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Motivated by the numerous healthcare applications of molecular communicationwithin Internet of Bio-Nano Things (IoBNT), this work addresses the problem ofabnormality detection in a blood vessel using multiple biological embeddedcomputing devices called cooperative biological nanomachines (CNs), and acommon receiver called the fusion center (FC). Due to blood flow inside avessel, each CN and the FC are assumed to be mobile. In this work, each of theCNs perform abnormality detection with certain probabilities of detection andfalse alarm by counting the number of molecules received from a source, e.g.,infected tissue. These CNs subsequently report their local decisions to a FCover a diffusion-advection blood flow channel using different types ofmolecules in the presence of inter-symbol interference, multi-sourceinterference, and counting errors. Due to limited computational capability atthe FC, OR and AND logic based fusion rules are employed to make the finaldecision after obtaining each local decision based on the optimal likelihoodratio test. For the aforementioned system, probabilities of detection and falsealarm at the FC are derived for OR and AND fusion rules. Finally, simulationresults are presented to validate the derived analytical results, which provideimportant insights.

Abnormality Detection inside Blood Vessels with Mobile Nanomachines