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作 者:杨帆 任守纲[3] 徐焕良[3] 孙元昊[2] 杨星[2] YANG Fan;REN Shou-gang;XU Huan-liang;SUN Yuan-hao;YANG Xing(School of Mathematics and Statistics,Jiangsu Normal University,Xuzhou 221116;College of Engineering,Nanjing Agricultural University,Nanjing 210031;College of Information Science and Technology,Nanjing Agricultural University,Nanjing 210095,China)
机构地区:[1]江苏师范大学数学与统计学院,江苏徐州221116 [2]南京农业大学工学院,江苏南京210031 [3]南京农业大学信息科学技术学院,江苏南京210095
出 处:《计算机工程与科学》2020年第3期449-455,共7页Computer Engineering & Science
基 金:徐州市推动科技创新项目(KC18004);江苏师范大学科研基金(15XLB02)。
摘 要:为了进一步提高稠密标签环境中标签估计算法的精度,在分析比较传统的基于比特标签估计算法的基础上,提出一种比特估计的优化算法。首先,基于二项分布理论,利用未被选择比特位的观测值计算空闲比特率;然后,通过确定空闲比特率的阈值,建立稠密标签环境中的标签数量估计模型;最后,推导出标签数量估计值与时隙消耗的数学表达式。仿真结果表明,改进算法的标签估计精度要优于传统的基于比特标签估计的精度,且对于不同规模的标签群,改进算法具有稳定的估计性能。In order to further improve the accuracy of the tag number estimation algorithms in dense tags environment,based on the analysis and comparison of the traditional bit estimation algorithms,a novel optimized bit estimation algorithm is proposed.Firstly,based on the binomial distribution theory,the observation of non-selected bits is used to calculate the idle bit rate.Then,a tag number estimation model in dense tags environment is established by determining the threshold of idle bit rate.Finally,the mathematical expression of the relationship between the estimated tag number and the slot consumption is derived.The simulation results show that the proposed algorithm has better estimation accuracy than the traditional bit estimation algorithms and is stable under different numbers of tags.
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