Iraq RF Spectrum Dataset: Real-World Multi-Band Raw IQ Measurements from Baghdad – Part 2

Part 2 of the Iraq RF Spectrum Dataset: Real-World Multi-Band Raw IQ Measurements from Baghdad, Iraq. This record contains raw IQ recordings from Day3 and Day4 of a real-world multi-band RF measurement campaign conducted in Baghdad, Iraq. Measurements were acquired using an RTL-SDR V3 receiver with GNU Radio and an Osmocom Source at a sampling rate of 2.048 MS/s. Fixed receiver settings were used, including RF gain = 40 dB, IF gain = 30 dB, and BB gain = 20 dB. Part 2 includes outdoor and indoor measurements collected under non-elevated conditions. Day3 was recorded during a night session spanning 5–6 June 2026 under outdoor non-elevated conditions, while Day4 was recorded on 7 June 2026 under indoor non-elevated conditions. The measurements cover FM, VHF, UHF, GSM900, ISM 433.92 MHz, ISM/LoRa 868 MHz, ISM/LoRa 915 MHz, and ADS-B 1090 MHz bands. The accompanying Iraq_RF_Master_Metadata_FINAL.csv provides harmonized per-recording metadata for the complete Day1–Day20 dataset (295 recordings), including recording dates, estimated timing information, duration, environment, elevation context, center frequency, receiver settings, and timing provenance. Original raw IQ filenames are preserved; the master metadata should be used to interpret documented filename inconsistencies. Where preserved file timestamps were available, recording start times were estimated from file modification times and recording durations. These times are therefore documented as estimated rather than directly measured acquisition timestamps. No external RF calibration instrument or calibrated reference signal was used during the measurement campaign. Post-acquisition quality control was performed on the stored complex IQ samples and should not be interpreted as RF calibration or absolute calibrated power measurement. The complete dataset is distributed across multiple Zenodo records because of the large size of the raw IQ recordings. The dataset is intended to support research in spectrum sensing, spectrum occupancy analysis, cognitive radio, dynamic spectrum access, software-defined radio, wireless communications, RF signal analysis, and machine/deep learning for RF spectrum analysis.