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K-Means Spreading Factor Allocation for Large-Scale LoRa Networks.

Muhammad Asad Ullah1, Junnaid Iqbal2, Arliones Hoeller3,4,5

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This summary is machine-generated.

This study introduces a K-means clustering algorithm for Long-Range (LoRa) spreading factor allocation in Internet of Things (IoT) networks. The method enhances network coverage probability and reduces performance disparities among devices.

Keywords:
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Area of Science:

  • Wireless Communication
  • Internet of Things (IoT)
  • Network Optimization

Background:

  • Low-Power Wide-Area Networks (LPWANs) are crucial for IoT due to low power and long-range capabilities.
  • Long-Range (LoRa) is a leading LPWAN technology with rapid adoption.
  • Efficient spreading factor (SF) allocation is vital for optimizing LoRaWAN performance.

Purpose of the Study:

  • To propose a novel K-means clustering algorithm for flexible and application-dependent SF allocation in LoRaWAN.
  • To evaluate the impact of SF allocation on network performance, specifically coverage probability and transmission reliability.
  • To improve fairness and reduce performance variations between network nodes.

Main Methods:

  • Development of a K-means clustering algorithm for SF allocation.
  • Modeling a large-scale, unconfirmed-mode, class-A LoRaWAN without retransmissions.
  • Performance assessment using outage probabilities, considering gateway distance and node density per SF.

Main Results:

  • The proposed SF allocation algorithm improves average network coverage probability by up to 5% compared to baseline models.
  • Significant reduction in performance difference between the best- and worst-case nodes, enhancing network fairness.
  • Demonstrated enhancement of worst-case performance by up to 1.53 times in specific deployment scenarios.

Conclusions:

  • The K-means based SF allocation algorithm offers a flexible approach for optimizing LoRaWAN performance.
  • The method effectively balances network load across SFs, leading to improved reliability and fairness.
  • This approach is valuable for designing efficient and robust IoT networks utilizing LoRa technology.