Uplink Performance Analysis of Cellular-Based Energy Harvesting IoT Networks

Abstract

In recent years, energy-harvesting (EH) technology is rapidly developing and served as a promising solution to enable the energy sustainability of Internet of things (IoT) networks. In this work, we study an uplink (UL) cellular-based energy harvesting IoT network where a joint energy supply strategy is employed to ensure energy continuity. To characterize both the spatial randomness of IoT devices, and spatio-temporal random arrival of traffic and harvested energy, we develop a spatio-temporal analytical framework to evaluate the IoT network performance by leveraging stochastic geometry and queueing theory. We first derive the traffic queue void probability of a random IoT device, and obtain the service rate and mean packet throughput (MPT). Then we derive the availability of the rechargeable battery and the energy efficiency (EE) of an IoT device. By studying the effect of key parameters on the network performance, we observe that the growth in UL traffic arrival rate leads to a reduction in service rate, MPT, and EE. A higher successful charging probability always enhances EE.