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When the radio frequency identification (RFID) system inventories multiple tags, the recognition rate will be seriously affected due to collisions. Based on the existing dynamic frame slotted Aloha (DFSA) algorithm, a sub-frame observation and cyclic redundancy check (CRC) grouping combined dynamic framed slotted Aloha (SUBF-CGDFSA) algorithm is proposed. The algorithm combines the precise estimation method of the quantity of large-scale tags, the large-scale tags grouping mechanism based on CRC pseudo-random characteristics, and the Aloha anti-collision optimization mechanism based on sub-frame observation. By grouping tags and sequentially identifying them within subframes, it accurately estimates the number of remaining tags and optimizes frame length accordingly to improve efficiency in large-scale RFID systems. Simulation outcomes demonstrate that this proposed algorithm can effectively break through the system throughput bottleneck of 36.8%, which is up to 30% higher than the existing DFSA standard scheme, and has more significant advantages, which is suitable for application in large-scale RFID tags scenarios.
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