An ALOHA-Based Algorithm Based on Grouping of Tag Prefixes for Industrial Internet of Things

Abstract

Nowadays, radio frequency identification (RFID) technology has been widely used in logistics, warehousing, urban transportation, medicine, and other fields due to its advantages of fast identification speed, low cost, and high security. The multitag collision problem causes the reader to fail to complete the identification of the tags in its coverage in time, thus seriously affecting the work efficiency of the entire RFID system. Therefore, the study of an efficient multitag identification algorithm is the basic premise to ensure the industrial application of RFID. Aiming at the problems of the low slot utilization rate of the existing DFSA algorithm in a large-scale tag recognition environment, we proposed a dynamic frame slotting anticollision algorithm based on tags prefix grouping called G-DFSA. G-DFSA uses the tag prefix to recognize the tag set and constructs the probe frame based on the grouping. Then, the slot statistics results of the probe frame are used to process the frames whose frame length does not match the number of tags. As shown in the simulation results, the system efficiency of the proposed algorithm is still close to the theoretical optimal throughput rate of DFSA algorithm 0.368 in the large-scale tag set. Compared with the existing methods, G-DFSA has obvious advantages in system throughput.