In this paper,the influence of voltage rising time on a pulsed-dc helium-air plasma at atmospheric pressure is numerically simulated.Simulation results show that as the voltage rising time increases from 10 ns to 30 n...In this paper,the influence of voltage rising time on a pulsed-dc helium-air plasma at atmospheric pressure is numerically simulated.Simulation results show that as the voltage rising time increases from 10 ns to 30 ns,there is a decrease in the discharge current,namely 0.052 A when the voltage rising time is 10 ns and 0.038 A when the voltage rising time is 30 ns.Additionally,a shorter voltage rising time results in a faster breakdown,a more rapidly rising current waveform,and a higher breakdown voltage.Furthermore,the basic parameters of the streamer discharge also increase with voltage rise rate,which is ascribed to the fact that more energetic electrons are produced in a shorter voltage rising time.Therefore,a pulsed-dc voltage with a short rising time is desirable for efficient production of nonequilibrium atmospheric pressure plasma discharge.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
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
基金supported by National Natural Science Foundation of China(NSFC) under Grant No.11465013the Natural Science Foundation of Jiangxi Province under Grant Nos.20151BAB212012 and 20161BAB201013part by the International Science and Technology Cooperation Program of China under Grant No.2015DFA61800
文摘In this paper,the influence of voltage rising time on a pulsed-dc helium-air plasma at atmospheric pressure is numerically simulated.Simulation results show that as the voltage rising time increases from 10 ns to 30 ns,there is a decrease in the discharge current,namely 0.052 A when the voltage rising time is 10 ns and 0.038 A when the voltage rising time is 30 ns.Additionally,a shorter voltage rising time results in a faster breakdown,a more rapidly rising current waveform,and a higher breakdown voltage.Furthermore,the basic parameters of the streamer discharge also increase with voltage rise rate,which is ascribed to the fact that more energetic electrons are produced in a shorter voltage rising time.Therefore,a pulsed-dc voltage with a short rising time is desirable for efficient production of nonequilibrium atmospheric pressure plasma discharge.
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.
