Massive MIMO is one of tile enabling technologies tbr beyond 4G and 5G systems due to its ability to provide beamforming gain and reduce interference Dual-polarized antenna is widely adopted to accommodate a large num...Massive MIMO is one of tile enabling technologies tbr beyond 4G and 5G systems due to its ability to provide beamforming gain and reduce interference Dual-polarized antenna is widely adopted to accommodate a large number of antenna elements in limited space. However, current CSI(channel state information) feedback schemes developed in LTE for conventional MIMO systems are not efficient enough for massive MIMO systems since the overhead increases almost linearly with the number of antenna. Moreover, the codebook for massive MIMO will be huge and difficult to design with the LTE methodology. This paper proposes a novel CSI feedback scheme named layered Multi-paths Information based CSI Feedback (LMPIF), which can achieve higher spectrum efficiency for dual-polarized antenna system with low feedback overhead. The MIMO channel is decomposed into long term components (multipath directions and amplitudes) and short term components (multipath phases). The relationship between the two components and the optimal precoder is derived in closed form. To reduce the overhead, different granularities in feedback time have been applied for the long term components and short term components Link and system level simulation results prove that LMPIF can improve performance considerably with low CSI feedback overhead.展开更多
Due to higher demands on product diversity,flexible shift between productions of different products in one equipment becomes a popular solution,resulting in existence of multiple operation modes in a single process.In...Due to higher demands on product diversity,flexible shift between productions of different products in one equipment becomes a popular solution,resulting in existence of multiple operation modes in a single process.In order to handle such multi-mode process,a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode.In addition,both low and high order information are considered in each layer.The common and specific information within each mode can be captured and separated into several subspaces according to the different order information.The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman(TE)benchmark.Compared with previous methods,superiority of the proposed method is validated by the better monitoring results.展开更多
An intelligent virtual environment is described for training users in the operation of complex engineering systems. After analyzing the original model of virtual environment, a virtual agent perception model was put f...An intelligent virtual environment is described for training users in the operation of complex engineering systems. After analyzing the original model of virtual environment, a virtual agent perception model was put forward. The information layer was inserted into original virtual environment. The model classifies all kinds of information and offers a way for knowledge description of virtual environment, and contributes to set up feeling model for the Virtual Agent within virtual environment.展开更多
基金supported by the National High-Tech R&D Program(863 Program 2015AA01A705)
文摘Massive MIMO is one of tile enabling technologies tbr beyond 4G and 5G systems due to its ability to provide beamforming gain and reduce interference Dual-polarized antenna is widely adopted to accommodate a large number of antenna elements in limited space. However, current CSI(channel state information) feedback schemes developed in LTE for conventional MIMO systems are not efficient enough for massive MIMO systems since the overhead increases almost linearly with the number of antenna. Moreover, the codebook for massive MIMO will be huge and difficult to design with the LTE methodology. This paper proposes a novel CSI feedback scheme named layered Multi-paths Information based CSI Feedback (LMPIF), which can achieve higher spectrum efficiency for dual-polarized antenna system with low feedback overhead. The MIMO channel is decomposed into long term components (multipath directions and amplitudes) and short term components (multipath phases). The relationship between the two components and the optimal precoder is derived in closed form. To reduce the overhead, different granularities in feedback time have been applied for the long term components and short term components Link and system level simulation results prove that LMPIF can improve performance considerably with low CSI feedback overhead.
基金the National Natural Science Foundation of China(61903352)China Postdoctoral Science Foundation(2020M671721)+4 种基金Zhejiang Province Natural Science Foundation of China(LQ19F030007)Natural Science Foundation of Jiangsu Province(BK20180594)Project of department of education of Zhejiang province(Y202044960)Project of Zhejiang Tongji Vocational College of Science and Technology(TRC1904)Foundation of Key Laboratory of Advanced Process Control for Light Industry(Jiangnan University),Ministry of Education,P.R.China,APCLI1803.
文摘Due to higher demands on product diversity,flexible shift between productions of different products in one equipment becomes a popular solution,resulting in existence of multiple operation modes in a single process.In order to handle such multi-mode process,a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode.In addition,both low and high order information are considered in each layer.The common and specific information within each mode can be captured and separated into several subspaces according to the different order information.The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman(TE)benchmark.Compared with previous methods,superiority of the proposed method is validated by the better monitoring results.
基金Supported by National Natural Science Foundation of China(No.60472093)
文摘An intelligent virtual environment is described for training users in the operation of complex engineering systems. After analyzing the original model of virtual environment, a virtual agent perception model was put forward. The information layer was inserted into original virtual environment. The model classifies all kinds of information and offers a way for knowledge description of virtual environment, and contributes to set up feeling model for the Virtual Agent within virtual environment.