As the underlying foundation of a digital twin network(DTN),digital twin channel(DTC)can accurately depict the electromagnetic wave propagation in the air interface to support the DTN-based 6G wireless network.Since e...As the underlying foundation of a digital twin network(DTN),digital twin channel(DTC)can accurately depict the electromagnetic wave propagation in the air interface to support the DTN-based 6G wireless network.Since electromagnetic wave propagation is affected by the environment,constructing the relationship between the environment and radio wave propagation is the key to implementing DTC.In the existing methods,the environmental information inputted into the neural network has many dimensions,and the correlation between the environment and the channel is unclear,resulting in a highly complex relationship construction process.To solve this issue,we propose a unified construction method of radio environment knowledge(REK)inspired by the electromagnetic wave property to quantify the propagation contribution based on easily obtainable location information.An effective scatterer determination scheme based on random geometry is proposed which reduces redundancy by 90%,87%,and 81%in scenarios with complete openness,impending blockage,and complete blockage,respectively.We also conduct a path loss prediction task based on a lightweight convolutional neural network(CNN)employing a simple two-layer convolutional structure to validate REK’s effectiveness.The results show that only 4 ms of testing time is needed with a prediction error of 0.3,effectively reducing the network complexity.展开更多
Can the geographical proximity of an industry to the“technological knowledge pool”outside its own sector effectively enhance its innovation performance?Are there differences in the effects brought about by geographi...Can the geographical proximity of an industry to the“technological knowledge pool”outside its own sector effectively enhance its innovation performance?Are there differences in the effects brought about by geographical proximity based on different types of linkages?Under the framework of the knowledge production function,this paper empirically examines the innovation performance enhancement effect of differentiated technological knowledge pools formed by directional industrial spatial coagglomeration,using data from the industrial enterprise database and patent database.The findings reveal that the level of industrial innovation is positively influenced by the diverse technological knowledge pools generated through industrial spatial coagglomeration.This conclusion remains valid even after addressing potential endogeneity issues by employing the UK's industrial coagglomeration index as an instrumental variable.In particular,knowledge spillovers serve as the primary mechanism through which industrial coagglomeration is influenced by technological knowledge pools from outside its own sector.The innovation spillover effect of active coagglomeration is significantly greater than that of passive coagglomeration,and the impact of technological knowledge pools on the scale of industrial innovation is slightly stronger than on the quality of innovation.Further research indicates that only active coagglomeration between industries with input-output linkages can significantly enhance the innovation capabilities of both industries,while industrial coagglomeration with technological linkages demonstrates a notable“parasitic effect.”The policy implications of this paper suggest that local governments should thoroughly consider the spatial dependency relationships and historical patterns of inter-industry location selection when developing regionally diversified industrial clusters.Simultaneously,they should strengthen intellectual property protection and industry regulation to achieve high-quality development of regional industries.展开更多
Additive manufacturing(AM),a revolutionary production technique that will make many previously inconceivable innovations a reality,is transforming the manufacturing sector.The technologies behind AM have a generic cha...Additive manufacturing(AM),a revolutionary production technique that will make many previously inconceivable innovations a reality,is transforming the manufacturing sector.The technologies behind AM have a generic character and possess immense and transformative potential that will be felt across different sectors of the economy.This paper studies how entrepreneurs can access,exploit,and diffuse this new disruptive knowledge,as well as the potential challenges that lie ahead.Further,we examine the magnitude of the knowledge pool created by the Top 10 countries in AM research from 2011 to 2016;specifically,we determine the leading countries,the pattern of organizational and international collaborations,leading disciplines contributing to AM,and the pattern in authors'affiliations.We find that the US is clearly the dominant country,while China witnessed a notable acceleration in AM research between 2014 and 2016;we also show that universities are the predominant actor in codified AM knowledge creation.Using this information,we paint a vivid picture of the technological and market opportunities for entrepreneurs and identify the gaps in the current knowledge production environment;we find that the challenges currently faced by entrepreneurs could be overcome through academic entrepreneurship,collective entrepreneurship,and the actions of an entrepreneurial state.展开更多
基金supported by the National Key R&D Program of China(No.2023YFB2904803)the National Natural Science Foundation of China(Nos.62341128,62201087,and 62101069)+2 种基金the National Science Fund for Distinguished Young Scholars,China(No.61925102)the Beijing Natural Science Foundation,China(No.L243002)the Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘As the underlying foundation of a digital twin network(DTN),digital twin channel(DTC)can accurately depict the electromagnetic wave propagation in the air interface to support the DTN-based 6G wireless network.Since electromagnetic wave propagation is affected by the environment,constructing the relationship between the environment and radio wave propagation is the key to implementing DTC.In the existing methods,the environmental information inputted into the neural network has many dimensions,and the correlation between the environment and the channel is unclear,resulting in a highly complex relationship construction process.To solve this issue,we propose a unified construction method of radio environment knowledge(REK)inspired by the electromagnetic wave property to quantify the propagation contribution based on easily obtainable location information.An effective scatterer determination scheme based on random geometry is proposed which reduces redundancy by 90%,87%,and 81%in scenarios with complete openness,impending blockage,and complete blockage,respectively.We also conduct a path loss prediction task based on a lightweight convolutional neural network(CNN)employing a simple two-layer convolutional structure to validate REK’s effectiveness.The results show that only 4 ms of testing time is needed with a prediction error of 0.3,effectively reducing the network complexity.
基金supported by the major project of the National Social Science Fund of China(No.22&ZD066)the youth program of the National Natural Science Foundation of China(No.72303026)the general program of the China Postdoctoral Science Foundation(No.2022M710693).
文摘Can the geographical proximity of an industry to the“technological knowledge pool”outside its own sector effectively enhance its innovation performance?Are there differences in the effects brought about by geographical proximity based on different types of linkages?Under the framework of the knowledge production function,this paper empirically examines the innovation performance enhancement effect of differentiated technological knowledge pools formed by directional industrial spatial coagglomeration,using data from the industrial enterprise database and patent database.The findings reveal that the level of industrial innovation is positively influenced by the diverse technological knowledge pools generated through industrial spatial coagglomeration.This conclusion remains valid even after addressing potential endogeneity issues by employing the UK's industrial coagglomeration index as an instrumental variable.In particular,knowledge spillovers serve as the primary mechanism through which industrial coagglomeration is influenced by technological knowledge pools from outside its own sector.The innovation spillover effect of active coagglomeration is significantly greater than that of passive coagglomeration,and the impact of technological knowledge pools on the scale of industrial innovation is slightly stronger than on the quality of innovation.Further research indicates that only active coagglomeration between industries with input-output linkages can significantly enhance the innovation capabilities of both industries,while industrial coagglomeration with technological linkages demonstrates a notable“parasitic effect.”The policy implications of this paper suggest that local governments should thoroughly consider the spatial dependency relationships and historical patterns of inter-industry location selection when developing regionally diversified industrial clusters.Simultaneously,they should strengthen intellectual property protection and industry regulation to achieve high-quality development of regional industries.
文摘Additive manufacturing(AM),a revolutionary production technique that will make many previously inconceivable innovations a reality,is transforming the manufacturing sector.The technologies behind AM have a generic character and possess immense and transformative potential that will be felt across different sectors of the economy.This paper studies how entrepreneurs can access,exploit,and diffuse this new disruptive knowledge,as well as the potential challenges that lie ahead.Further,we examine the magnitude of the knowledge pool created by the Top 10 countries in AM research from 2011 to 2016;specifically,we determine the leading countries,the pattern of organizational and international collaborations,leading disciplines contributing to AM,and the pattern in authors'affiliations.We find that the US is clearly the dominant country,while China witnessed a notable acceleration in AM research between 2014 and 2016;we also show that universities are the predominant actor in codified AM knowledge creation.Using this information,we paint a vivid picture of the technological and market opportunities for entrepreneurs and identify the gaps in the current knowledge production environment;we find that the challenges currently faced by entrepreneurs could be overcome through academic entrepreneurship,collective entrepreneurship,and the actions of an entrepreneurial state.
