Optimal Haptic Communications over Nanonetworks for E-Health Systems

Tactile Internet-based nanonetwork is an emerging
field that promises a new range of e-health applications, in which
human operators can efficiently operate and control devices
at the nanoscale for remote-patient treatment. Haptic feedback
is inevitable for establishing a link between the operator and
unknown in-body environment. However, haptic communications
over the terahertz band may incur significant path loss due to
molecular absorption. In this paper, we propose an optimization
framework for haptic communications over nanonetworks, in
which in-body nano-devices transmit haptic information to an
operator via the terahertz band. By considering the properties
of the terahertz band, we employ Brownian motion to describe
the mobility of the nano-devices and develop a time-variant
terahertz channel model. Furthermore, based on the developed
channel model, we construct a stochastic optimization problem
for improving haptic communications under the constraints of
system stability, energy consumption, and latency. To solve the
formulated non-convex stochastic problem, an improved timevarying
particle swarm optimization algorithm is presented,
which can deal with the constraints of the problem efficiently
by reducing the convergence time significantly. The simulation
results validate the theoretical analysis of the proposed system.