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.
In this paper, an anti-collision protocol called code division cooperative identification protocol (CDCIP) is proposed in order to tackle the reader collision problem in smart RFID systems. CDCIP allocates orthogonal sequences to each reader and composes a RFID network. Consequently, it strives to let more than one reader work at the same time and at the same frequency. Eventually, comparing with the traditional protocol, the simulation results show that the proposed protocol offers better average throughput and lower power consumption of the system.
In RFID system, one of the key problems is the collision between tags, and many methods have been proposed to solve the problem. Framed Slotted ALOHA is a widely used algorithm in the anti-collision field of RFID system. In this paper, Matching grouping Framed Slotted ALOHA Algorithm is proposed. Compared to the conventional algorithms, this algorithm groups the tags to match the length of the frame, and would resolve the" Stray problem" of the tags at the same time. The simulation results show that the algorithm can improve the average throughput of the RFID system
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