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Previous work has demonstrated the viability of using RF-DNA fingerprinting to provide serial number discrimination of IEEE 802.11a WiFi devices as a means to augment conventional bit-level security. This was done using RF-DNA extracted from signal regions containing standard pre-defined responses (preamble, midamble, etc.). Using these responses, proof-of-concept demonstrations with RF-DNA fingerprinting have shown some effectiveness for providing serial number discrimination. The discrimination challenge increases considerably when pre-defined signal responses are not present. This challenge is addressed here using experimentally collected IEEE 802.16e WiMAX signals from Alvarion BreezeMAX Mobile Subscriber (MS) devices. Relative to previous Time Domain (TD) and Spectral Domain (SD) fingerprint features, joint time-frequency Gabor (GT) and Gabor-Wigner (GWT) Transform features are considered here as a means to extract greater device discriminating information. For comparison, RF-DNA is extracted from TD, SD, GT, and GWT responses and MDA/ML feature extraction and classification performed. Preliminary assessment shows that Gabor-based RF-DNA fingerprinting is much more effective than either TD or SD methods. GT RF-DNA fingerprinting achieves individual WiMAX MS device classification of 98.5% or better for SNR ≥ -3 dB.