Maximum Likelihood decoding for non-synchronized UHF RFID tags

Kenawy H, Elsaid Ibrahim HAA, Robert J, Heuberger A (2016)


Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2016

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 89-92

Article Number: 7444330

ISBN: 9781509016907

DOI: 10.1109/WISNET.2016.7444330

Abstract

In Radio Frequency Identification (RFID) systems, when multiple tags reply at the same slot, collision occurs. The tags reply are with different data and also different rates. The rate tolerance between the tags reply reaches to 22% of the nominal value of the rate which plays a significant role for the stability and the efficiency of RFID systems. This variation in the tags reply rates inhibit to use the ML receiver which is very sensitive to the rate variation between collided replies. This paper focuses on decoding the collided tags with different rates in the RFID systems using Maximum Likelihood (ML) receiver. A new algorithm is proposed to make the ML receiver is insensitive the rate tolerance between the tags reply. The simulations show that the dual receive antennas ML receiver that is used to recover two collided tags over Rayleigh channel is not affected by the rate tolerance. The receiver performance is compared with the previous proposed dual antenna receivers, Minimum Mean Square Error (MMSE), Zero Forcing (ZF), and Ordered SUccessive Cancellation (OSUC). The proposed receiver outperforms the other types of receivers as it has the largest diversity gain.

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How to cite

APA:

Kenawy, H., Elsaid Ibrahim, H.A.A., Robert, J., & Heuberger, A. (2016). Maximum Likelihood decoding for non-synchronized UHF RFID tags. In Proceedings of the IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2016 (pp. 89-92). Institute of Electrical and Electronics Engineers Inc..

MLA:

Kenawy, Hamed, et al. "Maximum Likelihood decoding for non-synchronized UHF RFID tags." Proceedings of the IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2016 Institute of Electrical and Electronics Engineers Inc., 2016. 89-92.

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