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Measurement-Based Modeling of Large-Scale and Time-Varying Small-Scale Fading for LoRa in Indoor Multi-Floor

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This study characterizes Long Range (LoRa) radio propagation in multi-floor smart buildings. Results show LoRa offers reliable wireless sensor coverage, providing key data for indoor IoT infrastructure deployment.

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Area of Science:

  • Electrical Engineering
  • Wireless Communications
  • Internet of Things (IoT)

Background:

  • Smart buildings require robust wireless networks for IoT deployment.
  • Long Range (LoRa) technology offers low-power, long-range communication suitable for IoT.
  • Indoor radio propagation in multi-floor structures presents significant challenges for wireless signals.

Purpose of the Study:

  • To empirically characterize LoRa signal propagation at 433 MHz in a four-story university building.
  • To model large-scale and small-scale fading effects impacting LoRa performance.
  • To provide guidelines for planning and deploying indoor IoT infrastructure in multi-floor environments.

Main Methods:

  • Conducted extensive Received Signal Strength Indicator (RSSI) and Signal-to-Noise Ratio (SNR) measurements.
  • Developed a log-distance path loss model incorporating a Floor Attenuation Factor (FAF).
  • Characterized small-scale fading using a Markov-modulated process and modeled RSSI-SNR relationship with a logistic function.

Main Results:

  • Derived path loss exponent (n=2.53), FAF (5.52 dB/floor), and shadowing standard deviation (σ=6.93 dB).
  • Successfully modeled time-varying small-scale fading and identified a non-linear RSSI-SNR relationship.
  • Determined transceiver dynamic range (~30 dB) and minimum measurable RSSI (-125 dBm).

Conclusions:

  • The proposed models accurately describe LoRa propagation in complex indoor environments.
  • LoRa technology is validated as capable of providing reliable, building-wide wireless sensor coverage.
  • The findings offer essential guidelines for effective indoor IoT infrastructure planning and deployment.