# Performance Analysis of Uplink Cellular IoT Using Different Deployments   of Data Aggregators

**Authors:** Ghaith Hattab, Danijela Cabric

arXiv: 1812.01751 · 2018-12-06

## TL;DR

This paper analyzes uplink cellular IoT performance with various aggregator deployment strategies, deriving key metrics like power consumption and coverage, and shows aerial aggregators enhance device lifetime and coverage.

## Contribution

It provides closed-form expressions for IoT-specific performance metrics under different aggregator deployment strategies using stochastic geometry.

## Key findings

- Aerial aggregators significantly extend device lifetime.
- Optimal placement improves coverage for clustered devices.
- Simulation validates theoretical expressions.

## Abstract

Data aggregation is an effective solution to enable cellular support of Internet-of-things (IoT) communications. Indeed, it helps alleviate channel congestion, reduce the communication range, and extend battery-lifetime. In this paper, we use stochastic geometry to analyze the performance of uplink cellular IoT using different deployment strategies of aggregators, including terrestrial and aerial ones, e.g., drones or unmanned aerial vehicles. We focus on IoT-specific performance metrics, that are typically used by 3GPP. Specifically, we derive closed-form expressions of the average transmit power consumption, which is key to determine the lifetime of IoT devices, as well as the maximum coupling loss, which is essential to determine the maximum coverage the cellular system can support. Simulation results are presented to validate the derived theoretical expressions. It is shown that aerial aggregators can significantly extend the device lifetime and provide superior coverage compared to other deployment strategies. In addition, random deployment performs well when aggregators are densely deployed, whereas optimizing the location of a single terrestrial aggregator is beneficial when devices are more clustered.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1812.01751/full.md

## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/1812.01751/full.md

## References

16 references — full list in the complete paper: https://tomesphere.com/paper/1812.01751/full.md

---
Source: https://tomesphere.com/paper/1812.01751