LS Channel Estimation and Signal Separation for UHF RFID Tag Collision Recovery on the Physical Layer

In a passive ultra-high frequency (UHF) radio-frequency identification (RFID) system, tag collision is generally resolved on a medium access control (MAC) layer. However, some of collided tag signals could be recovered on a physical (PHY) layer and, thus, enhance the identification efficiency of the RFID system. For the recovery on the PHY layer, channel estimation is a critical issue. Good channel estimation will help to recover the collided signals. Existing channel estimates work well for two collided tags. When the number of collided tags is beyond two, however, the existing estimates have more estimation errors. In this paper, we propose a novel channel estimate for the UHF RFID system. It adopts an orthogonal matrix based on the information of preambles which is known for a reader and applies a minimum-mean-square-error (MMSE) criterion to estimate channels. From the estimated channel, we could accurately separate the collided signals and recover them. By means of numerical results, we show that the proposed estimate has lower estimation errors and higher separation efficiency than the existing estimates.

[1]  Wei Xiang,et al.  An energy- and time-efficient M-ary detecting tree RFID MAC protocol , 2015, 2015 IEEE International Conference on Communications (ICC).

[2]  Yuan-Cheng Lai,et al.  General binary tree protocol for coping with the capture effect in RFID tag identification , 2010, IEEE Communications Letters.

[3]  Yifan Chen,et al.  An improved dynamic framed slotted ALOHA Anti-collision algorithm based on estimation method for RFID systems , 2015, 2015 IEEE International Conference on RFID (RFID).

[4]  Yu Zeng,et al.  Bayesian Tag Estimate and Optimal Frame Length for Anti-Collision Aloha RFID System , 2010, IEEE Transactions on Automation Science and Engineering.

[5]  George N. Karystinos,et al.  Single-Antenna Coherent Detection of Collided FM0 RFID Signals , 2012, IEEE Transactions on Communications.

[6]  Iec Jtc . Subcommittee Sc Parameters for air interface communications at 860 MHz to 960 MHz = Paramètres pour les communications d'une interface d'air entre 860 MHz et 960 MHz , 2004 .

[7]  Paolo Castiglione,et al.  Pseudo-Random ALOHA for Enhanced Collision-Recovery in RFID , 2013, IEEE Communications Letters.

[8]  Xiaohu Tang,et al.  An Adaptive Anti-Collision Protocol for Large-Scale RFID Tag Identification , 2014, IEEE Wireless Communications Letters.

[9]  Min Shao,et al.  An improved dynamic adaptive multi-tree search anti-collision algorithm based on RFID , 2014, 2014 International Conference on Data Science and Advanced Analytics (DSAA).

[10]  Klaus Finkenzeller,et al.  Rfid Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification , 2003 .

[11]  Junyu Wang,et al.  Separation of multiple passive RFID signals using Software Defined Radio , 2009, 2009 IEEE International Conference on RFID.

[12]  Anna Scaglione,et al.  Multipacket Reception of Passive UHF RFID Tags: A Communication Theoretic Approach , 2011, IEEE Transactions on Signal Processing.

[13]  Kwan-Wu Chin,et al.  A Survey and Tutorial of RFID Anti-Collision Protocols , 2010, IEEE Communications Surveys & Tutorials.

[14]  Gaia Maselli,et al.  Inducing Collisions for Fast RFID Tag Identification , 2015, IEEE Communications Letters.

[15]  Etienne Perret,et al.  Simulation and measurement of collision signal in passive UHF RFID system and edge transition anti-collision algorithm , 2014, 2014 IEEE RFID Technology and Applications Conference (RFID-TA).

[16]  Robert Langwieser,et al.  RFID Reader Receivers for Physical Layer Collision Recovery , 2010, IEEE Trans. Commun..

[17]  Yu Zeng,et al.  Channel estimation for recovery of UHF RFID tag collision on physical layer , 2015, 2015 International Conference on Computer, Information and Telecommunication Systems (CITS).

[18]  Yu Zeng,et al.  Binary Tree Slotted ALOHA for Passive RFID Tag Anticollision , 2013, IEEE Transactions on Parallel and Distributed Systems.

[19]  Marc Moonen,et al.  Optimal training design for MIMO OFDM systems in mobile wireless channels , 2003, IEEE Trans. Signal Process..

[20]  Alberto J. Palma,et al.  Passive UHF RFID Tag with Multiple Sensing Capabilities , 2015, Sensors.