Analysis of Age-Energy Trade-off in IoT Networks Using Stochastic Geometry

TL;DR

This paper analyzes the energy and data success trade-offs in IoT networks with energy harvesting, proposing a slot division scheme and deriving bounds for success probability and age-of-information, guiding optimal parameter choices.

Contribution

It introduces a novel slot division scheme for IoT energy harvesting networks and derives bounds for success probability and age-of-information, aiding optimal network design.

Findings

Optimal slot partitioning balances energy harvesting and data transmission.

Both queuing disciplines can share the same optimal partitioning factor.

Guidelines for optimal parameters under different transmit powers and deployment areas.

Abstract

We study an internet of things (IoT) network where devices harvest energy from transmitter power. IoT devices use this harvested energy to operate and decode data packets. We propose a slot division scheme based on a parameter $\xi$, where the first phase is for energy harvesting (EH) and the second phase is for data transmission. We define the joint success probability (JSP) metric as the probability of the event that both the harvested energy and the received signal-to-interference ratio (SIR) exceed their respective thresholds. We provide lower and upper bounds of (JSP), as obtaining an exact JSP expression is challenging. Then, the peak age-of-information (PAoI) of data packets is determined using this framework. Higher slot intervals for EH reduce data transmission time, requiring higher link rates. In contrast, a lower EH slot interval will leave IoT devices without enough energy to decode the packets. We demonstrate that both non-preemptive and preemptive queuing disciplines may have the same optimal slot partitioning factor for maximizing the JSP and minimizing the PAoI. For different transmit powers and deployment areas, we recommend the optimal slot partitioning factor for the above two metrics under both queuing disciplines.