On the Bound of Energy Consumption in Cellular IoT Networks

TL;DR

This paper develops an analytical framework to estimate the lower bound of energy consumption in cellular IoT devices, considering interference and network geometry, validated through measurements and simulations.

Contribution

It introduces a novel analytic model for IoT energy consumption based on Shannon capacity and stochastic geometry, incorporating interference effects.

Findings

Current network performance is bounded between two geometric models.

The proposed framework aligns well with experimental and simulation data.

Interference impacts energy consumption estimates significantly.

Abstract

Billions of sensors are expected to be connected to the Internet through the emerging Internet of Things (IoT) technologies. Many of these sensors will primarily be connected using wireless technologies powered using batteries as their sole energy source which makes it paramount to optimize their energy consumption. In this paper, we provide an analytic framework of the energy-consumption profile and its lower bound for an IoT end device formulated based on Shannon capacity. We extend the study to model the average energy-consumption performance based on the random geometric distribution of IoT gateways by utilizing tools from stochastic geometry and real measurements of interference in the ISM-band. Experimental data, interference measurements and Monte-Carlo simulations are presented to validate the plausibility of the proposed analytic framework, where results demonstrate that the current network infrastructures performance is bounded between two extreme geometric models. This study considers interference seen by a gateway regardless of its source.