Toward Standardized Performance Evaluation of Flow-guided Nanoscale Localization
Nanoscale devices with Terahertz (THz) communication capabilities are envisioned to be deployed within human bloodstreams. Such devices will enable fine-grained sensing-based applications for detecting early indications (i.e., biomarkers) of various health conditions, as well as actuation-based ones...
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Zusammenfassung: | Nanoscale devices with Terahertz (THz) communication capabilities are
envisioned to be deployed within human bloodstreams. Such devices will enable
fine-grained sensing-based applications for detecting early indications (i.e.,
biomarkers) of various health conditions, as well as actuation-based ones such
as targeted drug delivery. Associating the locations of such events with the
events themselves would provide an additional utility for precision diagnostics
and treatment. This vision yielded a new class of in-body localization coined
under the term "flow-guided nanoscale localization". Such localization can be
piggybacked on THz communication for detecting body regions in which biological
events were observed based on the duration of one circulation of a nanodevice
in the bloodstream. From a decades-long research on objective benchmarking of
"traditional" indoor localization, as well as its eventual standardization
(e.g., ISO/IEC 18305:2016), we know that in early stages the reported
performance results were often incomplete (e.g., targeting a subset of relevant
performance metrics), carrying out benchmarking experiments in different
evaluation environments and scenarios, and utilizing inconsistent performance
indicators. To avoid such a "lock-in" in flow-guided localization, in this
paper we propose a workflow for standardized performance evaluation of such
localization. The workflow is implemented in the form of an open-source
simulation framework that is able to jointly account for the mobility of the
nanodevices, in-body THz communication between with on-body anchors, and
energy-related and other technological constraints (e.g., pulse-based
modulation) at the nanodevice level. Accounting for these constraints, the
framework is able to generate the raw data that can be streamlined into
different flow-guided localization solutions for generating standardized
performance benchmarks. |
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DOI: | 10.48550/arxiv.2303.07804 |