Simulation data for MuCode-LoRa: Coordinated Scheduling and Conditional Network Coding for Reliable LoRaWAN Uplinks

This dataset contains simulation results for the manuscript "MuCode-LoRa: Coordinated Scheduling and Conditional Network Coding for Reliable LoRaWAN Uplinks." The data were generated using ns-3.45 simulations with the public LoRaWAN module and a custom MuCode-LoRa extension. The dataset includes two CSV files: 1. Full_Campaign_individual_results.csv: 1,200 individual simulation runs with run-level performance metrics. 2. Full_Campaign_summary_with_ci.csv: aggregated statistics with 95% confidence intervals for 40 configurations (5 approaches x 2 scenarios x 4 traffic loads). Approaches evaluated in this version are: - ADR - Uncoordinated RLNC - MuCode-Coord (stored as MuCode_NoCode in the CSV files) - NCC-LoRa - MuCode-LoRa This version supersedes the earlier Zenodo deposit that referenced CAST-SF. CAST-SF campaign rows are not included in this version and are not reused. Scenarios: - Urban: 300 devices, 3 gateways - Rural: 120 devices, 2 gateways Traffic loads: - Light: 600 s inter-arrival - Medium: 300 s - Heavy: 60 s - Stress: 12 s Each configuration includes 30 independent runs, for a total of 1,200 runs. Metrics include packet delivery ratio (PDR), average and tail latency, duty-cycle utilization, gateway-load imbalance, airtime, retransmissions, coding efficiency, coding opportunities, coding enablement, and related run-level statistics. This dataset supports the experimental evaluation in the associated IEEE Internet of Things Journal submission.