An Advanced Dynamic Framed-Slotted ALOHA Algorithm Based on Bayesian Estimation and Probability Response | Zendy

Chaowei Wang | Zendy; Menglong Li | Zendy; Juyi Qiao | Zendy; Weidong Wang | Zendy; Xiuhua Li | Zendy

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An Advanced Dynamic Framed-Slotted ALOHA Algorithm Based on Bayesian Estimation and Probability Response

Author(s) -

Chaowei Wang,

Menglong Li,

Juyi Qiao,

Weidong Wang,

Xiuhua Li

Publication year - 2013

Publication title -

international journal of antennas and propagation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.282

H-Index - 37

eISSN - 1687-5877

pISSN - 1687-5869

DOI - 10.1155/2013/743468

Subject(s) - aloha , computer science , algorithm , frame (networking) , bayesian probability , stability (learning theory) , throughput , collision , estimation , identification (biology) , machine learning , artificial intelligence , engineering , telecommunications , wireless , systems engineering , botany , computer security , biology

This paper proposes an advanced dynamic framed-slotted ALOHA algorithm based on Bayesian estimation and probability response (BE-PDFSA) to improve the performance of radio frequency identification (RFID) system. The Bayesian estimation is introduced to improve the accuracy of the estimation algorithm for lacking a large number of observations in one query. The probability response is used to adjust responsive probability of the unrecognized tags to make the responsive tag number equal to the frame length. In this way, we can solve the problem of high collision rate with the increase of tag number and improve the throughput of the whole system. From the simulation results, we can see that the algorithm we proposed can greatly improve the stability of RFID system compared with DFSA and other commonly used algorithms

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