Recycling Cellular Energy for Self-Sustainable IoT Networks: A
Spatiotemporal Study
Abstract
This paper investigates the self-sustainability of an overlay Internet
of Things (IoT) network that relies on harvesting energy from a downlink
cellular network. Using stochastic geometry and queueing theory, we
develop a spatiotemporal model to derive the steady state distribution
of the number of packets in the buffers and energy levels in the
batteries of IoT devices given that the IoT and cellular communications
are allocated disjoint spectrum. Particularly, each IoT device is
modelled via a two-dimensional discrete-time Markov Chain (DTMC) that
jointly tracks the evolution of the data buffer and energy battery. In
this context, stochastic geometry is used to derive the energy
generation at the batteries and the packet transmission success
probability from buffers taking into account the mutual interference
from other active IoT devices. To this end, we show the Pareto-Frontiers
of the sustainability region, which define the network parameters that
ensure stable network operation and finite packet delay. Furthermore,
the spatially averaged network performance, in terms of transmission
success probability, average queueing delay, and average queue size are
investigated. For self-sustainable networks, the results quantify the
required buffer size and packet delay, which are crucial for the design
of IoT devices and time critical IoT applications.