Abstract
In this letter, a novel sub-frame-based dynamic frame slotted ALOHA (DFSA) algorithm is proposed for efficient tag identification based on EPC C1 Gen2 radio frequency identification (RFID) standard. Through the observation of slot states in a sub-frame, the reader estimates the tag number, and quickly adjusts the frame length to match the quantity of backlog. Once the appropriate frame length is observed, the algorithm will return to traditional DSFA. We use the modified maximum a posteriori probability (MAP) method for the estimation of tag quantity to improve the accuracy. To reduce the computation complexity of traditional MAP, we use tables to store estimation numbers. Due to the length strict of sub-frames, only a relatively small size of memory is required. Simulation results show that dynamic sub-frame MAP can improve the system utility (approximately 0.36) and reduce the computation complexity, only with an addition of less than 3-kB memory.
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