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
Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a ...Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a combined technology integrating an improved Kalman Filter with Space Domain Phase Difference of Arrival(SD-PDOA)and Received Signal Strength Indicator(RSSI).This methodology utilizes the distinct channel characteristics in multipath and NLoS contexts to effectively filter out interference and accurately extract localization information,thereby facilitating high precision and stability in passive RFID localization.The efficacy of this approach is demonstrated through detailed simulations and empirical tests conducted on a custom-built experimental platform consisting of passive RFID tags and an R420 reader.The findings are significant:in NLoS conditions,the four-antenna localization system achieved a notable localization accuracy of 0.25 m at a distance of 5 m.In complex multipath environments,this system achieved a localization accuracy of approximately 0.5 m at a distance of 5 m.When compared to conventional passive localization methods,our proposed solution exhibits a substantial improvement in indoor localization accuracy under NLoS and multipath conditions.This research provides a robust and effective technical solution for high-precision passive indoor localization in the Internet of Things(IoT)system,marking a significant advancement in the field.展开更多
Dear Editor,Asian rice(Oryza sativa)is the staple food for half the world and is a model crop that has been extensively studied.It contributes20%of calories to the human diet(Stein et al.,2018).With the increase in gl...Dear Editor,Asian rice(Oryza sativa)is the staple food for half the world and is a model crop that has been extensively studied.It contributes20%of calories to the human diet(Stein et al.,2018).With the increase in global population and rapid changes in climate,rice breeders need to develop new and sustainable cultivars with higher yields,healthier grains,and reduced environmental footprints(Wing et al.,2018).Since the first gold-standard reference genome of rice variety Nipponbare was published(International Rice Genome Sequencing Project,2005),an increasing number of rice accessions have been sequenced,assembled,and annotated with global efforts.Nowadays,a single reference genome is obviously insufficient to perform the genetic difference analysis for rice accessions.Therefore,the pan-genome has been proposed as a solution,which allows the discovery of more presence-absence variants compared with single-reference genome-based studies(Zhao et al.,2018).Over the past years,several databases,such as RAP-db(https://rapdb.dna.affrc.go.jp),RGAP(http://rice.uga.edu),and Gramene(https://www.gramene.org),have long-term served rice genomic research by providing information based on one or a series of individual reference genomes.To integrate and utilize the genomic information of multiple accessions,we performed comparative analyses and established the user-friendly Rice Gene Index(RGI;https://riceome.hzau.edu.cn)platform.RGI is the first gene-based pan-genome database for rice.展开更多
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.
基金supported in part by the Joint Project of National Natural Science Foundation of China(U22B2004,62371106)in part by 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Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a combined technology integrating an improved Kalman Filter with Space Domain Phase Difference of Arrival(SD-PDOA)and Received Signal Strength Indicator(RSSI).This methodology utilizes the distinct channel characteristics in multipath and NLoS contexts to effectively filter out interference and accurately extract localization information,thereby facilitating high precision and stability in passive RFID localization.The efficacy of this approach is demonstrated through detailed simulations and empirical tests conducted on a custom-built experimental platform consisting of passive RFID tags and an R420 reader.The findings are significant:in NLoS conditions,the four-antenna localization system achieved a notable localization accuracy of 0.25 m at a distance of 5 m.In complex multipath environments,this system achieved a localization accuracy of approximately 0.5 m at a distance of 5 m.When compared to conventional passive localization methods,our proposed solution exhibits a substantial improvement in indoor localization accuracy under NLoS and multipath conditions.This research provides a robust and effective technical solution for high-precision passive indoor localization in the Internet of Things(IoT)system,marking a significant advancement in the field.
基金supported by Fundamental Research Funds for the Central Universities(2662020SKPY010)the Major Project of Hubei Hongshan Laboratory(2022HSZD031)Huazhong Agricultural University’s Start-up Fund to J.Z.
文摘Dear Editor,Asian rice(Oryza sativa)is the staple food for half the world and is a model crop that has been extensively studied.It contributes20%of calories to the human diet(Stein et al.,2018).With the increase in global population and rapid changes in climate,rice breeders need to develop new and sustainable cultivars with higher yields,healthier grains,and reduced environmental footprints(Wing et al.,2018).Since the first gold-standard reference genome of rice variety Nipponbare was published(International Rice Genome Sequencing Project,2005),an increasing number of rice accessions have been sequenced,assembled,and annotated with global efforts.Nowadays,a single reference genome is obviously insufficient to perform the genetic difference analysis for rice accessions.Therefore,the pan-genome has been proposed as a solution,which allows the discovery of more presence-absence variants compared with single-reference genome-based studies(Zhao et al.,2018).Over the past years,several databases,such as RAP-db(https://rapdb.dna.affrc.go.jp),RGAP(http://rice.uga.edu),and Gramene(https://www.gramene.org),have long-term served rice genomic research by providing information based on one or a series of individual reference genomes.To integrate and utilize the genomic information of multiple accessions,we performed comparative analyses and established the user-friendly Rice Gene Index(RGI;https://riceome.hzau.edu.cn)platform.RGI is the first gene-based pan-genome database for rice.