2026-10-14T15:58:25Z https://www.scidb.cn/oai

10.57760/sciencedb.40202 2026-06-16T16:15:42Z

2026-06-16 EAFM-SEI/SEV-RF Dataset: Envelope-guided Adaptive Feature Modulation for Radio Frequency Fingerprinting across Rician Fading Channels with Hardware Impairments doi:10.57760/sciencedb.40202 en EAFM-RF-CC Dataset (Envelope-guided Adaptive Feature Modulation Radio Frequency Fingerprinting Dataset for Cross-Channel Scenarios) is a comprehensive synthetic dataset specifically designed for Specific Emitter Identification (SEI) and Specific Emitter Verification (SEV) in UAV communications and IoT applications. The dataset addresses the fundamental challenge of robust device identification under varying Rician fading channel conditions with hardware impairments.1) Signal and Physical-layer/Link Geometry Parameters · QPSK symbol number (Nsymbols): 512· Samples per symbol (SPS): 4· Root-raised cosine rolloff (α): 0.3· RRC filter span (Mspan): 8· Sampling rate (Fs): 30.72 MHz· Carrier frequency (Fc): 2.4 GHz· Transmitter antenna height (hBS): 10 m· Receiver antenna height (hUT): 100 m· Two-dimensional distance (d2D): 500 m· Three-dimensional distance (d3D): 508.0 m2) Channel Model Parameters: Rician Fading and K-factor · Rician K-factor values (training coverage): {−2, 2, 6, 10} dB3) Multipath Delays and Power Configuration (Rician multipath channel)Using the Rician fading multipath configuration (paper-provided taps):· Path delays (ns): {0, 80, 200, 570, 1090, 1730, 2510} ns· Corresponding power levels (dB): {0.0, −2.7, −3.0, −4.6, −7.5, −10.6, −13.1} dB4) Transmitter Hardware Parameters Hardware distortion parameters for multiple devices (used to model I/Q imbalance, carrier leakage, spurious/sideband components, PA nonlinearity, etc.). The fields include:· G: gain imbalance parameter· ζ · π/180: phase offset (in radians derived from degrees)· aST: spurious tone/sideband amplitude· fST (MHz): spurious tone frequency offset· ξm × 10−3: carrier leakage coefficient scaling· [b1, b2, b3]: Taylor-series coefficients for the PA (for PA nonlinearity model order (L=3))Device parameters (Dev1–Dev5):· Dev1: G = 0.9998, ζ·π/180 = −0.0180, a^ST = 0.0082, f^ST = 0.129 MHz, ξ_m × 10⁻³ = 1.3 + 8.2j, [b₁, b₂, b₃] = [1.00, 0.50, 0.30]· Dev2: G = 1.0056, ζ·π/180 = 0.0175, a^ST = 0.0075, f^ST = 0.132 MHz, ξ_m × 10⁻³ = 1.5 + 7.2j, [b₁, b₂, b₃] = [1.00, 0.08, 0.60]· Dev3: G = 1.0102, ζ·π/180 = 0.0120, a^ST = 0.0070, f^ST = 0.123 MHz, ξ_m × 10⁻³ = 1.1 + 6.8j, [b₁, b₂, b₃] = [1.00, 0.01, 0.01]· Dev4: G = 0.9992, ζ·π/180 = 0.0030, a^ST = 0.0087, f^ST = 0.135 MHz, ξ_m × 10⁻³ = 1.7 + 9.0j, [b₁, b₂, b₃] = [1.00, 0.01, 0.40]· Dev5 (spoofing attack device, used for testing only): G = 0.9500, ζ·π/180 = 0.0300, a^ST = 0.0195, f^ST = 0.165 MHz, ξ_m × 10⁻³ = 3.2 + 13.5j, [b₁, b₂, b₃] = [1.00, 0.95, 0.80]Note: In the SEV scenario, Dev5 is used as the unknown spoofing attack device, while Dev1–Dev4 are legitimate devices. Specific Emitter Identification (SEI); Radio Frequency Fingerprinting (RFF); Rician Fading Channel; Hardware Impairment Simulation Yuhao Chen PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank