Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77521
 Title: PHY-Tree : physical layer tree-based RFID identification Authors: Hou, Y Zheng, Y Keywords: Physical layerRFIDTree-based identification Issue Date: 2018 Publisher: Institute of Electrical and Electronics Engineers Source: IEEE/ACM transactions on networking, 2018, v. 26, no. 2, p. 711-723 How to cite? Journal: IEEE/ACM transactions on networking 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 feedback from tag responses. Existing works cannot function well under the scenario of non-uniform ID distribution as they ignore those ID 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 information regarding ID distribution from every encountered colliding signal. First, we can 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 sub-tree 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 sub-tree can be skipped vertically. We thus call the two types of information as horizontal and vertical info. Evaluations from both experiments and simulations demonstrate that PHY-Tree outperforms the state-of-the-art schemes by at least 1.79\times . URI: http://hdl.handle.net/10397/77521 ISSN: 1063-6692 DOI: 10.1109/TNET.2018.2791938 Appears in Collections: Journal/Magazine Article