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Link Quality Modeling for LoRa Networks in Orchards

Authors:

Tingruixiang Su,

Wan DuAuthors Info & Claims

IPSN '23: Proceedings of the 22nd International Conference on Information Processing in Sensor Networks

Pages 27 - 39

https://doi.org/10.1145/3583120.3586969

Published: 09 May 2023 Publication History

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Abstract

LoRa networks have been deployed in many orchards for environmental monitoring and crop management. An accurate propagation model is essential for efficiently deploying a LoRa network in orchards, e.g., determining gateway coverage and sensor placement. Although some propagation models have been studied for LoRa networks, they are not suitable for orchard environments, because they do not consider the shadowing effect on wireless propagation caused by the ground and tree canopies. This paper presents FLog, a propagation model for LoRa signals in orchard environments. FLog leverages a unique feature of orchards, i.e., all trees have similar shapes and are planted regularly in space. We develop a 3D model of the orchards. Once we have the location of a sensor and a gateway, we know the mediums that the wireless signal traverse. Based on this knowledge, we generate the First Fresnel Zone (FFZ) between the sender and the receiver. The intrinsic path loss exponents (PLE) of all mediums can be combined into a classic Log-Normal Shadowing model in the FFZ. Extensive experiments in almond orchards show that FLog reduces the link quality estimation error by 42.7% and improves gateway coverage estimation accuracy by 70.3%, compared with a widely-used propagation model.

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Cited By

Pandey SKumari PGupta HRai DRao S(2024)A Site-Specific LoRaWAN Parameters Selection Approach with Multi-Loss Propagation Model2024 IFIP Networking Conference (IFIP Networking)10.23919/IFIPNetworking62109.2024.10619879(350-358)Online publication date: 3-Jun-2024
https://doi.org/10.23919/IFIPNetworking62109.2024.10619879
Yang KDu W(2024)A Low-Density Parity-Check Coding Scheme for LoRa NetworkingACM Transactions on Sensor Networks10.1145/366592820:4(1-29)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3665928
Ding XDu W(2024)Optimizing Irrigation Efficiency using Deep Reinforcement Learning in the FieldACM Transactions on Sensor Networks10.1145/366218220:4(1-34)Online publication date: 8-Jul-2024
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Index Terms

Link Quality Modeling for LoRa Networks in Orchards
1. Networks
  1. Network performance evaluation
    1. Network measurement
  2. Network properties
    1. Network range
      1. Wide area networks

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cover image ACM Conferences

IPSN '23: Proceedings of the 22nd International Conference on Information Processing in Sensor Networks

May 2023

385 pages

ISBN:9798400701184

DOI:10.1145/3583120

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 09 May 2023

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Fresno-Merced Future of Food Innovation Initiative (F3) challenge grant

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IPSN '23: The 22nd International Conference on Information Processing in Sensor Networks

May 9 - 12, 2023

TX, San Antonio, USA

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Cited By

Pandey SKumari PGupta HRai DRao S(2024)A Site-Specific LoRaWAN Parameters Selection Approach with Multi-Loss Propagation Model2024 IFIP Networking Conference (IFIP Networking)10.23919/IFIPNetworking62109.2024.10619879(350-358)Online publication date: 3-Jun-2024
https://doi.org/10.23919/IFIPNetworking62109.2024.10619879
Yang KDu W(2024)A Low-Density Parity-Check Coding Scheme for LoRa NetworkingACM Transactions on Sensor Networks10.1145/366592820:4(1-29)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3665928
Ding XDu W(2024)Optimizing Irrigation Efficiency using Deep Reinforcement Learning in the FieldACM Transactions on Sensor Networks10.1145/366218220:4(1-34)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3662182
Ding XCerpa ADu W(2024)Exploring Deep Reinforcement Learning for Holistic Smart Building ControlACM Transactions on Sensor Networks10.1145/365604320:3(1-28)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.1145/3656043
Yang KChen YDu WOkoshi TKo JLiKamWa R(2024)OrchLoc: In-Orchard Localization via a Single LoRa Gateway and Generative Diffusion Model-based FingerprintingProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661876(304-317)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661876
Li CRen YTong SSiam SZhang MWang JLiu YCao ZOkoshi TKo JLiKamWa R(2024)ChirpTransformer: Versatile LoRa Encoding for Low-power Wide-area IoTProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661861(479-491)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661861
Chen YYang KAn ZHolder BPaloutzian LBali KDu WBaeza-Yates RBonchi F(2024)MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer RechargeProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671533(4862-4872)Online publication date: 25-Aug-2024
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Ren YSun WDu JZeng HDong YZhang MChen SLiu YLi TCao ZGanesan DLane NShi W(2024)Demeter: Reliable Cross-soil LPWAN with Low-cost Signal Polarization AlignmentProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3649358(230-245)Online publication date: 29-May-2024
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Yang KLiu MDu W(2024)RALoRa: Rateless-Enabled Link Adaptation for LoRa NetworkingIEEE/ACM Transactions on Networking10.1109/TNET.2024.339234232:4(3392-3407)Online publication date: Aug-2024
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Lin JXiong RXu ZTian WChen CDong XLuo J(2024)Multi-Node Concurrent Localization in LoRa Networks: Optimizing Accuracy and EfficiencyIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621435(1091-1100)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621435

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