3 research outputs found
Energy Efficient Event Localization and Classification for Nano IoT
Advancements in nanotechnology promises new capabilities for Internet of
Things (IoT) to monitor extremely fine-grained events by deploying sensors as
small as a few hundred nanometers. Researchers predict that such tiny sensors
can transmit wireless data using graphene-based nano-antenna radiating in the
terahertz band (0.1-10 THz). Powering such wireless communications with
nanoscale energy supply, however, is a major challenge to overcome. In this
paper, we propose an energy efficient event monitoring framework for nano IoT
that enables nanosensors to update a remote base station about the location and
type of the detected event using only a single short pulse. Nanosensors encode
different events using different center frequencies with non overlapping half
power bandwidth over the entire terahertz band. Using uniform linear array
(ULA) antenna, the base station localizes the events by estimating the
direction of arrival of the pulse and classifies them from the center frequency
estimated by spectral centroid of the received signal. Simulation results
confirm that, from a distance of 1 meter, a 6th derivative Gaussian pulse
consuming only 1 atto Joule can achieve localization and classification
accuracies of 1.58 degree and 98.8%, respectively.Comment: 6 pages, 18 Figures, accepted for publication in IEEE GLOBECOM
Conference 201