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Intelligent scatter radio, RF harvesting analysis, and resource allocation for ultra-low-power Internet-of-Things

Alevizos Panagiotis

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Extent157 pagesen
TitleIntelligent scatter radio, RF harvesting analysis, and resource allocation for ultra-low-power Internet-of-Thingsel
CreatorAlevizos Panagiotisen
CreatorΑλεβιζος Παναγιωτηςel
Contributor [Thesis Supervisor]Bletsas Aggelosen
Contributor [Thesis Supervisor]Μπλετσας Αγγελοςel
Contributor [Committee Member]Karystinos Georgiosen
Contributor [Committee Member]Καρυστινος Γεωργιοςel
Contributor [Committee Member]Deligiannakis Antoniosen
Contributor [Committee Member]Δεληγιαννακης Αντωνιοςel
Contributor [Committee Member]Lagoudakis Michaelen
Contributor [Committee Member]Λαγουδακης Μιχαηλel
Contributor [Committee Member]Paterakis Michalisen
Contributor [Committee Member]Πατερακης Μιχαληςel
Contributor [Committee Member]Liavas Athanasiosen
Contributor [Committee Member]Λιαβας Αθανασιοςel
Contributor [Committee Member]Sidiropoulos Nikosen
Contributor [Committee Member]Σιδηροπουλος Νικοςel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitTechnical University of Crete::School of Electrical and Computer Engineeringen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστώνel
Content SummaryUbiquitous sensing anywhere and anytime is envisioned under the general umbrella of Internet-of-Things (IoT). The objective of this dissertation is to contribute ultra-low-power IoT technology, exploiting novel concepts in wireless communications and networking. The first part of this work studies far field radio frequency (RF) energy harvesting, taking into account non-linearity, sensitivity, and saturation effects of existing rectenna circuits. The proposed methodology offers the statistics of the harvested power for any given rectenna model, under mild assumptions. It is also demonstrated that currently-used linear RF harvesting models in the literature deviate from reality. In the second part, scatter radio technology, i.e., communication via means of reflection, is studied in order to enable ultra-low-power radio communication with single-transistor front-ends. The thesis proposes low-complexity detection schemes as well as decoding techniques for short block-length channel codes, tailored to coherent, as well as noncoherent reception of scatter radio. The goal was to target resource-constrained, i.e., hardware-``thin'', scatter radio tags and simple, low-latency receivers. The developed detection and decoding algorithms are based on composite hypothesis testing framework. Interestingly, it is demonstrated that the bit error rate (BER) performance gap between coherent and noncoherent reception depends on the kind of channel codes employed, the fading conditions, as well as the utilized coding interleaving depth. The third part of this work proposes a multistatic scatter radio network architecture, based on orthogonal signaling, contrasted to existing architectures for dyadic Nakagami fading. Orthogonal signaling allows for collision free multi-user access for low-bitrate tags. It is shown that the proposed scatter radio architecture offers better diversity order, more reliable reception, as well as better field coverage, while demonstrating smaller sensitivity to the topology of the scatter radio tags, compared to existing monostatic architecture. Finally, the last part of the dissertation studies resource allocation in multi-cell backscatter sensor networks (BSNs). The average long-term signal-to interference-plus-noise ratio (SINR) of linear detectors is explored for multi-cell BSNs, and subsequently harnessed to allocate frequency sub-channels at tags. The proposed resource allocation algorithm is based on the Max-Sum inference algorithm and its convergence-complexity trade-off is quantified. Experimental studies in an outdoor scatter radio testbed corroborate the theoretical findings of this work. Hopefully, this thesis will establish the viability of scatter radio for ultra-low-power communications, enabling critical current and future IoT applications.en
Type of ItemΔιδακτορική Διατριβήel
Type of ItemDoctoral Dissertationen
Date of Item2017-12-04-
Date of Publication2017-
SubjectWireless communicationsen
SubjectBackscatter radiosen
SubjectWireless sensor networksen
SubjectDetection and estimationen
SubjectBistatic architectureen
SubjectFrequency-shift keyingen
SubjectResource allocationen
Bibliographic CitationPanagiotis Alevizos, "Intelligent scatter radio, RF harvesting analysis, and resource allocation for ultra-low-power Internet-of-Things", Doctoral Dissertation, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2017en

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