Standard machine-learning approaches involve the centralization of training data in a data center,where centralized machine-learning algorithms can be applied for data analysis and inference.However,due to privacy res...Standard machine-learning approaches involve the centralization of training data in a data center,where centralized machine-learning algorithms can be applied for data analysis and inference.However,due to privacy restrictions and limited communication resources in wireless networks,it is often undesirable or impractical for the devices to transmit data to parameter sever.One approach to mitigate these problems is federated learning(FL),which enables the devices to train a common machine learning model without data sharing and transmission.This paper provides a comprehensive overview of FL applications for envisioned sixth generation(6G)wireless networks.In particular,the essential requirements for applying FL to wireless communications are first described.Then potential FL applications in wireless communications are detailed.The main problems and challenges associated with such applications are discussed.Finally,a comprehensive FL implementation for wireless communications is described.展开更多
The plasmonic photocatalyst of Pd supported on graphitic carbon nitride(Pd/g-C3N4)exhibits excellent catalytic activity in photo-induced hydrogenation of biomass-based aldehydes with environmental benign reagents of f...The plasmonic photocatalyst of Pd supported on graphitic carbon nitride(Pd/g-C3N4)exhibits excellent catalytic activity in photo-induced hydrogenation of biomass-based aldehydes with environmental benign reagents of formic acid(HCOOH)as proton source and triethylamine(TEA)as sacrificial electron donator.The chemical and configurational properties of the Pd/g-C3N4 were systematically analyzed with XRD,TEM and XPS.Under optimized conditions,27%yield of furfuryl alcohol with the corresponding turnover frequency(TOF)around 3.72 h^(-1) were obtained from furfural and TEA-HCOOH under visible-light irradiation by using Pd/g-C3N4.Our research additionally reveals that Pd atom is the true catalytic active site for the hydrogenation and the photo-promoted reduction mainly occurs through noble metal nanoparticles(NPs)-induced effect of surface plasmon resonance(SPR).The photo-catalytic system of Pd/g-C3N4 thus demonstrates a green and effective method for the hydrogenation of biomass-based aldehydes with sustainable solar energy as a driven force.展开更多
In this paper,the problem of trajectory de-sign of unmanned aerial vehicles(UAVs)for maximizing the number of satisfied users is studied in a UAV based cellular network where the UAV works as a flying base station tha...In this paper,the problem of trajectory de-sign of unmanned aerial vehicles(UAVs)for maximizing the number of satisfied users is studied in a UAV based cellular network where the UAV works as a flying base station that serves users,and the user indicates its satis-faction in terms of completion of its data request within an allowable maximum waiting time.The trajectory design is formulated as an optimization problem whose goal is to maximize the number of satisfied users.To solve this problem,a machine learning framework based on double Q-learning algorithm is proposed.The algorithm enables the UAV tofind the optimal trajectory that maximizes the number of satisfied users.Compared to the traditional learning algorithms,such as Q-learning that selects and evaluates the action using the same Q-table,the proposed algorithm can decouple the selection from the evaluation,therefore avoid overestimation which leads to sub-optimal policies.Simulation results show that the proposed algorithm can achieve up to 19.4% and 14.1% gains in terms of the number of satisfied users compared to random algorithm and Q-learning algorithm.展开更多
基金This work was supported by research grants from the Engineering and Physical Sciences Research Council(EPSRC),UK(EP/T015985/1)from US National Science Foundation(CCF-1908308).
文摘Standard machine-learning approaches involve the centralization of training data in a data center,where centralized machine-learning algorithms can be applied for data analysis and inference.However,due to privacy restrictions and limited communication resources in wireless networks,it is often undesirable or impractical for the devices to transmit data to parameter sever.One approach to mitigate these problems is federated learning(FL),which enables the devices to train a common machine learning model without data sharing and transmission.This paper provides a comprehensive overview of FL applications for envisioned sixth generation(6G)wireless networks.In particular,the essential requirements for applying FL to wireless communications are first described.Then potential FL applications in wireless communications are detailed.The main problems and challenges associated with such applications are discussed.Finally,a comprehensive FL implementation for wireless communications is described.
基金We are grateful for the financial support from National Natural Science Foundation of China(U1810111,21676089)Natural Science Foundation of Guangdong Province,China(2018B030311010)+1 种基金Youth Science and Technology Innovation Talent of Guangdong TeZhi Plan(2019TQ05L111)Key Laboratory of Biomass Chemical Engineering of Ministry of Education,Zhejiang University(2018BCE002).
文摘The plasmonic photocatalyst of Pd supported on graphitic carbon nitride(Pd/g-C3N4)exhibits excellent catalytic activity in photo-induced hydrogenation of biomass-based aldehydes with environmental benign reagents of formic acid(HCOOH)as proton source and triethylamine(TEA)as sacrificial electron donator.The chemical and configurational properties of the Pd/g-C3N4 were systematically analyzed with XRD,TEM and XPS.Under optimized conditions,27%yield of furfuryl alcohol with the corresponding turnover frequency(TOF)around 3.72 h^(-1) were obtained from furfural and TEA-HCOOH under visible-light irradiation by using Pd/g-C3N4.Our research additionally reveals that Pd atom is the true catalytic active site for the hydrogenation and the photo-promoted reduction mainly occurs through noble metal nanoparticles(NPs)-induced effect of surface plasmon resonance(SPR).The photo-catalytic system of Pd/g-C3N4 thus demonstrates a green and effective method for the hydrogenation of biomass-based aldehydes with sustainable solar energy as a driven force.
基金supported by the National Natural Science Foundation of China(U21A20284)Science and Technology Foundation of Guizhou Province(QKHZC20202Y037)+4 种基金the Science and Technology Innovation Program of Hunan Province(2020RC40052019RS1004)Innovation Mover Program of Central South University(2020CX007)National Research Foundation of Korea(NRF-2017R1A2B3004383)the China Scholarship Council(CSC)for the financial support(202006370306)。
基金supported in part by the National Natural Science Foundation of China under Grant 61671086 and Grant 61629101。
文摘In this paper,the problem of trajectory de-sign of unmanned aerial vehicles(UAVs)for maximizing the number of satisfied users is studied in a UAV based cellular network where the UAV works as a flying base station that serves users,and the user indicates its satis-faction in terms of completion of its data request within an allowable maximum waiting time.The trajectory design is formulated as an optimization problem whose goal is to maximize the number of satisfied users.To solve this problem,a machine learning framework based on double Q-learning algorithm is proposed.The algorithm enables the UAV tofind the optimal trajectory that maximizes the number of satisfied users.Compared to the traditional learning algorithms,such as Q-learning that selects and evaluates the action using the same Q-table,the proposed algorithm can decouple the selection from the evaluation,therefore avoid overestimation which leads to sub-optimal policies.Simulation results show that the proposed algorithm can achieve up to 19.4% and 14.1% gains in terms of the number of satisfied users compared to random algorithm and Q-learning algorithm.
