Power line communication(PLC)provides intelligent electrical functions such as power quality measurement,fault surveys,and remote control of electrical network.Most of research works have been done in low voltage(LV)s...Power line communication(PLC)provides intelligent electrical functions such as power quality measurement,fault surveys,and remote control of electrical network.Most of research works have been done in low voltage(LV)scenario due to the fast development of in-home PLC.The aim of this paper is to evaluate the link-level performance of a medium voltage(MV)MIMO-OFDM communication system based on transmission link under underground power line channel.The MIMO channel is modeled as a modified multipath model in the presence of impulsive noise and background noise.We first perform a measurement on the practical MV MIMO channel parameters for a section of buried cable of 1 km long in Ganzhou city,Jiangxi province,China.Based on the measured channel,we design the frame structure based on an IEEE standard for broadband over power line networks[1]to support MV MIMO-OFDM transmission.According to designed frame structure,we design an encoder and a decoder for a dual binary tail-biting turbo code and optimize some key decoder parameters for low bit error rate performance.Finally,the link-level performance for both spatial multiplexing and spatial diversity are evaluated.Numeral results show that MV MIMO-OFDM is a promising approach to provide both high data rate and link reliability for PLC.展开更多
The distributed parameters of the transmission lines have the significant impact to the signal propagation. In the conventional method of the distributed parameter extraction,the discontinuity of inverse trigonometric...The distributed parameters of the transmission lines have the significant impact to the signal propagation. In the conventional method of the distributed parameter extraction,the discontinuity of inverse trigonometric or hyperbolic can arise the problem about phase ambiguity which causes significant errors for transmission models. A difference iteration method（ DIM） is proposed for extracting distributed parameters of high frequency transmission line structure in order to overcome the phase ambiguity in the conventional method（ CM）. The formulations of the proposed method are first derived for two-conductor and multi-conductor lines. Then the validation is performed for the models of micro-strip transmission line. Numerical results demonstrate that the proposed DIM can solve the problem about the phase ambiguity and the extracted distributed parameters are accurate and efficient for a wide range of the frequencies of interest and line lengths.展开更多
The display image of a PC can be reconstructed by using the conducted emission on the PC＇s network cable. The relevant signals which be used to reconstruct the original image are coupling from the radiation of the sw...The display image of a PC can be reconstructed by using the conducted emission on the PC＇s network cable. The relevant signals which be used to reconstruct the original image are coupling from the radiation of the switching of red, green, blue （RGB） signals in PC. These pertinent signals are partly contained in the frequency region higher than 30 MHz in the conducted emission. From these findings, the near-field coupling principle from PC to the network cable is analyzed firstly. And then, a multi-conductor transmission model for the RGB signals which transmit in the network cable is proposed. In addition, the maximum safe distance is estimated by using this model. In order to check the validity of the estimating distance, the eavesdropping experiment is carried out to reconstruct the original display image. The results demonstrate that the blurred display image can be retrieved at the place of 29.5 m.展开更多
Signal processing has entered the era of big data,and improving processing efficiency becomes crucial.Traditional computing architectures face computational efficiency limitations due to the separation of storage and ...Signal processing has entered the era of big data,and improving processing efficiency becomes crucial.Traditional computing architectures face computational efficiency limitations due to the separation of storage and computation.Array circuits based on multi-conductor devices enable full hardware convolutional neural networks(CNNs),which hold great potential to improve computational efficiency.However,when processing large-scale convolutional computations,there is still a significant amount of device redundancy,resulting in low computational power consumption and high computational costs.Here,we innovatively propose a memristor-based in-situ convolutional strategy,which uses the dynamic changes in the conductive wire,doping area,and polarization area of memristors as the process of convolutional operations,and uses the time required for conductance switching of a single device as the computation result,embodying convolutional computation through the unique spiked digital signal of the memristor.Our strategy reasonably encodes complex analog signals into simple digital signals through a memristor,completing the convolutional computation at the device level,which is essential for complex signal processing and computational efficiency improvement.Based on the implementation of device-level convolutional computing,we have achieved feature recognition and noise filtering for braille signals.We believe that our successful implementation of convolutional computing at the device level will promote the construction of complex CNNs with large-scale convolutional computing capabilities,bringing innovation and development to the field of neuromorphic computing.展开更多
文摘Power line communication(PLC)provides intelligent electrical functions such as power quality measurement,fault surveys,and remote control of electrical network.Most of research works have been done in low voltage(LV)scenario due to the fast development of in-home PLC.The aim of this paper is to evaluate the link-level performance of a medium voltage(MV)MIMO-OFDM communication system based on transmission link under underground power line channel.The MIMO channel is modeled as a modified multipath model in the presence of impulsive noise and background noise.We first perform a measurement on the practical MV MIMO channel parameters for a section of buried cable of 1 km long in Ganzhou city,Jiangxi province,China.Based on the measured channel,we design the frame structure based on an IEEE standard for broadband over power line networks[1]to support MV MIMO-OFDM transmission.According to designed frame structure,we design an encoder and a decoder for a dual binary tail-biting turbo code and optimize some key decoder parameters for low bit error rate performance.Finally,the link-level performance for both spatial multiplexing and spatial diversity are evaluated.Numeral results show that MV MIMO-OFDM is a promising approach to provide both high data rate and link reliability for PLC.
基金supported by the National Natural Science Foundation of China(61201082)the Youth Science and Engineering Planning Project of Communication University of China(3132018XNG1817)
文摘The distributed parameters of the transmission lines have the significant impact to the signal propagation. In the conventional method of the distributed parameter extraction,the discontinuity of inverse trigonometric or hyperbolic can arise the problem about phase ambiguity which causes significant errors for transmission models. A difference iteration method（ DIM） is proposed for extracting distributed parameters of high frequency transmission line structure in order to overcome the phase ambiguity in the conventional method（ CM）. The formulations of the proposed method are first derived for two-conductor and multi-conductor lines. Then the validation is performed for the models of micro-strip transmission line. Numerical results demonstrate that the proposed DIM can solve the problem about the phase ambiguity and the extracted distributed parameters are accurate and efficient for a wide range of the frequencies of interest and line lengths.
基金supported by the National Natural Science Foundation of China (61072136, 61171051)
文摘The display image of a PC can be reconstructed by using the conducted emission on the PC＇s network cable. The relevant signals which be used to reconstruct the original image are coupling from the radiation of the switching of red, green, blue （RGB） signals in PC. These pertinent signals are partly contained in the frequency region higher than 30 MHz in the conducted emission. From these findings, the near-field coupling principle from PC to the network cable is analyzed firstly. And then, a multi-conductor transmission model for the RGB signals which transmit in the network cable is proposed. In addition, the maximum safe distance is estimated by using this model. In order to check the validity of the estimating distance, the eavesdropping experiment is carried out to reconstruct the original display image. The results demonstrate that the blurred display image can be retrieved at the place of 29.5 m.
基金the financial support from the National Natural Science Foundation of China(62374033,and 62304039)Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(2021ZZ129)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(GZB20240155)。
文摘Signal processing has entered the era of big data,and improving processing efficiency becomes crucial.Traditional computing architectures face computational efficiency limitations due to the separation of storage and computation.Array circuits based on multi-conductor devices enable full hardware convolutional neural networks(CNNs),which hold great potential to improve computational efficiency.However,when processing large-scale convolutional computations,there is still a significant amount of device redundancy,resulting in low computational power consumption and high computational costs.Here,we innovatively propose a memristor-based in-situ convolutional strategy,which uses the dynamic changes in the conductive wire,doping area,and polarization area of memristors as the process of convolutional operations,and uses the time required for conductance switching of a single device as the computation result,embodying convolutional computation through the unique spiked digital signal of the memristor.Our strategy reasonably encodes complex analog signals into simple digital signals through a memristor,completing the convolutional computation at the device level,which is essential for complex signal processing and computational efficiency improvement.Based on the implementation of device-level convolutional computing,we have achieved feature recognition and noise filtering for braille signals.We believe that our successful implementation of convolutional computing at the device level will promote the construction of complex CNNs with large-scale convolutional computing capabilities,bringing innovation and development to the field of neuromorphic computing.
