为提高射频识别(Radio frequency identification,RFID)标签的识别效率,本文针对RFID动态帧时隙ALOHA防冲突系统,提出了新的标签估计方法和帧长确定方案.标签估计中采用了不同的贝叶斯代价函数,提出了几种贝叶斯标签估计方法,它们的估...为提高射频识别(Radio frequency identification,RFID)标签的识别效率,本文针对RFID动态帧时隙ALOHA防冲突系统,提出了新的标签估计方法和帧长确定方案.标签估计中采用了不同的贝叶斯代价函数,提出了几种贝叶斯标签估计方法,它们的估计结果准确,而且通过减小标签数取值范围可使计算复杂度得到降低.随后,推导出一种根据标签数确定最优帧长的方案,它能使系统达到最大的信道利用率,该最大信道利用率要大于帧的时隙数等于标签数时所能达到的最大利用率.展开更多
在射频识别(radio frequency identification, RFID)系统中,动态帧时隙ALOHA算法是解决标签碰撞问题的常用算法。针对现有ALOHA算法存在调整至最佳帧长消耗步数过长和再识别过程中空时隙过多问题,文章提出了一种基于动态帧时隙ALOHA的...在射频识别(radio frequency identification, RFID)系统中,动态帧时隙ALOHA算法是解决标签碰撞问题的常用算法。针对现有ALOHA算法存在调整至最佳帧长消耗步数过长和再识别过程中空时隙过多问题,文章提出了一种基于动态帧时隙ALOHA的改进算法。该算法根据当前时刻静态标签数确定阈值和调整帧长,减少了达到最佳帧长的步数,再识别过程中利用分治算法思想,对冲突标签按冲突时隙数划分成若干相互独立、规模较小的最优子结构,使每次轮询空时隙降到最低,从而实现了以最少时延完成识别。仿真结果表明,本文提出的算法能有效地降低时延,提高系统运行效率。展开更多
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-fr...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-randomcharacteristics,and the Aloha anti-collision optimization mechanism based on sub-frame observation.By grouping tags and sequentially identifying themwithin 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 algorithmcan 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 largescale RFID tags scenarios.展开更多
文摘为提高射频识别(Radio frequency identification,RFID)标签的识别效率,本文针对RFID动态帧时隙ALOHA防冲突系统,提出了新的标签估计方法和帧长确定方案.标签估计中采用了不同的贝叶斯代价函数,提出了几种贝叶斯标签估计方法,它们的估计结果准确,而且通过减小标签数取值范围可使计算复杂度得到降低.随后,推导出一种根据标签数确定最优帧长的方案,它能使系统达到最大的信道利用率,该最大信道利用率要大于帧的时隙数等于标签数时所能达到的最大利用率.
文摘在射频识别(radio frequency identification, RFID)系统中,动态帧时隙ALOHA算法是解决标签碰撞问题的常用算法。针对现有ALOHA算法存在调整至最佳帧长消耗步数过长和再识别过程中空时隙过多问题,文章提出了一种基于动态帧时隙ALOHA的改进算法。该算法根据当前时刻静态标签数确定阈值和调整帧长,减少了达到最佳帧长的步数,再识别过程中利用分治算法思想,对冲突标签按冲突时隙数划分成若干相互独立、规模较小的最优子结构,使每次轮询空时隙降到最低,从而实现了以最少时延完成识别。仿真结果表明,本文提出的算法能有效地降低时延,提高系统运行效率。
基金supported in part by National Natural Science Foundation of China(U22B2004,62371106)in part by the Joint Project of China Mobile Research Institute&X-NET(Project Number:2022H002)+6 种基金in part by the Pre-Research Project(31513070501)in part by National Key R&D Program(2018AAA0103203)in part by Guangdong Provincial Research and Development Plan in Key Areas(2019B010141001)in part by Sichuan Provincial Science and Technology Planning Program of China(2022YFG0230,2023YFG0040)in part by the Fundamental Enhancement Program Technology Area Fund(2021-JCJQ-JJ-0667)in part by the Joint Fund of ZF and Ministry of Education(8091B022126)in part by Innovation Ability Construction Project for Sichuan Provincial Engineering Research Center of Communication Technology for Intelligent IoT(2303-510109-04-03-318020).
文摘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-randomcharacteristics,and the Aloha anti-collision optimization mechanism based on sub-frame observation.By grouping tags and sequentially identifying themwithin 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 algorithmcan 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 largescale RFID tags scenarios.
