SLoRa+: A Systematic Framework for Enhanced Interference Resilience in LoRaWAN

LoRa technology has become critical in numerous IoT applications, offering long-range connections with low energy consumption. However, their low-power nature makes them vulnerable to cross-technology interference (CTI) from other wireless technologies sharing the same unlicensed frequency bands. Existing solutions address this issue through signal analysis and coding techniques. Despite these efforts, the research on CTI mitigation needs to go one step further - to design a systematic framework for enhanced interference resilience. This article proposes SLoRa+, a systematic framework that integrates symbol recovery with soft decoding to achieve synergic interference resilience for LoRa. SLoRa+’s symbol recovery employs a two-stage analysis to recover corrupted LoRa symbols at a low cost. It also estimates the confidence of the recovered symbols by considering the characteristics of both LoRa and CTI. This confidence information is then utilized in soft decoding to improve error correction capabilities. Supported by theoretical analysis and real testbed evaluations, including commercial LoRa nodes and USRP B210, our experiments under different settings, i.e., various CTI sources and frequency bands, demonstrate SLoRa+’s effectiveness. Compared with state-of-the-art techniques, SLoRa+ enhances CTI protection capability by 1.6× with only 1% of the computation cost.

Authors

Institutions

Publication Details

Journal
ACM Transactions on Sensor Networks
Published
2025-09-12
DOI
https://doi.org/10.1145/3767338
Citations
1
Primary Topic
IoT Networks and Protocols
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SLoRa+: A Systematic Framework for Enhanced Interference Resilience in LoRaWAN

Zhimeng Yin, Qiling Xu, Binbin Xie, Pengpeng Chen et al.
1 citations
ACM Transactions on Sensor Networks
IoT Networks and Protocols
0.73
article

SLoRa+: A Systematic Framework for Enhanced Interference Resilience in LoRaWAN

Zhimeng Yin, Qiling Xu, Binbin Xie, Pengpeng Chen, Danei Gong, Shuai Wang, Kai Sun
article en
1 citations

Abstract

LoRa technology has become critical in numerous IoT applications, offering long-range connections with low energy consumption. However, their low-power nature makes them vulnerable to cross-technology interference (CTI) from other wireless technologies sharing the same unlicensed frequency bands. Existing solutions address this issue through signal analysis and coding techniques. Despite these efforts, the research on CTI mitigation needs to go one step further - to design a systematic framework for enhanced interference resilience. This article proposes SLoRa+, a systematic framework that integrates symbol recovery with soft decoding to achieve synergic interference resilience for LoRa. SLoRa+’s symbol recovery employs a two-stage analysis to recover corrupted LoRa symbols at a low cost. It also estimates the confidence of the recovered symbols by considering the characteristics of both LoRa and CTI. This confidence information is then utilized in soft decoding to improve error correction capabilities. Supported by theoretical analysis and real testbed evaluations, including commercial LoRa nodes and USRP B210, our experiments under different settings, i.e., various CTI sources and frequency bands, demonstrate SLoRa+’s effectiveness. Compared with state-of-the-art techniques, SLoRa+ enhances CTI protection capability by 1.6× with only 1% of the computation cost.

ACM Transactions on Sensor NetworksVol. 21(6)
City University of Hong Kong (HK), The University of Texas at Arlington (US), China University of Mining and Technology (CN), Southeast University (CN)
Openalex Percentile: Top 23%
IoT Networks and Protocols
0.73
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.

SLoRa+: A Systematic Framework for Enhanced Interference Resilience in LoRaWAN — Zhimeng Yin, Qiling Xu, et al. · ACM Transactions on Sensor Networks (2025) | TGRS Research Map | TGRS