Graduation Semester and Year




Document Type


Degree Name

Master of Science in Electrical Engineering


Electrical Engineering

First Advisor

Stephen R. Gibbs


Radio-frequency identification (RFID) systems are designed for fast and accurate identification of multiple RFID tags. Their performance depends on the effective detection andresolution of communication collisions caused by the presence of multiple tags in the reader's field. Present RFID protocols do not rely upon the received physical waveform obtainedduring a collision for either collision resolution or improved identification rate. This signal contains important information that is often ignored or otherwise discarded.In this thesis I analyze the physical layer information extracted from a collision waveform from the ISO-18000-6C protocol and identifypotentially performance enhancing information contained therein. Utilization of this information to increase the tag identification rate is examined and the effectivenessof these approaches is analyzed. We find that utilizing the information contained within the physical waveforms can improve the identification rate for ISO 18000-6C systems by as much as 21\%. By modifying the protocol to explicitly take advantage of this waveform information, we estimate that another 10\% identification rate improvement may be achieved.This thesis proposes a method of using the physical layer signal from a collision to detect the existence of a weak tag in the presence of stronger tag to improve the reliability of the present protocol.The performance of random number generator on the chip and may be non-ideal leading to a non-uniform distribution. The effect of this deviation from the theoretical values and its effect on the performance of the protocol is analyzed by simulation. Output of the random number generator of some standard RFID tags is also evaluated.


Electrical and Computer Engineering | Engineering


Degree granted by The University of Texas at Arlington