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A Fuzzy Logic Approach for Predicting Efficient LoRa Communication

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Abstract

With the anticipated increment in connected devices for the Internet of Things (IoT) applications, ensuring low power consumption with long-range data transmission is needed. An low power wide area network (LPWAN) technology is well suited to fulfill this requirement. LoRa is known to customize its physical layer settings to achieve desired transmission range, coverage, and energy consumption. For large-scale realistic deployments, LoRa based Industrial IoT (IIoT) solution needs to offer configurable granularity and compatibility with legacy systems and processes. However, the requirement of a seam-less handoff across end-to-end (E2E) systems is usually based on dense short-range wireless systems. As IIoT applications typically experience varying environmental conditions, we consider four scenarios, namely line-of-sight (LOS), non-LOS (NLOS), obstruction, and conventional environment, to present the variation in the network efficiency (NE). This paper aims to implement the fuzzy inference system algorithm as a controller in an IIoT-based based application. The Mamdani fuzzy inference system algorithm is implemented on the gateway node that receives sensor values and computes network parameters to predict NE. The result of the FIS is then analyzed for tuning hardware settings on LoRa nodes. These settings are then propagated to the actuator nodes to set optimal tuning of the spreading factor, bandwidth, and coding rate for maximizing lifetime and optimizing data flow. We also study and ascertain that the parameters under different network conditions need to be observed to interpret the results predicted from the FIS model.

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Author notes

  1. Sakshi Gupta, Itu Snigdh and Sudip Kumar Sahana contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science and Engineering, Birla Institute of Technology Mesra, Ranchi, Jharkhand, India

    Sakshi Gupta, Itu Snigdh & Sudip Kumar Sahana

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  1. Sakshi Gupta
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  2. Itu Snigdh
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  3. Sudip Kumar Sahana
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Correspondence to Sudip Kumar Sahana.

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Gupta, S., Snigdh, I. & Sahana, S.K. A Fuzzy Logic Approach for Predicting Efficient LoRa Communication. Int. J. Fuzzy Syst. 24, 2591–2599 (2022). https://doi.org/10.1007/s40815-021-01233-4

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  • DOI: https://doi.org/10.1007/s40815-021-01233-4

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