关键词: 贝叶斯算法, 泊松分布规则, FastICA 独立主成分分析法, EPC 编码

Abstract:

The channel resources of RFID ( Radio Frequency Identification) systems are limited, and when multiple tags compete for the same frequency or time slot, it can lead to collisions and conflicts. In order to optimize the communication efficiency of broadcast channels, a collision prevention algorithm for RFID broadcast channels in the Internet of Things based on frame time slot ALOHA is proposed. This method introduces the concept of frame time slots and divides the communication time into time slots; By analyzing the probability of occurrence of idle, successful identification, and collision states within the time slot, the cause of collision in the

broadcast channel is obtained. By combining Bayesian algorithm and Poisson distribution rules, the probability distribution of the number of tags is calculated to estimate the number of tags within the range of the reader and writer, and the next frame length is adjusted based on the calculation result of the number of tags. If there is still label collision problem within the adjusted frame time slot range, FastICA( Indcpendent Component Analysis) independent principal component analysis is used to transform the label recognition problem within the frame time slot into an EPC(Electronic Product Code) encoding generation problem, thereby achieving parallel recognition of multiple labels within a unified time slot and avoiding collision situations. The experiment shows that the estimation of the number of labels proposed is accurate, which can improve the label recognition rate within the time slot and effectively improve the propagation efficiency of the broadcast channel while ensuring the stability of the communication channel.

Key words: bayesian algorithm, poisson distribution rule, indcpendent component analysis ( FastICA ) independent principal component analysis, electronic product code(EPC) code