PHY assisted tree-based RFID identification

Abstract

Tree-based RFID identification adopts a binary-tree structure to collect IDs of an unknown set. Tag IDs locate at the leaf nodes and the reader queries through intermediate tree nodes and converges to these IDs using feedbacks from tag responses. Existing works cannot function well under random ID distribution as they ignore the distribution information hidden in the physical-layer signal of colliding tags. Different from them, we introduce PHY-Tree, a novel tree-based scheme that collects two types of distribution information from every encountered colliding signal. First, we detect if all colliding tags send the same bit content at each bit index by looking into inherent temporal features of the tag modulation schemes. If such resonant states are detected, either left or right branch of a certain subtree can be trimmed horizontally. Second, we estimate the number of colliding tags in a slot by computing a related metric defined over the signal's constellation map, based on which nodes in the same layers of a certain subtree can be skipped vertically. Evaluations from both experiments and simulations demonstrate that PHY-Tree outperforms state-of-the-art schemes by at least 1.79×.