitored environment, bridging the gap between monitoring systems and the knowledge ...

In nowadays communication systems, error correction provides robust data transmission through imperfect (noisy) channels. Error correcting codes are a crucial component in most storage and communication systems – wired or wireless –, e.g. GSM, UMTS, xDSL, CD/DVD. At least as important as the data integrity issue is the recent realization that error correcting codes fundamentally change the trade-offs in system design. High-integrity, low redundancy coding can be applied to increase data rate, or battery life time or by reducing hardware costs, making it possible to enter mass market. When it comes to the design of error correcting codes and their properties, there are two main theories that play an important role in this work. Classical coding theory aims at finding the best code given an available block length. This thesis focuses on the ubiquitous Reed-Solomon codes, one of the major ...

This thesis deals with the problem of increasing the spectrum efficiency of cellular systems, by the use of antenna array base stations. The focus of the thesis is on downlink transmission in frequency division duplex systems, i.e., systems with different up and downlink carrier frequency. In a short summary the thesis: * Proposes five reasonable propagation models. * Uses these models to design and analyze three different beamformers: The maximum desired power (MDP), the summed interference to carrier ratio minimizing (SCIR) and the generalized-SCIR beamformer. * Introduces three capacity enhancement approaches: same sector frequency reuse (SSFR), reduced cluster size without nulling (RCS-WON) and reduced cluster size with nulling (RCS-WIN). * Proposes channel allocation, power control, and beamforming algorithms for these approaches. * Estimates the ``outage probability'' (probability of insufficient quality), for SICR-SSFR, SICR-RCS-WON and SICR-RCS-WIN, using simulations as well as ...

The number of cameras increases rapidly in squares, shopping centers, railway stations and airport halls. There are hundreds of cameras in the city center of Amsterdam. This is still modest compared to the tens of thousands of cameras in London, where citizens are expected to be filmed by more than three hundred cameras of over thirty separate Closed Circuit Television (CCTV) systems in a single day [84]. These CCTV systems include both publicly owned systems (railway stations, squares, airports) and privately owned systems (shops, banks, hotels). The main purpose of all these cameras is to detect, prevent and monitor crime and anti-social behaviour. Other goals of camera surveillance can be detection of unauthorized access, improvement of service, fire safety, etc. Since the terrorist attack on 9/11, detection and prevention of terrorist activities especially at high profiled locations such as airports, ...

It is well known that Ultra WideBand (UWB) transmission is inherently robust against small-scale-fading (SSF) that arises in multipath scattering environments, due to its large signal bandwidth. However, no model with a physical interpretation exists that relates the variations of received signal strength to the signal bandwidth and general channel parameters, like e.g. the average channel power delay profile. Such a model would be of relevance for e.g. system designers, who have to make tradeoffs between system aspects, like complexity and energy efficiency on one hand, and robustness against small-scale fading on the other hand. In this thesis, a model is presented that allows for such a tradeoff analysis, relating the average power delay profile parameters and signal bandwidth to the statistical properties of the SSF. Additionally, it is shown how the uncoded and coded BER of BPSK modulation can ...