An Analytical Model of Packet Collisions in IEEE 802.15.4 Wireless Networks

Numerous studies showed that concurrent transmissions can boost wireless network performance despite collisions. While these works provide empirical evidence that concurrent transmissions may be received reliably, existing signal capture models only partially explain the root causes of this phenomenon. We present a comprehensive mathematical model that reveals the reasons and provides insights on the key parameters affecting the performance of MSK-modulated transmissions. A major contribution is a closed-form derivation of the receiver bit decision variable for arbitrary numbers of colliding signals and constellations of power ratios, timing offsets, and carrier phase offsets. We systematically explore the root causes for successful packet delivery under concurrent transmissions across the whole parameter space of the model. We confirm the capture threshold behavior observed in previous studies but also reveal new insights relevant for the design of optimal protocols: We identify capture zones depending not only on the signal power ratio but also on time and phase offsets.Comment: Accepted for publication in the IEEE Transactions on Wireless Communications under the title "On the Reception of Concurrent Transmissions in Wireless Sensor Networks.

Key Generation in Wireless Sensor Networks Based on Frequency-selective Channels - Design, Implementation, and Analysis

Key management in wireless sensor networks faces several new challenges. The scale, resource limitations, and new threats such as node capture necessitate the use of an on-line key generation by the nodes themselves. However, the cost of such schemes is high since their secrecy is based on computational complexity. Recently, several research contributions justified that the wireless channel itself can be used to generate information-theoretic secure keys. By exchanging sampling messages during movement, a bit string can be derived that is only known to the involved entities. Yet, movement is not the only possibility to generate randomness. The channel response is also strongly dependent on the frequency of the transmitted signal. In our work, we introduce a protocol for key generation based on the frequency-selectivity of channel fading. The practical advantage of this approach is that we do not require node movement. Thus, the frequent case of a sensor network with static motes is supported. Furthermore, the error correction property of the protocol mitigates the effects of measurement errors and other temporal effects, giving rise to an agreement rate of over 97%. We show the applicability of our protocol by implementing it on MICAz motes, and evaluate its robustness and secrecy through experiments and analysis.Comment: Submitted to IEEE Transactions on Dependable and Secure Computin

Synthetic Genetic Tracing of Molecular and Cellular Heterogeneity in Glioblastoma

Das Glioblastom (GBM) repräsentiert den am schwierigsten zu behandelnden primären soliden Tumor des Zentralnervensystems dar, trotz der intensiv wachsenden Zahl von Studien zu seinen molekularen und zellulären Eigenschaften. Obwohl die GBM-Therapie aggressiv ist und chirurgische Resektion, Strahlentherapie und Chemotherapie umfasst, ist ein Wiederauftreten des Tumors unvermeidlich. Die GBM-Behandlungsresistenz ist mit genetischer und zellulärer Heterogenität sowie phänotypischer Plastizität verbunden. Um das Verständnis der Heterogenität des Glioblastoms zu vertiefen, haben wir maßgeschneiderte genetische Tracing-Strategien für subtypspezifische Transkriptionszustände aus Glioblastom-Patientensignaturen entwickelt. In GBM-Zellen ermöglichte uns unsere neuartige Technologie, intrinsische und nicht-zellautonome Bestimmungsfaktoren von Zellzuständen zu identifizieren. In vitro und in vivo konnten wir zeigen, dass sich der mesenchymale GBM-Subtyp als adaptive Identität in Gegenwart von Mikroumgebungssignalen ausbildet und durch Entzündungs- und Differenzierungsprogramme reguliert wird. Wir haben gezeigt, dass die Ausbildung eines mesenchymalen Zellzustand adaptiv und reversibel ist und durch verschiedene Auslöser wie externer Signaltransduktion und ionisierende Strahlung mit teilweise überlappenden transkriptionellen Signaturen eingenommen werden kann. Insbesondere konnten wir mithilfe synthetischer Locus-Kontrollregionen (sLCRs) eine Interaktion zwischen Zellen des angeborenen Immunsystems und Glioma-Zellen aufdecken, wodurch die Tumorzellen in einen mesenchymalen Zustand versetzt wurden, der mit einer erhöhten Resistenz gegen Chemotherapie verbunden ist. Hier bauen wir auf diesem innovativen Ansatz auf, um Übergänge von Zellzuständen in komplexen biologischen Umgebungen zu verfolgen, mit einem Schwerpunkt auf der zellulären Wechselwirkung zwischen gesunden und Tumorzellen im Zusammenhang mit phänotypischer Plastizität und therapeutischer Resistenz. Darüber hinaus bietet diese Methode ein breites translationales Potenzial für die Anwendung auf andere Forschungsgebiete, einschließlich der Entwicklungsbiologie oder der regenerativen Medizin.Glioblastoma (GBM) remains the most difficult primary solid tumor of the central nervous system despite the intensively growing body of research on its molecular and cellular characteristics. Whereas GBM treatment is aggressive and involves surgical resection, radiotherapy, and chemotherapy, tumor recurrence is unavoidable. GBM treatment resistance is associated with genetic and cellular heterogeneity, as well as phenotypic plasticity. To improve understanding of Glioblastoma heterogeneity, we developed custom genetic tracing strategies for subtype-specific transcriptional states from Glioblastoma patient signatures. In GBM cells, our novel technology enabled us to identify intrinsic and non-cell autonomous determinants of cell fate commitment. In vitro and in vivo, we discovered that the mesenchymal GBM adapts in the presence of microenvironmental signaling and is regulated by inflammatory and differentiation programs. We demonstrated that cell fate commitment towards a mesenchymal state is adaptive and reversible and occurs through partially overlapping transcriptional responses, including external signaling and ionizing radiation. Importantly, using synthetic locus control regions (sLCRs), we were able to uncover crosstalk between innate immune cells and glioma-initiating cells, directing the tumor cells into a mesenchymal state linked to increased resistance to chemotherapy. Here, we build on this innovative approach to trace cell fate transitions in complex biological settings, with a focus on the cellular crosstalk between malignant and non-tumor cells in the context of phenotypic plasticity and therapeutic resistance. Beyond that, this method offers the broad translational potential to be applied to other fields of research, including developmental biology or regenerative medicine