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A cooperative Bayesian and lower bound estimation in dynamic framed slotted ALOHA algorithm for RFID systems
Author(s) -
Benssalah Mustapha,
Djeddou Mustapha,
Dahou Brahim,
Drouiche Karim,
Maali Abdelmadjid
Publication year - 2018
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3723
Subject(s) - aloha , computer science , algorithm , radio frequency identification , upper and lower bounds , bayesian probability , identification (biology) , bayes estimator , cramér–rao bound , real time computing , estimation theory , throughput , telecommunications , artificial intelligence , mathematics , wireless , computer security , mathematical analysis , botany , biology
Summary A novel estimation scheme that combines Bayesian and lower bound estimating radio frequency identification tag population size is proposed. The developed methodology is based on the fusion between the Bayesian and lower bound estimating techniques. It turns out that the fusion rule is built up thanks to an existing linear relationship between the cited techniques. Simulation results show that the developed technique significantly improves the accuracy of the estimating tag quantity and presents less estimation error. Also, the resulting advanced dynamic framed slotted ALOHA protocol considerably improves the performance and efficiency of the radio frequency identification anti‐collision compared with the most recent protocols using others estimating methods.