Yes / This paper presents the architectural design, software implementation, the validation and flight trial results of an aeronautical communications system developed within the Seamless Aeronautical Networking through integration of Data links Radios and Antennas (SANDRA) project funded by the European 7th Framework Aeronautics and Transport Programme. Based on Software Defined Radio (SDR) techniques, an Integrated Modular Radio (IMR) platform was developed to accommodate several radio technologies. This can drastically reduce the size, weight and cost in avionics with respect to current radio systems implemented as standalone equipment. In addition, the modular approach ensures the possibility to dynamically reconfigure each radio element to operate on a specific type of radio link. A radio resource management (RRM) framework is developed in the IMR consisting of a communication manager for the resource allocation and management of the different radio links and a radio adaptation manager to ensure protocol convergence through IP. The IMR has been validated though flight trials held at Oberpfaffenhofen, Germany in June 2013. The results presented in the paper validate the flexibility and scalability of the IMR platform and demonstrate seamless service coverage across different airspace domains through interworking between the IMR and other components of the SANDRA network. / European Commission

This dissertation presents an empirical approach to identifying decisions for adapting cognitive radio parameters with no a priori knowledge of the environment. Cognitively inspired radios, attempt to combine observed metrics of system performance with artificial intelligence decision-making algorithms. Current architectures trend towards hybrid combinations of heuristics, such as genetic algorithms (GA) and experiential methods, such as case-based reasoning (CBR). A weakness in the GA is its reliance on limited mathematical models for estimating bit error rate, packet error rate, throughput, and signal-to-noise ratio. The CBR approach is similarly limited by its dependency on past experiences. Both methods have potential to suffer in environments not previously encountered. In contrast, the statistical methods identify performance estimation models based on exercising defined experimental designs. This represents an experiential decision-making process formed in the present rather than the past. There are three core contributions from this empirical framework: 1) it enables a new approach to decision making based on empirical estimation models of system performance, 2) it provides a systematic method for initializing cognitive engine configuration parameters, and 3) it facilitates deeper understanding of system behavior by quantifying parameter significance, and interaction effects. Ultimately, this understanding enables simplification of system models by identifying insignificant parameters. This dissertation defines an abstract framework that enables application of statistical approaches to cognitive radio systems regardless of its platform or application space. Specifically, it assesses factorial design of experiments and response surface methodology (RSM) to an over-the-air wireless radio link. Results are compared to a benchmark GA cognitive engine. The framework is then used for identifying software-defined radio initialization settings. Taguchi designs, a related statistical method, are implemented to identify initialization settings of a GA. / Ph. D.

Global System for Mobile Communications (GSM) networks are receiving increasing attention in the open-source community. Open-source software allows for deployment of a mobile cellular network with lower costs, more customization, and scalable control. Two popular projects have emerged that offer varying network architectures and allow users to implement a GSM network in different capacities depending on individual needs. Osmocom provides more network control and scalability but requires commercial Base Transceiver Station (BTS) hardware with limited availability and closed source code. OpenBTS provides minimal GSM network functionality with more easily available and open-source hardware; however, it does not allow multi-cellular network configuration. This thesis offers a significant contribution towards a fully open-source GSM network by integrating the two major open-source communities, Osmocom and OpenBTS. Specifically, the Osmo-USRP program provides an inter-layer interface between the different network architectures of two GSM base station projects. Inter-layer primitive messages are processed in a thread multiplexer that manages logical channels across the interface. Downstream flow control is implemented in order to receive data frames on time for transmitting at the appropriate GSM frame number (FN). Uplink measurements, which are necessary for decision making in the Base Station Controller (BSC), are also gathered in the physical layer of Osmo-USRP and reported to Osmocom. Osmo-USRP operation is tested using a Universal Software Radio Peripheral (USRP), a relatively inexpensive and accessible Software-Defined Radio (SDR). Standard GSM events are investigated for single cell and multi-cellular network configurations. These tests include subscriber authentication and encryption, location updating, International Mobile Subscriber Identity (IMSI) attach and detach, Short Message Service (SMS) storage and delivery, voice calls with the full-rate audio codec, and uplink and downlink measurement reporting. While most functionality is successfully tested, inter-cell handover is not currently implemented. Further details on the proposed implementation of program limitations, especially inter-cell handover, are also discussed. / Master of Science

A radio direction finding (DF) system is an antenna array and a receiver arranged in a combination to determine the azimuth angle of a distant emitter. Basically, all DF systems derive the emitter location from an initial determination of the angle-of-arrival (AOA). Radio direction finding techniques have classically been based on multiple-antenna systems employing multiple receivers. Classic techniques such as MUSIC [1][2] and ESPRIT use simultaneous phase information from each antenna to estimate the angle-of-arrival of the signal of interest. In many scenarios (e.g., hand-held systems), however, multiple receivers are impractical. Thus, single channel techniques are of interest, particularly in mobile scenarios. Although the amount of existing research for single channel DF is considerably less than for multi-channel direction finding, single channel direction finding techniques have been previously investigated. Since many of the single channel direction finding techniques are older analog techniques and have been analyzed in previous work, we will investigate a new single channel direction finding technique that takes specific advantage of digital capabilities. Specifically, we propose a phase-based method that uses a bank of Phase-Locked Loops (PLLs) in combination with an eight-element circular array. Our method is similar to the Pseudo-Doppler method in that it samples antennas in a circular array using a commutative switch. In the proposed approach the sampled data is fed to a bank of PLLs which track the phase on each element. The parallel PLLs are implemented in software and their outputs are fed to a signal processing block that estimates the AOA. This thesis presents the details of the new Phase-Locked Loop (PLL) algorithm and compares its performance to existing single channel DF techniques such as the Watson-Watt and the Pseudo-Doppler techniques. We also describe the implementation of the PLL algorithm on a DRS Signal Solutions, Incorporated (DRS-SS) WJ-8629A Software Definable Receiver with Sunrise™ Technology and present measured performance results. / Master of Science

The rise of 5G and beyond systems has fuelled research in merging machine learning with wireless communications to achieve cognitive radios. However, the portability and limited power supply of radio frequency devices limits engineers' ability to combine them with powerful predictive models. This hinders the ability to support advanced 5G applications such as device-to-device (D2D) communication and dynamic spectrum sharing (DSS). This challenge has inspired a wave of research in energy efficient machine learning hardware with low computational and area overhead. In particular, hardware implementations of the delayed feedback reservoir (DFR) model show promising results for meeting these constraints while achieving high accuracy in cognitive radio applications. This thesis answers two research questions surrounding the applicability of FPGA DFR systems for DSS. First, can a DFR network implemented on an FPGA run faster and with lower power than a purely software approach? Second, can the system be implemented efficiently on an edge device running at less than 10 watts? Two systems are proposed that prove FPGA DFRs can achieve these feats: a mixed-signal circuit, followed by a high-level synthesis circuit. The implementations execute up to 58 times faster, and operate at more than 90% lower power than the software models. Furthermore, the lowest recorded average power of 0.130 watts proves that these approaches meet typical edge device constraints. When validated on the NARMA10 benchmark, the systems achieve a normalized error of 0.21 compared to state-of-the-art error values of 0.15. In a DSS task, the systems are able to predict spectrum occupancy with up to 0.87 AUC in high noise, multiple input, multiple output (MIMO) antenna configurations compared to 0.99 AUC in other works. At the end of this thesis, the trade-offs between the approaches are analyzed, and future directions for advancing this study are proposed. / Master of Science / The rise of 5G and beyond systems has fuelled research in merging machine learning with wireless communications to achieve cognitive radios. However, the portability and limited power supply of radio frequency devices limits engineers' ability to combine them with powerful predictive models. This hinders the ability to support advanced 5G and internet-of-things (IoT) applications. This challenge has inspired a wave of research in energy efficient machine learning hardware with low computational and area overhead. In particular, hardware implementations of a low complexity neural network model, called the delayed feedback reservoir, show promising results for meeting these constraints while achieving high accuracy in cognitive radio applications. This thesis answers two research questions surrounding the applicability of field-programmable gate array (FPGA) delayed feedback reservoir systems for wireless communication applications. First, can this network implemented on an FPGA run faster and with lower power than a purely software approach? Second, can the network be implemented efficiently on an edge device running at less than 10 watts? Two systems are proposed that prove the FPGA networks can achieve these feats. The systems demonstrate lower power consumption and latency than the software models. Additionally, the systems maintain high accuracy on traditional neural network benchmarks and wireless communications tasks. The second implementation is further demonstrated in a software-defined radio architecture. At the end of this thesis, the trade-offs between the approaches are analyzed, and future directions for advancing this study are proposed.

The history of Software-Defined Radios (SDRs) epitomizes innovation in wireless communication. Initially serving military needs, SDRs swiftly transitioned to civilian applications, revolutionizing communication. This thesis explores SDR applications such as Spectrum Scanning Systems, Contraband Cellphone Detection, and Human Activity Recognition via Wi-Fi signals. SDRs empower Spectrum Scanning Systems to monitor and analyze radio frequencies, optimizing spectrum allocation for seamless wireless communication. In Contraband Cellphone Detection, SDRs identify unauthorized signals in restricted areas, bolstering security efforts by thwarting illicit cellphone usage. Human Activity Recognition utilizes Raspberry Pi 3B+ to track movement patterns via Wi-Fi signals, offering insights across various sectors. Additionally, the thesis conducts a comparative analysis of Wi-Fi-based Human Activity Recognition and Radar for accuracy assessment. SDRs continue to drive innovation, enhancing wireless communication and security in diverse domains, from defense to healthcare and beyond.

The objective of this dissertation is to better understand the impact of the range extension and interference effects of opportunistic large arrays (OLAs), in the context of cooperative routing in multi-hop ad hoc networks. OLAs are a type of concurrent cooperative transmission (CCT), in which the number and location of nodes that will participate in a particular CCT cannot be known a priori. The motivation of this research is that the previous CCT research simplifies or neglects significant issues that impact the CCT-based network performance. Therefore, to develop and design more efficient and realistic OLA-based protocols, we clarify and examine through experimentation and analysis the simplified or neglected characteristics of CCT, which should be considered in the network-level system design. The main contributions of this research are (i) intra-flow interference analysis and throughput optimization in both disk- and strip-shaped networks, for multi-packet OLA transmission, (ii) CCT link modeling focusing on path-loss disparity and link asymmetry, (iii) demonstration of CCT range-extension and OLA-based routing using a software-defined radio (SDR) test-bed, (iv) a new OLA-based routing protocol with practical error control algorithm. In the throughput optimization in presence of the intra-channel interference, we analyze the feasibility condition of spatially pipelined OLA transmissions using the same channel and present numerical results with various system parameters. In the CCT link model, we provide the impact of path-loss disparity that are inherent in a virtual multiple-input-single-output (VMISO) link and propose an approximate model to calculate outage rates in high signal-to-noise-ratio (SNR) regime. Moreover, we present why link asymmetry is relatively more severe in CCT compared to single-input-single-output (SISO) links. The experimental studies show actual measurement values of the CCT range extension and realistic performance evaluation of OLA-based routing. Lastly, OLA with primary route set-up (OLA-PRISE) is proposed with a practical route recovery technique.

This dissertation develops and analyzes several techniques for improving channel estimation and tracking performance in distributed multi-input multi-output (D-MIMO) wireless communication systems. D-MIMO communication systems have been studied for the last decade and are known to offer the benefits of antenna arrays, e.g., improved range and data rates, to systems of single-antenna devices. D-MIMO communication systems are considered a promising technology for future wireless standards including advanced cellular communication systems. This dissertation considers problems related to channel estimation and tracking in D-MIMO communication systems and is focused on three related topics: (i) characterizing oscillator stability for nodes in D-MIMO systems, (ii) the development of an optimal unified tracking framework and a performance comparison to previously considered sub-optimal tracking approaches, and (iii) incorporating independent kinematics into dynamic channel models and using accelerometers to improve channel tracking performance. A key challenge of D-MIMO systems is estimating and tracking the time-varying channels present between each pair of nodes in the system. Even if the propagation channel between a pair of nodes is time-invariant, the independent local oscillators in each node cause the carrier phases and frequencies and the effective channels between the nodes to have random time-varying phase offsets. The first part of this dissertation considers the problem of characterizing the stability parameters of the oscillators used as references for the transmitted waveforms. Having good estimates of these parameters is critical to facilitate optimal tracking of the phase and frequency offsets. We develop a new method for estimating these oscillator stability parameters based on Allan deviation measurements and compare this method to several previously developed parameter estimation techniques based on innovation covariance whitening. The Allan deviation method is validated with both simulations and experimental data from low-precision and high-precision oscillators. The second part of this dissertation considers a D-MIMO scenario with $N_t$ transmitters and $N_r$ receivers. While there are $N_t imes N_r$ node-to-node pairwise channels in such a system, there are only $N_t + N_r$ independent oscillators. We develop a new unified tracking model where one Kalman filter jointly tracks all of the pairwise channels and compare the performance of unified tracking to previously developed suboptimal local tracking approaches where the channels are not jointly tracked. Numerical results show that unified tracking tends to provide similar beamforming performance to local tracking but can provide significantly better nullforming performance in some scenarios. The third part of this dissertation considers a scenario where the transmit nodes in a D-MIMO system have independent kinematics. In general, this makes the channel tracking problem more difficult since the independent kinematics make the D-MIMO channels less predictable. We develop dynamics models which incorporate the effects of acceleration on oscillator frequency and displacement on propagation time. The tracking performance of a system with conventional feedback is compared to a system with conventional feedback and local accelerometer measurements. Numerical results show that the tracking performance is significantly improved with local accelerometer measurements.

Le concept de radio logicielle (SDR) est une solution pertinente pour concevoir des équipements multi-standards. Une façon de réaliser de tels équipements est d'identifier les fonctions et opérateurs communs entre les standards. Cette approche s’appelle la paramétrisation et est divisée en deux catégories : l'approche pragmatique qui est une version pratique pour créer et développer des opérateurs communs à partir d’opérateurs existants, et l'approche théorique dont l’objectif est de réaliser une exploration graphique d’un équipement multi-standards selon différents niveaux de granularité, accompagnée d’un problème d'optimisation. C’est cette dernière approche qui a constitué le sujet de base de cette thèse. Ainsi, une fonction de coût doit être optimisée afin de sélectionner les opérateurs communs entre les différentes normes, ce qui permet de proposer une configuration optimale à partir de laquelle sont déduits les opérateurs communs. Dans notre travail, nous avons dans un premier temps modélisé théoriquement la structure graphique d’un système multi-standards par un hypergraphe orienté. En outre, nous avons fourni une expression mathématique alternative de la fonction de coût suggérée, en utilisant des définitions propres à la théorie des graphes. Ensuite, nous avons montré que le problème d'optimisation associé était un problème NP sous une certaine contrainte, ce qui a entraîné une preuve d'exclusion de certaines configurations dont les coûts ne peuvent être minimaux. Ceci a constitué la deuxième contribution de cette thèse. Enfin, nous avons proposé un nouvel algorithme permettant de résoudre le problème d'optimisation donné, et dont l'intérêt est de donner une solution optimale du problème au lieu d’une solution approchée fournie par les méthodes heuristiques classiques. Un programme associé à cet algorithme a été développé en langage C, puis appliqué à plusieurs exemples de cas génériques afin d’en étudier les performances. / The Software-Defined Radio (SDR) concept is emerging as a potential and efficient solution for designing flexible future-proof multi-standard systems. A way of realizing a multi-standard terminal is to identify the appropriate common functions and operators inside and between the standards. This is what's called the parametrization approach, which can be divided into two categories: the pragmatic approach which is a practical version to create and develop common operators, and the theoretical approach which represents a graphical exploration of the SDR multi-standard system at different levels of granularity accompanied with an optimization problem. It’s in this last approach where our thesis subject dwells. In this context, a suggested cost function (in previous work) has to be optimized in order to select the convenient common operators between the different standards, enabling to construct an optimal design. In our work, we theoretically model a previously proposed graph structure of an SDR multi-standard system as a directed hypergraph as well as provide an alternative mathematical formal expression of the suggested cost function, using various graph theoretical definitions and notations. Afterwards, we prove that the associated optimization problem is an NP-problem under a certain constraint, which entails a proof of exclusion of some particular design options when searching for a minimum cost design. This was the second contribution in this thesis before we finally present a new algorithm (which exploits various modelization aspects of directed hypergraphs) that can solve the optimization problem, whose interest is in it giving an exact-optimal solution to our problem instead of a near-optimal one provided by heuristics. A program code for this algorithm was developed in C-language, and then it was applied on several generic case examples in order to explore its performance skills.

Twenty-first century Field-Programmable Gate Arrays (FPGAs) are no longer used for implementing simple “glue logic” functions. They have become complex arrays of reconfigurable logic resources and memories as well as highly optimised functional blocks, capable of implementing large systems on a single chip. Moreover, Dynamic Partial Reconfiguration (DPR) capability permits to adjust some logic resources on the chip at runtime, whilst the rest are still performing active computations. During the last few years, DPR has become a hot research topic with the objective of building more reliable, efficient and powerful electronic systems. For instance, DPR can be used to mitigate spontaneously occurring bit upsets provoked by radiation, or to jiggle around the FPGA resources which progressively get damaged as the silicon ages. Moreover, DPR is the enabling technology for a new computing paradigm which combines computation in time and space. In Reconfigurable Computing (RC), a battery of computation-specific circuits (“hardware tasks”) are swapped in and out of the FPGA on demand to hold a continuous stream of input operands, computation and output results. Multitasking, adaptation and specialisation are key properties in RC, as multiple swappable tasks can run concurrently at different positions on chip, each with custom data-paths for efficient execution of specific computations. As a result, considerable computational throughput can be achieved even at low clock frequencies. However, DPR penetration in the commercial market is still testimonial, mainly due to the lack of suitable high-level design tools to exploit this technology. Indeed, currently, special skills are required to successfully develop a dynamically reconfigurable application. In light of the above, this thesis aims at bridging the gap between high-level application and low-level DPR technology. Its main objective is to develop Operating System (OS)-like support for high-level software-centric application developers in order to exploit the benefits brought about by DPR technology, without having to deal with the complex low-level hardware details. The developed solution in this thesis is named as R3TOS, which stands for Reliable Reconfigurable Real-Time Operating System. R3TOS defines a flexible infrastructure for reliably executing reconfigurable hardware-based applications under real-time constraints. In R3TOS, the hardware tasks are scheduled in order to meet their computation deadlines and allocated to non-damaged resources, keeping the system fault-free at all times. In addition, R3TOS envisages a computing framework whereby both hardware and software tasks coexist in a seamless manner, allowing the user to access the advanced computation capabilities of modern reconfigurable hardware from a software “look and feel” environment. This thesis covers all of the design and implementation aspects of R3TOS. The thesis proposes a novel EDF-based scheduling algorithm, two novel task allocation heuristics (EAC and EVC) and a novel task allocation strategy (called Snake), addressing many RC-related particularities as well as technological constraints imposed by current FPGA technology. Empirical results show that these approaches improve on the state of the art. Besides, the thesis describes a novel way to harness the internal reconfiguration mechanism of modern FPGAs to performinter-task communications and synchronisation regardless of the physical location of tasks on-chip. This paves the way for implementing more sophisticated RC solutions which were only possible in theory in the past. The thesis illustrates R3TOS through a proof-of-concept prototype with two demonstrator applications: (1) dependability oriented control of the power chain of a railway traction vehicle, and (2) datastreaming oriented Software Defined Radio (SDR).