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Signal Attenuation in LoRaWAN: A Survey of Modeling Techniques and Experimental Evaluation

https://doi.org/10.2139/ssrn.5885758
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inferredcites →https://doi.org/10.1016/j.iot.2023.100964openalex-snapshot
A 3D simulation framework with ray-tracing propagation for LoRaWAN communication
inferredcites →https://doi.org/10.1016/j.iot.2023.100974openalex-snapshot
Dynamic transmission policy for enhancing LoRa network performance: A deep reinforcement learning approach
inferredcites →https://doi.org/10.1016/j.simpat.2010.10.001openalex-snapshot
Modelling and simulation of Rayleigh fading, path loss, and shadowing fading for wireless mobile networks
inferredcites →https://doi.org/10.1049/iet-com.2008.0297openalex-snapshot
Compact Rayleigh and Rician fading simulator based on random walk processes
inferredcites →https://doi.org/10.1109/35.601747openalex-snapshot
Rayleigh fading channels in mobile digital communication systems .I. Characterization
inferredcites →https://doi.org/10.1109/5.282243openalex-snapshot
Spread-spectrum technology for commercial applications
inferredcites →https://doi.org/10.1109/access.2020.3016042openalex-snapshot
Accuracy Assessment and Cross-Validation of LPWAN Propagation Models in Urban Scenarios
inferredcites →https://doi.org/10.1109/access.2022.3166895openalex-snapshot
Log Distance Path Loss Model: Application and Improvement for Sub 5 GHz Rural Fixed Wireless Networks
inferredcites →https://doi.org/10.1109/ap-s/inc-usnc-ursi52054.2024.10686629openalex-snapshot
Wave-Controlled RIS as Reconfigurable Reflective Lens for Focusing in the Fresnel Zone
inferredcites →https://doi.org/10.1109/comst.2023.3274934openalex-snapshot
A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges
inferredcites →https://doi.org/10.1109/jiot.2019.2906838openalex-snapshot
LoRaWAN Network: Radio Propagation Models and Performance Evaluation in Various Environments in Lebanon
inferredcites →https://doi.org/10.1109/jiot.2019.2946487openalex-snapshot
A Thorough Study of LoRaWAN Performance Under Different Parameter Settings
inferredcites →https://doi.org/10.1109/jiot.2019.2953804openalex-snapshot
Characterization of LoRa Point-to-Point Path Loss: Measurement Campaigns and Modeling Considering Censored Data
inferredcites →https://doi.org/10.1109/jiot.2019.2962976openalex-snapshot
On the Use of LoRaWAN in Smart Cities: A Study With Blocking Interference
inferredcites →https://doi.org/10.1109/jiot.2020.3017044openalex-snapshot
LoRa System for Search and Rescue: Path-Loss Models and Procedures in Mountain Scenarios
inferredcites →https://doi.org/10.1109/jiot.2022.3191639openalex-snapshot
Large-Scale Modeling and Analysis of Uplink and Downlink Channels for LoRa Technology in Suburban Environments
inferredcites →https://doi.org/10.1109/jiot.2023.3239827openalex-snapshot
Machine-Learning-Based Combined Path Loss and Shadowing Model in LoRaWAN for Energy Efficiency Enhancement
inferredcites →https://doi.org/10.1109/jsen.2022.3212319openalex-snapshot
LoRaWAN: Lost for Localization?
inferredcites →https://doi.org/10.1109/map.2016.2630035openalex-snapshot
Path-Loss Modeling for Wireless Sensor Networks: A review of models and comparative evaluations
inferredcites →https://doi.org/10.1109/ojcoms.2021.3122286openalex-snapshot
Path Loss Prediction Model Development in a Mountainous Forest Environment
inferredcites →https://doi.org/10.1109/tcomm.2003.813259openalex-snapshot
Simulation models with correct statistical properties for rayleigh fading channels
inferredcites →https://doi.org/10.1109/tii.2020.3044942openalex-snapshot
Performance Analysis of LoRaWAN in Industrial Scenarios
inferredcites →https://doi.org/10.1109/tvt.2004.841555openalex-snapshot
Efficient Nakagami- $m$ Fading Channel Simulation
inferredcites →https://doi.org/10.1109/ucom62433.2024.10695834openalex-snapshot
Path Loss Prediction Based on Deep Neural Networks Considering Fresnel Zone
inferredcites →https://doi.org/10.1109/wf-iot.2019.8767245openalex-snapshot
Comparative Performance Analysis of Empirical Propagation Models for LoRaWAN 868MHz in an Urban Scenario
inferredcites →https://doi.org/10.1145/3711953openalex-snapshot
A Comprehensive Survey of Data-Driven Solutions for LoRaWAN: Challenges and Future Directions
inferredcites →https://doi.org/10.3390/bdcc1010007openalex-snapshot
A Neural Network Propagation Model for LoRaWAN and Critical Analysis with Real-World Measurements
inferredcites →https://doi.org/10.3390/s20185044openalex-snapshot
A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
inferredcites →https://doi.org/10.3390/s22145397openalex-snapshot
A Multiwall Path-Loss Prediction Model Using 433 MHz LoRa-WAN Frequency to Characterize Foliage’s Influence in a Malaysian Palm Oil Plantation Environment
inferredcites →https://doi.org/10.3390/s24102991openalex-snapshot
A Deep Learning Approach for Accurate Path Loss Prediction in LoRaWAN Livestock Monitoring
inferredcites →https://doi.org/10.3390/s24123877openalex-snapshot
A Critical Review of the Propagation Models Employed in LoRa Systems
inferredcites →https://doi.org/10.3991/ijim.v16i11.30095openalex-snapshot
ANN-based LoRaWAN Channel Propagation Model
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