390 research outputs found

    Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

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    Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

    Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems

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    Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.Mohamed Elgendi, Björn Eskofier, Socrates Dokos, Derek Abbot

    Research on Cognitive Radio within the Freeband-AAF project

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    Dirty RF Signal Processing for Mitigation of Receiver Front-end Non-linearity

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    Moderne drahtlose Kommunikationssysteme stellen hohe und teilweise gegensätzliche Anforderungen an die Hardware der Funkmodule, wie z.B. niedriger Energieverbrauch, große Bandbreite und hohe Linearität. Die Gewährleistung einer ausreichenden Linearität ist, neben anderen analogen Parametern, eine Herausforderung im praktischen Design der Funkmodule. Der Fokus der Dissertation liegt auf breitbandigen HF-Frontends für Software-konfigurierbare Funkmodule, die seit einigen Jahren kommerziell verfügbar sind. Die praktischen Herausforderungen und Grenzen solcher flexiblen Funkmodule offenbaren sich vor allem im realen Experiment. Eines der Hauptprobleme ist die Sicherstellung einer ausreichenden analogen Performanz über einen weiten Frequenzbereich. Aus einer Vielzahl an analogen Störeffekten behandelt die Arbeit die Analyse und Minderung von Nichtlinearitäten in Empfängern mit direkt-umsetzender Architektur. Im Vordergrund stehen dabei Signalverarbeitungsstrategien zur Minderung nichtlinear verursachter Interferenz - ein Algorithmus, der besser unter "Dirty RF"-Techniken bekannt ist. Ein digitales Verfahren nach der Vorwärtskopplung wird durch intensive Simulationen, Messungen und Implementierung in realer Hardware verifiziert. Um die Lücken zwischen Theorie und praktischer Anwendbarkeit zu schließen und das Verfahren in reale Funkmodule zu integrieren, werden verschiedene Untersuchungen durchgeführt. Hierzu wird ein erweitertes Verhaltensmodell entwickelt, das die Struktur direkt-umsetzender Empfänger am besten nachbildet und damit alle Verzerrungen im HF- und Basisband erfasst. Darüber hinaus wird die Leistungsfähigkeit des Algorithmus unter realen Funkkanal-Bedingungen untersucht. Zusätzlich folgt die Vorstellung einer ressourceneffizienten Echtzeit-Implementierung des Verfahrens auf einem FPGA. Abschließend diskutiert die Arbeit verschiedene Anwendungsfelder, darunter spektrales Sensing, robuster GSM-Empfang und GSM-basiertes Passivradar. Es wird gezeigt, dass nichtlineare Verzerrungen erfolgreich in der digitalen Domäne gemindert werden können, wodurch die Bitfehlerrate gestörter modulierter Signale sinkt und der Anteil nichtlinear verursachter Interferenz minimiert wird. Schließlich kann durch das Verfahren die effektive Linearität des HF-Frontends stark erhöht werden. Damit wird der zuverlässige Betrieb eines einfachen Funkmoduls unter dem Einfluss der Empfängernichtlinearität möglich. Aufgrund des flexiblen Designs ist der Algorithmus für breitbandige Empfänger universal einsetzbar und ist nicht auf Software-konfigurierbare Funkmodule beschränkt.Today's wireless communication systems place high requirements on the radio's hardware that are largely mutually exclusive, such as low power consumption, wide bandwidth, and high linearity. Achieving a sufficient linearity, among other analogue characteristics, is a challenging issue in practical transceiver design. The focus of this thesis is on wideband receiver RF front-ends for software defined radio technology, which became commercially available in the recent years. Practical challenges and limitations are being revealed in real-world experiments with these radios. One of the main problems is to ensure a sufficient RF performance of the front-end over a wide bandwidth. The thesis covers the analysis and mitigation of receiver non-linearity of typical direct-conversion receiver architectures, among other RF impairments. The main focus is on DSP-based algorithms for mitigating non-linearly induced interference, an approach also known as "Dirty RF" signal processing techniques. The conceived digital feedforward mitigation algorithm is verified through extensive simulations, RF measurements, and implementation in real hardware. Various studies are carried out that bridge the gap between theory and practical applicability of this approach, especially with the aim of integrating that technique into real devices. To this end, an advanced baseband behavioural model is developed that matches to direct-conversion receiver architectures as close as possible, and thus considers all generated distortions at RF and baseband. In addition, the algorithm's performance is verified under challenging fading conditions. Moreover, the thesis presents a resource-efficient real-time implementation of the proposed solution on an FPGA. Finally, different use cases are covered in the thesis that includes spectrum monitoring or sensing, GSM downlink reception, and GSM-based passive radar. It is shown that non-linear distortions can be successfully mitigated at system level in the digital domain, thereby decreasing the bit error rate of distorted modulated signals and reducing the amount of non-linearly induced interference. Finally, the effective linearity of the front-end is increased substantially. Thus, the proper operation of a low-cost radio under presence of receiver non-linearity is possible. Due to the flexible design, the algorithm is generally applicable for wideband receivers and is not restricted to software defined radios

    Development of a Resource Manager Framework for Adaptive Beamformer Selection

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    Adaptive digital beamforming (DBF) algorithms are designed to mitigate the effects of interference and noise in the electromagnetic (EM) environment encountered by modern electronic support (ES) receivers. Traditionally, an ES receiver employs a single adaptive DBF algorithm that is part of the design of the receiver system. While the traditional form of receiver implementation is effective in many scenarios it has inherent limitations. This dissertation proposes a new ES receiver framework capable of overcoming the limitations of traditional ES receivers. The proposed receiver framework is capable of forming multiple, independent, simultaneous adaptive digital beams toward multiple signals of interest in an electromagnetic environment. The main contribution of the research is the development, validation, and verification of a resource manager (RM) algorithm. The RM estimates a set of parameters that characterizes the electromagnetic environment and selects an adaptive digital beam forming DBF algorithm for implementation toward all each signal of interest (SOI) in the environment. Adaptive DBF algorithms are chosen by the RM based upon their signal to interference plus noise ratio (SINR) improvement ratio and their computational complexity. The proposed receiver framework is demonstrated to correctly estimate the desired electromagnetic parameters and select an adaptive DBF from the LUT

    A Multi-Purpose Aerial Software Defined Radio Platform

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    This project focuses on incorporating two new technologies, drones and software defined radios, to detect and localize relevant wireless signals with increased maneuverability. The objective lies in building a platform for wireless signal mapping for search and rescue purposes. The platform prototype will be a baseline for future development through the recommendations provided in this report
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