Design and Analysis of a Wireless Nanosensor Network for Monitoring Human Lung Cells

Thanks to nanotechnology, it is now possible to fabricate sensor nodes below 100 nanometers in size. Although wireless communication at this scale has not been successfully demonstrated yet, simulations confirm that these sensor nodes would be able to communicate in the terahertz band using graphene as a transmission antenna. These developments suggest that deployment of wireless nanoscale sensor networks (WNSNs) inside human body could be a reality one day. In this paper, we design and analyse a WNSN for monitoring human lung cells. We find that respiration, i.e., the periodic inhalation and exhalation of oxygen and carbon dioxide, is the major process that influences the terahertz channel inside lung cells. The channel is characterised as a two-state channel, where it periodically switches between good and bad states. Using real human respiratory data, we find that the channel absorbs terahertz signal much faster when it is in bad state compared to good state. Our simulation experiments confirm that we could reduce transmission power of the nanosensors, and hence the electromagnetic radiation inside lungs due to deployment of WNSN, by a factor of 20 if we could schedule all communication only during good channel states. We propose two duty cycling protocols along with a simple channel estimation algorithm that enables nanosensors to achieve such scheduling.