Enhancing LoRaWAN Communication for Mobile Nodes with Techniques for Predicting Signal Strength

Slavkoski, Hristijan; Trendov, Simeon; Kalendar, Eduard

doi:10.25673/121721.2

Proceedings of International Conference on Applied Innovation in IT · 2025/08/29 · Vol. 13 · Issue 4 · pp. 63–69

Enhancing LoRaWAN Communication for Mobile Nodes with Techniques for Predicting Signal Strength

Hristijan Slavkoski, Simeon Trendov, Eduard Siemens and Marija Kalendar

📄 Download PDF DOI: 10.25673/121721.2

Abstract

Mobile LoRaWAN links suffer from rapid RSSI/SNR fluctuations due to motion, obstacles, and interference, degrading reliability and wasting energy. This work evaluates lightweight signal-strength prediction combined with adaptive control on resource-constrained hardware. A Kalman filter is applied to smooth per-packet RSSI/SNR and to trigger parameter updates to transmit power, spreading factor, and coding rate only when persistent degradation is detected. The approach is implemented on an Arduino sender and a Raspberry Pi receiver and tested in urban, rural, park, and free-field environments. Results show variance reductions in RSSI of about one third and SNR of about one fifth, translating into energy savings of 15â€“27% without loss of reliability. Compared with a reactive baseline and the principles of LoRaWAN ADR, the method responds faster to recovery and avoids prolonged high-power operation in mobility. The findings indicate that simple predictive filtering is an effective building block for robust and energy-efficient mobile LoRaWAN systems.

Keywords

Adaptive Control Adaptive Data Rate (ADR) Coding Rate (CR) Energy Efficiency Internet of Things (IoT) Kalman Filter LoRaWAN Mobile Communication Received Signal Strength Indicator (RSSI) Signal-to-Noise Ratio (SNR) Signal Strength Prediction Spreading Factor (SF) Transmit Power (TP).

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