Read Me for LoRaWAN ACM Dataset and Code for Simulation
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Title: Optimizing LoRaWAN Throughput in Maritime Environments Through Adaptive Coding and Modulation in Rayleigh Fading Channels

Author: Martine Lyimo et al.

Institution: NM-AIST, Arusha, Tanzania

Description:

Datasets and sample simulation code for the results presented in the manuscript The paper studied the possibility of employing Adaptive Coding and Modulation (ACM) to enhance LoRaWAN performance in maritime under Rayleigh fading conditions.

Contents:
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1. PER_vs_SNR.csv

	PER for SF7–SF12 with SNR from -20 dB to 10 dB

2. Throughput_vs_SNR.csv

	Throughput — with SNR ranging for each SF configuration

3. ACM_Gain_vs_SF7.csv

	Throughput gain achieved by the ACM approach over a fixed SF7 configuration

4. Energy_Efficiency_vs_SNR.csv

	Energy per bit (in µJ/bit) for all configurations and ACM strategy vs SNR.

5. Spectral_Efficiency_vs_SNR. csv

	Bits/s/Hz spectral efficiency in each configuration and ACM strategy.

6. ACM_Algorithm.m

	The MATLAB code of the SNR-based switching algorithm for ACM.

7. config_levels.csv

The six PHY configurations levels are used in simulations below download the file.

Each variant is based on a specific combination of:

Spreading Factor (SF),

Bandwidth (BW in kHz),

Coding Rate (CR),

Size of Payload (Defined is 100B constant)

and its Time on Air (ToA in ms).

Values of those parameters were taken from standard LoRa ToA expressions found in Semtech doc 1, and referred to in the article.

License:
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The data and code are licensed under CC-BY 4.0 License Please site the original article where this dataset is from.

Contact:
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Martine Lyimo

Email: martine.lyimo@nm-aist.ac.tz