基于非空时隙数的无线射频识别标签估算算法

针对无线射频识别(RFID)系统中现有标签估计算法估计时间长、误差大的问题,提出了一种基于非空时隙数的标签估算方法。首先,分析了动态帧时隙ALOHA(DFSA)算法的系统模型,指出标签估算的必要性;其次,对当前存在的一些标签估计算法进行了研究,列举其存在的不足;再次,通过在不同帧长条件下对非空时隙平均数与待识别标签数的关系进行研究,得出两者之间存在着的不依赖于帧长的归一化曲线并将其运用于标签估计。而且通过引入精度需求,运用概率分析理论和折半查找的方法来确定不同标签总数下的轮询次数K;最后,对所提标签估计算法进行仿真,从估算精度和估算时间两个方面与现有的标签估算算法作了性能对比分析。仿真结果表明,该算法最大估计误差仅为1%,在帧长为128、标签数为400的情况下,相比Adaptive Slotted ALOHA Protocol(ASAP)、Fast Zero Estimation(FZE)、最大后验概率(MAP)估计算法,其误差率分别减少了66.7%、78.3%和72.2%;此外在识别相同数目标签的情况下,所提算法耗费的估计时间也明显少于上述3种算法。由此可见,基于非空时隙数的标签估算算法具有较高的估算精度和估算效率,能够对RFID系统中的待识别标签进行快速准确的识别。

Estimation algorithm of radio frequency identification tags based on non-empty slot number

Regarding the problem of long estimation time and big estimation error of tag estimation algorithms that currently exist in Radio Frequency Identification (RFID) system, a novel tag estimation method based on non-empty slot number was proposed. Firstly, the model of Dynamic Frame Slot ALOHA (DFSA) algorithm was analyzed to point out the necessity of tag estimation; secondly, some tag estimation algorithms were researched and their shortcomings were listed; thirdly, by researching the relationship between the average number of non-empty slots and the number of total tags to be identified in different frame length conditions, a normalized curve independent of frame length was obtained and applied to estimate tag numbers. Furthermore, by introducing accuracy demand, the total number of polling times K under different tag numbers was determined by using probability theory and binary search method; finally, a simulation was conducted and a comparative analysis of performance between the proposed method and some existing tag estimation algorithms was done from aspects of estimation accuracy and estimation time. The simulation results show that the maximum error rate of the proposed algorithm is only 1%. When the frame length was 128 and the total tag number was 400, the error rate of the proposed tag estimation algorithm was reduced by 66.7%, 78.3% and 72.2% respectively compared with Adaptive Slotted ALOHA Protocol (ASAP), Fast Zero Estimation (FZE) and Maximum A Posteriori (MAP) estimation algorithm. What's more, in the case of recognizing the same number of tags, the estimation time of the proposed algorithm was also significantly less than that of the above-mentioned three algorithms. Thus, the proposed method has higher estimation accuracy and estimation efficiency and can identify tags quickly and accurately in RFID system.