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Adaptive Data Rate (ADR) mechanisms are essential for optimizing communication performance and energy efficiency in LoRaWAN networks. However, traditional ADR schemes often struggle to adapt reliably to dynamic channel conditions, especially when devices are mobile. To address these challenges, this work introduces the Fuzzy ADR sensitive to the Coefficient of Variation with a Dynamic Transmission Window (FADR-CVM), a fuzzy-logic-based mechanism that applies robust normalization of the Signal-to-Noise Ratio (SNR), the link’s Coefficient of Variation (CV), and the variation in the number of measured SNR values–also inferred by the fuzzy system. Based on these factors, the mechanism dynamically adjusts the number of future uplink transmissions, infers changes to the spreading factor (SF) and transmit power (TP), and thus aims to boost data-delivery reliability and improve energy efficiency. The proposed mechanism was evaluated through simulations in the NS-3 tool, considering a 100 km \(^2\) area with up to 1000 randomly distributed end devices (EDs) operating either statically or under mobility. Experimental results show that the proposed solution improves the packet delivery ratio (PDR) by up to 10% and increases energy efficiency by up to 60 bits/J. These results highlight the potential of integrating fuzzy logic with dynamic transmission adjustments as an effective strategy for enabling more robust and energy-efficient communications in LoRaWAN networks.

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ADR Based on Fuzzy Logic with Dynamic Number of Uplink Transmissions Adjustment for LoRaWAN Networks in Mobility Scenarios

  • 会议论文

  • 发表日期：

    2026年

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  • Fernando Jorge Vieira Santos,
  • Geraldo A. Sarmento Neto,
  • Thiago Allisson R. da Silva,
  • Pedro F. F. de Abreu,
  • Luis H. de O. Mendes,
  • José V. dos Reis Junior

摘要

Adaptive Data Rate (ADR) mechanisms are essential for optimizing communication performance and energy efficiency in LoRaWAN networks. However, traditional ADR schemes often struggle to adapt reliably to dynamic channel conditions, especially when devices are mobile. To address these challenges, this work introduces the Fuzzy ADR sensitive to the Coefficient of Variation with a Dynamic Transmission Window (FADR-CVM), a fuzzy-logic-based mechanism that applies robust normalization of the Signal-to-Noise Ratio (SNR), the link’s Coefficient of Variation (CV), and the variation in the number of measured SNR values–also inferred by the fuzzy system. Based on these factors, the mechanism dynamically adjusts the number of future uplink transmissions, infers changes to the spreading factor (SF) and transmit power (TP), and thus aims to boost data-delivery reliability and improve energy efficiency. The proposed mechanism was evaluated through simulations in the NS-3 tool, considering a 100 km \(^2\) area with up to 1000 randomly distributed end devices (EDs) operating either statically or under mobility. Experimental results show that the proposed solution improves the packet delivery ratio (PDR) by up to 10% and increases energy efficiency by up to 60 bits/J. These results highlight the potential of integrating fuzzy logic with dynamic transmission adjustments as an effective strategy for enabling more robust and energy-efficient communications in LoRaWAN networks.