随着对于大规模人群聚集活动的监控需求日益凸显,基于Wi-Fi的人群密度监测技术逐渐应用于公共安全管理,但其受限于RSSI(received signal strength indicator)的显著波动性与MAC地址匿名化造成的个体识别困难,特别在高密度场景下,其估计...随着对于大规模人群聚集活动的监控需求日益凸显,基于Wi-Fi的人群密度监测技术逐渐应用于公共安全管理,但其受限于RSSI(received signal strength indicator)的显著波动性与MAC地址匿名化造成的个体识别困难,特别在高密度场景下,其估计精度与稳定性仍难以保障。对此,提出一种抗随机性的Wi-Fi探针数据人群密度估计方法,通过设计一种基于时间窗的累计RSSI计算策略,利用局部建模构建区域密度映射关系,捕捉区域人群的动态变化,实现了复杂环境下稳定人群密度估计。所提方法在米级精度上分别取得了0.9723的整体准确率和0.8974的高密度场景准确率,实验结果表明其性能良好,具备跨场景推广的理论潜力与良好的泛用性。展开更多
In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and m...In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and multiple user detection techniques,our scheme can reach a high throughput of 0.98 without feedback under finite frame size settings,where the upper bound on performance is 1.Moreover,a lower bound on throughput performance is derived,which is tight in some parameter settings and can be used to approximate theoretical performance.Simulation results validate our analysis and confirm the advantages of our proposed scheme.展开更多
Hydrogel microcapsules are powerful microreactor vessels that have attracted widespread attention and research.Among the various methods for their generation,the aqueous two-phase system(ATPS)is by far the most straig...Hydrogel microcapsules are powerful microreactor vessels that have attracted widespread attention and research.Among the various methods for their generation,the aqueous two-phase system(ATPS)is by far the most straightforward approach.However,the high viscosity of ATPS solutions significantly limits the generation throughput of hydrogel microcapsule.In this study,we developed a novel high-throughput approach for generating hydrogel microcapsules using a microfluidic bubble-triggering strategy.By integrating constant-pressure air flow with droplet microfluidics devices,we efficiently manipulated the formation of ATPS droplet through bubble-induced Rayleigh-Plateau instability,enabling the production of uniform,monodisperse microcapsules.Additionally,the droplet generation frequency in the bubble-triggering method exceeded 36 kHz.We further demonstrated the encapsulation of genetically engineered Escherichia coli strains,which acted as biosensors for arsenic ions and caprolactam,highlighting the potential of these microcapsules for biosensing applications.This advancement in hydrogel microcapsule generation offers promising implications for scalable applications in biosensing,organoid culture,and high-throughput screening.展开更多
The integration of the intelligent reflecting surface(IRS)with simultaneous wireless information and power transfer(SWIPT)has emerged as a cost-effective and efficient solution to enhance the performance of informatio...The integration of the intelligent reflecting surface(IRS)with simultaneous wireless information and power transfer(SWIPT)has emerged as a cost-effective and efficient solution to enhance the performance of information and energy transfer.In this research,a hybrid active/passive IRS-assisted SWIPT system is proposed.Specifically,an active IRS(AIRS)and a passive IRS(PIRS)are deployed in the SWIPT system to facilitate a multiantenna base station(BS)in simultaneously delivering information and energy to multiple information users(IUs)and energy users(EUs).The objective is to maximize the sum throughput by jointly optimizing the transmitter beamforming and the reflection coefficient matrices of the AIRS and the PIRS while satisfying the transmitter power constraints,the energy harvesting(EH)requirements of EUs,and the AIRS amplification power limitations.However,the optimization variables are highly coupled and cannot be solved directly.To tackle this complex problem,we propose an efficient algorithm based on alternating optimization(AO)and semi-definite relaxation(SDR)techniques to obtain high-quality solutions.Simulation results demonstrate that the hybrid active/passive IRSassisted SWIPT system significantly enhances throughput performance and outperforms benchmark systems.展开更多
Wi-Fi technology has evolved significantly since its introduction in 1997,advancing to Wi-Fi 6 as the latest standard,with Wi-Fi 7 currently under development.Despite these advancements,integrating machine learning in...Wi-Fi technology has evolved significantly since its introduction in 1997,advancing to Wi-Fi 6 as the latest standard,with Wi-Fi 7 currently under development.Despite these advancements,integrating machine learning into Wi-Fi networks remains challenging,especially in decentralized environments with multiple access points(mAPs).This paper is a short review that summarizes the potential applications of federated reinforcement learning(FRL)across eight key areas of Wi-Fi functionality,including channel access,link adaptation,beamforming,multi-user transmissions,channel bonding,multi-link operation,spatial reuse,and multi-basic servic set(multi-BSS)coordination.FRL is highlighted as a promising framework for enabling decentralized training and decision-making while preserving data privacy.To illustrate its role in practice,we present a case study on link activation in a multi-link operation(MLO)environment with multiple APs.Through theoretical discussion and simulation results,the study demonstrates how FRL can improve performance and reliability,paving the way for more adaptive and collaborative Wi-Fi networks in the era of Wi-Fi 7 and beyond.展开更多
文摘随着对于大规模人群聚集活动的监控需求日益凸显,基于Wi-Fi的人群密度监测技术逐渐应用于公共安全管理,但其受限于RSSI(received signal strength indicator)的显著波动性与MAC地址匿名化造成的个体识别困难,特别在高密度场景下,其估计精度与稳定性仍难以保障。对此,提出一种抗随机性的Wi-Fi探针数据人群密度估计方法,通过设计一种基于时间窗的累计RSSI计算策略,利用局部建模构建区域密度映射关系,捕捉区域人群的动态变化,实现了复杂环境下稳定人群密度估计。所提方法在米级精度上分别取得了0.9723的整体准确率和0.8974的高密度场景准确率,实验结果表明其性能良好,具备跨场景推广的理论潜力与良好的泛用性。
文摘In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and multiple user detection techniques,our scheme can reach a high throughput of 0.98 without feedback under finite frame size settings,where the upper bound on performance is 1.Moreover,a lower bound on throughput performance is derived,which is tight in some parameter settings and can be used to approximate theoretical performance.Simulation results validate our analysis and confirm the advantages of our proposed scheme.
基金sponsored by the National Key R&D Program of China(no.2023YFB3208203)the National Natural Science Foundation of China(no.62374170)the Science and Technology Commission of Shanghai Municipality(no.23J21900200).
文摘Hydrogel microcapsules are powerful microreactor vessels that have attracted widespread attention and research.Among the various methods for their generation,the aqueous two-phase system(ATPS)is by far the most straightforward approach.However,the high viscosity of ATPS solutions significantly limits the generation throughput of hydrogel microcapsule.In this study,we developed a novel high-throughput approach for generating hydrogel microcapsules using a microfluidic bubble-triggering strategy.By integrating constant-pressure air flow with droplet microfluidics devices,we efficiently manipulated the formation of ATPS droplet through bubble-induced Rayleigh-Plateau instability,enabling the production of uniform,monodisperse microcapsules.Additionally,the droplet generation frequency in the bubble-triggering method exceeded 36 kHz.We further demonstrated the encapsulation of genetically engineered Escherichia coli strains,which acted as biosensors for arsenic ions and caprolactam,highlighting the potential of these microcapsules for biosensing applications.This advancement in hydrogel microcapsule generation offers promising implications for scalable applications in biosensing,organoid culture,and high-throughput screening.
基金National Natural Science Foundation of China(No.62301141)。
文摘The integration of the intelligent reflecting surface(IRS)with simultaneous wireless information and power transfer(SWIPT)has emerged as a cost-effective and efficient solution to enhance the performance of information and energy transfer.In this research,a hybrid active/passive IRS-assisted SWIPT system is proposed.Specifically,an active IRS(AIRS)and a passive IRS(PIRS)are deployed in the SWIPT system to facilitate a multiantenna base station(BS)in simultaneously delivering information and energy to multiple information users(IUs)and energy users(EUs).The objective is to maximize the sum throughput by jointly optimizing the transmitter beamforming and the reflection coefficient matrices of the AIRS and the PIRS while satisfying the transmitter power constraints,the energy harvesting(EH)requirements of EUs,and the AIRS amplification power limitations.However,the optimization variables are highly coupled and cannot be solved directly.To tackle this complex problem,we propose an efficient algorithm based on alternating optimization(AO)and semi-definite relaxation(SDR)techniques to obtain high-quality solutions.Simulation results demonstrate that the hybrid active/passive IRSassisted SWIPT system significantly enhances throughput performance and outperforms benchmark systems.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia,grant number RG-2-611-42(A.O.A.).
文摘Wi-Fi technology has evolved significantly since its introduction in 1997,advancing to Wi-Fi 6 as the latest standard,with Wi-Fi 7 currently under development.Despite these advancements,integrating machine learning into Wi-Fi networks remains challenging,especially in decentralized environments with multiple access points(mAPs).This paper is a short review that summarizes the potential applications of federated reinforcement learning(FRL)across eight key areas of Wi-Fi functionality,including channel access,link adaptation,beamforming,multi-user transmissions,channel bonding,multi-link operation,spatial reuse,and multi-basic servic set(multi-BSS)coordination.FRL is highlighted as a promising framework for enabling decentralized training and decision-making while preserving data privacy.To illustrate its role in practice,we present a case study on link activation in a multi-link operation(MLO)environment with multiple APs.Through theoretical discussion and simulation results,the study demonstrates how FRL can improve performance and reliability,paving the way for more adaptive and collaborative Wi-Fi networks in the era of Wi-Fi 7 and beyond.
