Abstract
RFID tags are used for varied applications in large numbers. Human Tracking is one such important application wherein the RFID system detects the presence of a tag in a dense tag environment. Quick estimation of the number of tags in the field at a desired level of accuracy is one of the most common requirements in the present scenario. Identification of tags has become a critical area which need more time and unsuitable in many situations; especially where tag set is dense. We introduce a novel medium access control (MAC) protocol for Radio Frequency IDentification (RFID) systems which exploits the statistical information collected at the reader. The protocol, termed Adaptive Slot Adaptive Frame (ASAF) ALOHA protocol, is motivated to significantly improve the total read time performance of the currently suggested MAC protocols for RFID systems by minimizing the collisions of the tags. In order to perform this task, ASAF estimates the dynamic tag population and adapts the frame size and number of slots simultaneously in the subsequent round via a simple policy that maximizes an appropriately defined function. We demonstrated that ASAF is better than the current RFID MAC protocols. We also considered the case where suddenly if the number of tags increases, the running frame with adapted slots gets flushed away and new frame with increased number of slots gets adapted automatically by the system showing the robustness in this case as well.
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