ZigBee networks are increasingly popular for use in medical, industrial, and other applications. Traditional security techniques for ZigBee networks are based on presenting and verifying device bit-level credentials (e.g. keys). While historically effective, ZigBee networks remain vulnerable to attack by any unauthorized rogue device that can obtain and present bit-level credentials for an authorized device. This research focused on utilizing a National Instruments (NI) X310 Software-Defined Radio (SDR) hosting an on-board Field Programmable Gate Array (FPGA). The demonstrations included device discrimination assessments using like-model ZigBee AVR RZUSBstick devices and included generating RF fingerprints in real-time, as an extension to AFIT\u27s RF-DNA fingerprinting work. The goal was to develop a fingerprinting process that was both 1) effective at discriminating between like-model ZigBee devices and 2) efficient for implementation in FPGA hardware. As designed and implemented, the full-dimensional FPGA fingerprint generator only utilized approximately 7% of the X310 Kintex-7 FPGA resources. The full-dimensional fingerprinting performance of using only 7% of FPGA resources demonstrates the feasibility for real-time RF-DNA fingerprint generation and like-model ZigBee device discrimination using an SDR platform