ToA estimation

This set of datasets is designed for the validation and testing of Time of Arrival (TOA) estimation methods in LoRa-based Low-Power Wide-Area Networks (LPWANs). The datasets cover SNR values of -10, 0, 10, and 20 dB, representing different noise levels that impact signal detection. Each dataset provides a structured representation of signal behavior over time in an LPWAN with a star topology, capturing realistic transmission conditions. This allows for a thorough evaluation of TOA estimation models across varying signal conditions, ensuring robustness and adaptability. The datasets support benchmarking, model validation, and comparative testing, enabling researchers and engineers to refine TOA detection techniques for improved accuracy and efficiency in resource-constrained IoT networks. By incorporating multiple SNR scenarios, this dataset helps in assessing model performance in both low and high signal quality environments, making it a valuable resource for the development of advanced ML-based TOA estimation methods.