Inter-Protocol Interference Impact of LoRaWAN on IEEE 802.11ah in a Simulation Environment

The spectral coexistence of LPWAN technologies, such as IEEE 802.11ah and LoRaWAN, in the sub-GHz band presents significant challenges for the performance of dense IoT networks. This study analyzes the impact of LoRaWAN interference on IEEE 802.11ah using an NS-3-based simulation environment. To this end, both technologies were integrated within a unified simulation framework, enabling the configuration of PHY and MAC parameters, as well as operating frequency bands consistent with real-world deployments in the US902-928 MHz ISM band and aligned with official standards. The evaluation focuses on fundamental performance metrics-throughput, total packet loss percentage (PPP), and signal-to-interference-plus-noise ratio (SINR)-under varying node densities and payload configurations. Across our sweep, moving from the lowest to the highest LoRa load (from 10 to 8000 LoRa nodes within the specified deployment radius), IEEE 802.11ah throughput decreases by up to 31%, and the packet loss percentage (PPP) increases by up to 79%. Furthermore, an SINR threshold was established as the criterion for packet loss under interference. Overall, this work provides a reproducible methodology for assessing inter-protocol coexistence in unlicensed sub-GHz bands, contributing quantitative evidence to the analysis and design of multi-protocol IoT networks in dense environments.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2025-11-13
DOI
https://doi.org/10.3390/s25226924
Primary Topic
IoT Networks and Protocols
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Inter-Protocol Interference Impact of LoRaWAN on IEEE 802.11ah in a Simulation Environment

Edgar Maya-Olalla, Fabián Cuzme-Rodríguez, Mauricio Domínguez-Limaico, Mateo Tito-Lara
Sensors
IoT Networks and Protocols
article

Inter-Protocol Interference Impact of LoRaWAN on IEEE 802.11ah in a Simulation Environment

Edgar Maya-Olalla, Fabián Cuzme-Rodríguez, Mauricio Domínguez-Limaico, Mateo Tito-Lara
article en

Abstract

The spectral coexistence of LPWAN technologies, such as IEEE 802.11ah and LoRaWAN, in the sub-GHz band presents significant challenges for the performance of dense IoT networks. This study analyzes the impact of LoRaWAN interference on IEEE 802.11ah using an NS-3-based simulation environment. To this end, both technologies were integrated within a unified simulation framework, enabling the configuration of PHY and MAC parameters, as well as operating frequency bands consistent with real-world deployments in the US902-928 MHz ISM band and aligned with official standards. The evaluation focuses on fundamental performance metrics-throughput, total packet loss percentage (PPP), and signal-to-interference-plus-noise ratio (SINR)-under varying node densities and payload configurations. Across our sweep, moving from the lowest to the highest LoRa load (from 10 to 8000 LoRa nodes within the specified deployment radius), IEEE 802.11ah throughput decreases by up to 31%, and the packet loss percentage (PPP) increases by up to 79%. Furthermore, an SINR threshold was established as the criterion for packet loss under interference. Overall, this work provides a reproducible methodology for assessing inter-protocol coexistence in unlicensed sub-GHz bands, contributing quantitative evidence to the analysis and design of multi-protocol IoT networks in dense environments.

SensorsVol. 25(22)
Universidad Técnica del Norte (EC)
Openalex Percentile: Top 66%
IoT Networks and Protocols
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.