Performance Enhancement of RFID Anti-Collision Algorithm Based on Reinforcement Learning 


Vol. 45,  No. 9, pp. 1587-1590, Sep.  2020
10.7840/kics.2020.45.9.1587


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  Abstract

In the RFID (Radio Frequency Identification) systems, when a number of tags send their own IDs, the number of slots in a frame can be adjusted to alleviate the collisions. However, non-optimal frame size causes throughput decrease and significantly increases the time to complete transmissions. In this letter, we adopted the Q-Learning, one of reinforcement learning methods and the proposed method showed better performance in views of throughput and transmission completion time compared previous studies.

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  Cite this article

[IEEE Style]

T. Kim and G. Hwang, "Performance Enhancement of RFID Anti-Collision Algorithm Based on Reinforcement Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 9, pp. 1587-1590, 2020. DOI: 10.7840/kics.2020.45.9.1587.

[ACM Style]

Tae-Wook Kim and Gyung-Ho Hwang. 2020. Performance Enhancement of RFID Anti-Collision Algorithm Based on Reinforcement Learning. The Journal of Korean Institute of Communications and Information Sciences, 45, 9, (2020), 1587-1590. DOI: 10.7840/kics.2020.45.9.1587.

[KICS Style]

Tae-Wook Kim and Gyung-Ho Hwang, "Performance Enhancement of RFID Anti-Collision Algorithm Based on Reinforcement Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 9, pp. 1587-1590, 9. 2020. (https://doi.org/10.7840/kics.2020.45.9.1587)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880