Cognitive Radio is an innovative technology that allows the secondary unlicensed users to share the spectrum with licensed primary users to utilize the spectrum. For maximum utilization of spectrum, in cognitive radio network spectrum sensing is an important issue. Cognitive user under extreme shadowing and channel fading can‟t sense the primary licensed user signal correctly and thus to improve the performance of spectrum sensing, collaboration between secondary unlicensed users is required. In collaborative spectrum sensing the observation of each secondary user is received by a base station acting as a central entity, where a final conclusion about the presence or absence of the primary user signal is made using a particular decision and fusion rule. Due to spatially correlated shadowing the collaborative spectrum sensing performance decreases, and thus optimum secondary users must be selected to, not only improve spectrum sensing performance but also lessen the processing overhead of the central entity. A particular situation is depicted in the project where according to some performance parameters, first those optimum secondary users that have enough spatial separation and high average received SNR are selected using Genetic Algorithm, and then collaboration among these optimum secondary users is done to evaluate the performance. The collaboration of optimal secondary user providing high probability of detection and low probability of false alarm, for sensing the spectrum is compared with the collaboration of all the available secondary users in that radio environment. At the end a conclusion has been made that collaboration of selected optimum secondary users provides better performance, then the collaboration of all the secondary users available. / Cognitive Radio is an innovative technology that allows the secondary unlicensed users to share the spectrum with licensed primary users to utilize the spectrum. For maximum utilization of spectrum, in cognitive radio network spectrum sensing is an important issue. Cognitive user under extreme shadowing and channel fading can‟t sense the primary licensed user signal correctly and thus to improve the performance of spectrum sensing, collaboration between secondary unlicensed users is required. In collaborative spectrum sensing the observation of each secondary user is received by a base station acting as a central entity, where a final conclusion about the presence or absence of the primary user signal is made using a particular decision and fusion rule. Due to spatially correlated shadowing the collaborative spectrum sensing performance decreases, and thus optimum secondary users must be selected to, not only improve spectrum sensing performance but also lessen the processing overhead of the central entity. A particular situation is depicted in the project where according to some performance parameters, first those optimum secondary users that have enough spatial separation and high average received SNR are selected using Genetic Algorithm, and then collaboration among these optimum secondary users is done to evaluate the performance. The collaboration of optimal secondary user providing high probability of detection and low probability of false alarm, for sensing the spectrum is compared with the collaboration of all the available secondary users in that radio environment. At the end a conclusion has been made that collaboration of selected optimum secondary users provides better performance, then the collaboration of all the secondary users available.

Cognitive Radio Networks (CRNs) provide a solution for the spectrum scarcity problem facing the wireless communications community. However, due to the infancy of CRNs, further research is needed before we can truly benefit from CRNs. The basic concept of CRNs relies on utilizing the unused spectrum of a primary network, without interfering with the activity of primary users (PUs). In order to successfully achieve that, users in a CRN has to perform spectrum sensing, spectrum management, spectrum mobility, and spectrum sharing. The latter, which is the focus of our research, deals with how secondary users (SUs) share the unused spectrum. Furthermore, to be able to utilize CRNs in practical applications, a certain level of quality-of-service (QoS) should be guaranteed to SUs in such networks. QoS requirements vary according to the application. Interested in voice communications, we propose a packet scheduling scheme that orders the SUs' transmissions according to the packet dropping rate and the number of packets queued waiting for transmission. Two medium access control (MAC) layer protocols, based on the mentioned scheduling scheme, are proposed for a centralized CRN. In addition, the scheduling scheme is adapted for a distributed CRN, by introducing a feature that allows SUs to organize access to the available spectrum without the need for a central unit. Finally, extensive simulation based experiments are carried out to evaluate the proposed protocols and compare their performance with that of other MAC protocols designed for CRNs. These results reflect the effectiveness of our proposed protocols to guarantee the required QoS for voice packet transmission, while maintaining fairness among SUs in a CRN.

Cognitive Radio Networks (CRNs) provide a solution for the spectrum scarcity problem facing the wireless communications community. However, due to the infancy of CRNs, further research is needed before we can truly benefit from CRNs. The basic concept of CRNs relies on utilizing the unused spectrum of a primary network, without interfering with the activity of primary users (PUs). In order to successfully achieve that, users in a CRN has to perform spectrum sensing, spectrum management, spectrum mobility, and spectrum sharing. The latter, which is the focus of our research, deals with how secondary users (SUs) share the unused spectrum. Furthermore, to be able to utilize CRNs in practical applications, a certain level of quality-of-service (QoS) should be guaranteed to SUs in such networks. QoS requirements vary according to the application. Interested in voice communications, we propose a packet scheduling scheme that orders the SUs' transmissions according to the packet dropping rate and the number of packets queued waiting for transmission. Two medium access control (MAC) layer protocols, based on the mentioned scheduling scheme, are proposed for a centralized CRN. In addition, the scheduling scheme is adapted for a distributed CRN, by introducing a feature that allows SUs to organize access to the available spectrum without the need for a central unit. Finally, extensive simulation based experiments are carried out to evaluate the proposed protocols and compare their performance with that of other MAC protocols designed for CRNs. These results reflect the effectiveness of our proposed protocols to guarantee the required QoS for voice packet transmission, while maintaining fairness among SUs in a CRN.

Indiana University-Purdue University Indianapolis (IUPUI) / Primary users can create a user experience (UX) for others—secondary users— when interacting with a system in public. Common ground occurs when people have certain knowledge in common and each knows that they have this shared understanding. This research investigates how designing for a secondary UX improves common ground during a patient-provider first encounter. During formative work, patients and providers participated in telephonic interviews and answered online questionnaires so that their respective information requirements for clinical encounters could be understood. The outcome of the formative work was a smartphone application prototype to be used as the treatment in an experimental study. In a mixed methods study, with a patient role-player using the prototype during a simulated clinical encounter with 12 providers, the impact of the prototype upon secondary user satisfaction and common ground was assessed. The main finding was that the prototype was capable of positively impacting secondary user satisfaction and facilitating common ground in certain instances. Combining the notions of human-computer interaction design, common ground, and smartphone technology improved the efficiency and effectiveness of providers during the simulated face-to-face first encounter with a patient. The investigation substantiated the notion that properly designed interactive systems have the potential to provide a satisfactory secondary UX and facilitate common ground.

No description available.

Les bandes des fréquences, telles qu'elles sont aménagées aujourd'hui, sont statiquement allouées. Afin d'améliorer la productivité et l'efficacité de l'utilisation du spectre, une nouvelle approche a été proposée : le "partage dynamique du spectre". Les régulateurs, les industriels et les scientifiques ont examiné le partage des bandes fédérales entre les détenteurs de licences (utilisateurs primaires) et les nouveaux entrants (utilisateurs secondaires). La nature d'un tel partage peut faciliter les attaques d'inférence et mettre en péril les paramètres opérationnels des utilisateurs primaires. Par conséquent, le but de cette thèse est d'améliorer la confidentialité des utilisateurs primaires tout en permettant un accès secondaire au spectre. Premièrement, nous présentons une brève description des règles de partage et des exigences en termes de confidentialité dans les bandes fédérales. Nous étudions également les techniques de conservation de confidentialité (obscurcissement) proposées dans les domaines d'exploration et d'édition de données pour contrecarrer les attaques d'inférence. Ensuite, nous proposons et mettons en œuvre notre approche pour protéger la fréquence et la localisation opérationnelles contre les attaques d'inférence. La première partie étudie la protection de la fréquence opérationnelle en utilisant un obscurcissement inhérent et explicite pour préserver la confidentialité. La deuxième partie traite la protection de la localisation opérationnelle en utilisant la confiance comme principale contre-mesure pour identifier et atténuer un risque d'inférence. Enfin, nous présentons un cadre axé sur les risques qui résume notre travail et s'adapte à d'autres approches de protection de la confidentialité. Ce travail est soutenu par des modèles, des simulations et des résultats qui focalisent sur l'importance de quantifier les techniques de préservation de la confidentialité et d'analyser le compromis entre la protection de la confidentialité et l'efficacité du partage du spectre / Radio frequencies, as currently allocated, are statically managed. Spectrum sharing between commercial users and incumbent users in the Federal bands has been considered by regulators, industry, and academia as a great way to enhance productivity and effectiveness in spectrum use. However, allowing secondary users to share frequency bands with sensitive government incumbent users creates new privacy threats in the form of inference attacks. Therefore, the aim of this thesis is to enhance the privacy of the incumbent while allowing secondary access to the spectrum. First, we present a brief description of different sharing regulations and privacy requirements in Federal bands. We also survey the privacy-preserving techniques (i.e., obfuscation) proposed in data mining and publishing to thwart inference attacks. Next, we propose and implement our approach to protect the operational frequency and location of the incumbent operations from inferences. We follow with research on frequency protection using inherent and explicit obfuscation to preserve the incumbent's privacy. Then, we address location protection using trust as the main countermeasure to identify and mitigate an inference risk. Finally, we present a risk-based framework that integrates our work and accommodates other privacy-preserving approaches. This work is supported with models, simulations and results that showcase our work and quantify the importance of evaluating privacy-preserving techniques and analyzing the trade-off between privacy protection and spectrum efficiency

Είναι γνωστό από τη Θεωρία της Πληροφορίας, πως η δειγματοληψία σημάτων ακολουθεί το Θεώρημα των Shannon-Nyquist. Σύμφωνα με το θεώρημα αυτό, για την εκτέλεση της δειγματοληψίας ενός σήματος χωρίς απώλεια πληροφορίας, ο ρυθμός δειγματοληψίας αυτού θα πρέπει να είναι τουλάχιστον δύο φορές μεγαλύτερος από τη μεγαλύτερη συχνότητα που εμφανίζεται στο φάσμα του σήματος. Αυτή τη θεωρία κατάφερε – κατά κάποιο τρόπο - να ανατρέψει το 2006 μια νέα, αυτή της Συμπιεσμένης Καταγραφής που ξεκίνησε από δύο επιστημονικές εργασίες των Donoho, Candes, Romberg και Tao και η οποία έρχεται να αλλάξει τα έως σήμερα δεδομένα. Σήμερα, λίγα έτη αργότερα, μια αφθονία θεωρητικών πτυχών της συμπιεσμένης καταγραφής εξερευνάται ήδη σε περισσότερες από 1000 δημοσιεύσεις. Οι εφαρμογές αυτής της τεχνικής εκτείνονται και σε άλλα πεδία όπως η επεξεργασία εικόνας, η μαγνητική τομογραφία, η ανάλυση γεωφυσικών δεδομένων, η επεξεργασία εικόνας radar, η αστρονομία κ.α. Η μέθοδος της συμπιεσμένης καταγραφής ή αλλιώς Compressed Sensing ή Compressed Sampling, όπως αυτή είναι γνωστή στη βιβλιογραφία, στηρίζεται στη δυνατότητα ανακατασκευής αραιών σημάτων από πλήθος δειγμάτων αισθητά κατώτερο από αυτό που προβλέπει το θεωρητικό όριο του Nyquist. Έχει αποδειχθεί ότι, η ανακατασκευή αυτή είναι δυνατή όταν το σήμα ή έστω κάποιος μετασχηματισμός του περιέχει λίγα μη μηδενικά στοιχεία σε σχέση με το μήκος του. Στα πλαίσια αυτής της εργασίας παρουσιάζονται οι βασικές αρχές που διέπουν την ανακατασκευή αραιών σημάτων μέσω της επίλυσης υπο-ορισμένων συστημάτων γραμμικών εξισώσεων. Στη συγκεκριμένη εργασία, γίνεται μία προσπάθεια εφαρμογής της εν λόγω μεθόδου στα ανερχόμενα Cognitive Radio δίκτυα (Cognitive Radio Networks - CRN) τα οποία εμφανίζουν την ιδιότητα Spectrum Sharing. Σύμφωνα με αυτή την ιδιότητα, δηλαδή, το διαμοιρασμό του διαθέσιμου φάσματος, ο πρωταρχικός στόχος, είναι η ανίχνευση και η αναγνώριση των λεγόμενων spectrum holes σε ασύρματο περιβάλλον. Πιο συγκεκριμένα, παρουσιάζεται μια Distributed (κατανεμημένη) προσέγγιση συμπιεσμένης καταγραφής φάσματος για (τα ultra-) Wideband Cognitive Radio δίκτυα. Η τεχνική Compressed Sensing εφαρμόζεται σε τοπικά CRs του δικτύου, προκειμένου να ανιχνεύσει το υπερ-ευρύ φάσμα (ultra-wideband) με ρεαλιστική πολυπλοκότητα ανάκτησης του αρχικού σήματος. Οι φασματικές εκτιμήσεις από πολλαπλούς τοπικούς CRs του δικτύου «συνενώνονται» για να αποκομίσουν το χωρικό κέρδος ποικιλομορφίας (spatial diversity gain), το οποίο όσο αυξάνεται, βελτιώνει την ποιότητα ανίχνευσης, ειδικά στην περίπτωση των υπό εξασθένιση καναλιών (channel fading effect). Αρχικά, μελετάται ένας κατανεμημένος αλγόριθμος πλειοψηφίας (Distributed Consensus Algorithm) για να επιτευχθεί η συνεργασία κατά το στάδιο της ανίχνευσης της πληροφορίας που μεταφέρεται στο δίκτυο και έπειτα η αποστολή αυτής σε ένα fusion center. Αυτού του είδους ο distributed αλγόριθμος που χρησιμοποιεί μόνο one-hop επικοινωνία, συγκλίνει γρήγορα σε συνολικά βέλτιστες λύσεις που λειτουργούν με χαμηλό φόρτο επικοινωνίας και υπολογισμού που είναι ανάλογο του μεγέθους του δικτύου. Ένα σενάριο που εξετάζεται στο πλαίσιο αυτής της εργασίας, είναι η συγκεντρωτική ανίχνευση φάσματος ευρείας ζώνης με επικαλυπτόμενες συχνότητες ή αλλιώς κανάλια που είναι κοινά (frequency overlapping) σε Cognitive Radio δίκτυα και τα οποία, χρησιμοποιούν την τεχνική Compressed Sensing καθώς επίσης και την από κοινού ανακατασκευή (Joint Reconstruction) του αρχικού σήματος. Τέλος, προτείνεται ένα σενάριο, μιας κατανεμημένης αυτή τη φορά, τεχνικής ανίχνευσης φάσματος, που βασίζεται σε κανόνες πλειοψηφίας. Τα αποτελέσματα της προσομοίωσης, σε περιβάλλον Matlab, επιβεβαιώνουν την αποτελεσματικότητα αυτής της προτεινόμενης προσέγγισης, δηλαδή την ανίχνευση φάσματος, από συνδυασμό Cognitive Radio δικτύων με αραιά επικαλυπτόμενες συχνότητες. / It is well known from Information Theory, that the sampling of signals should be performed as dictated by the celebrated Shannon – Nyquist theorem. According to this theorem, in order to fully recover a signal from its samples, it must be sampled at a sampling rate that should be at least twice the bandwidth of the signal. This theory has been significantly extended over the past few years by the advent of the so-called Compressed Sensing theory, which first appeared in seminal scientific articles of Donoho, Candes, Romberg and Tao in 2006. Nowadays, an abundance of theoretical aspects of compressed sensing is already explored in more than 1000 articles. Τhis technique has been applied in various fields such as image processing, magnetic tomography, analysis of geophysical data, radar image processing, astronomy etc. The method of Compressed Sensing, also known as Compressed Sampling, is related to the reconstruction of sparse signals from far fewer samples or measurements than what the theoretical limit of Nyquist suggests. It has been proved that, this reconstruction is possible when the signal or a transformation of it, contains just a few non-zero elements with respect to its length. In this work, we firstly summarize the basic principles that condition the reconstruction of sparse signals via the solution of underdetermined systems of linear equations. Next, in this Master Thesis we aim at implementing Compressed Sensing method in emerging Cognitive Radio (CR) networks with spectrum sharing. The first cognitive task preceding any dynamic spectrum access is the sensing and identification of spectral holes in wireless environments. In more detail, this work is mainly concerned with a distributed compressed spectrum sensing approach for (ultra-)wideband CR networks. Compressed sensing is performed at local CRs to scan the very wide spectrum at practical signal-acquisition complexity. Meanwhile, spectral estimates from multiple local CR detectors are fused to collect spatial diversity gain, which improves the sensing quality especially under fading channels. Initially, a distributed consensus algorithm is analyzed for collaborative sensing and fusion in a scenario where all nodes are estimating the same spectral bands. Using only one-hop local communications, this distributed algorithm converges fast to the globally optimal solutions, at low communication and computation load scalable to the network size. Another scenario that has been investigated in this thesis is the joint wideband spectrum sensing in frequency overlapping cognitive radio networks, using centralized compressive sensing techniques. Finally, for the latter scenario, a distributed compressive sensing technique, based on consensus, has been proposed. Simulation results in Matlab environment verify the effectiveness of proposed joint spectrum sensing approach in jointly sparse frequency overlapping cognitive radio networks.