The wireless communication system's performance is greatly constrained by the wireless channel characteristics,especially in some specific environment.Therefore,signal transmission will be greatly impacted even if...The wireless communication system's performance is greatly constrained by the wireless channel characteristics,especially in some specific environment.Therefore,signal transmission will be greatly impacted even if not in a complicated topography.Testing results show that it is hardly to characterize the radio propagation properties for the antenna installed on the ground.In order to ensure a successful communication,the radio frequency(RF)wireless signal intensity monitor system was designed.We can get the wireless link transmission loss through measuring signal strength from received node.The test shows that the near-ground wireless signal propagation characteristics still can be characterized by the log distance propagation loss model.These results will conduce to studying the transmission characteristic of Near-Earth wireless signals and will predict the coverage of the earth's surface wireless sensor network.展开更多
Wireless channel modeling has always been one of the most fundamental highlights of the wireless communication research.The performance of new advanced models and technologies heavily depends on the accuracy of the wi...Wireless channel modeling has always been one of the most fundamental highlights of the wireless communication research.The performance of new advanced models and technologies heavily depends on the accuracy of the wireless CSI(Channel State Information).This study examined the randomness of the wireless channel parameters based on the characteristics of the radio propagation environment.The diversity of the statistical properties of wireless channel parameters inspired us to introduce the concept of the tomographic channel model.With this model,the static part of the CSI can be extracted from the huge amount of existing CSI data of previous measurements,which can be de ned as the wireless channel feature.In the proposed scheme for obtaining CSI with the tomographic channel model,the GMM(Gaussian Mixture Model)is applied to acquire the distribution of the wireless channel parameters,and the CNN(Convolutional Neural Network)is applied to automatically distinguish di erent wireless channels.The wireless channel feature information can be stored oine to guide the design of pilot symbols and save pilot resources.The numerical results based on actual measurements demonstrated the clear diversity of the statistical properties of wireless channel parameters and that the proposed scheme can extract the wireless channel feature automatically with fewer pilot resources.Thus,computing and storage resources can be exchanged for the nite and precious spectrum resource.展开更多
文摘The wireless communication system's performance is greatly constrained by the wireless channel characteristics,especially in some specific environment.Therefore,signal transmission will be greatly impacted even if not in a complicated topography.Testing results show that it is hardly to characterize the radio propagation properties for the antenna installed on the ground.In order to ensure a successful communication,the radio frequency(RF)wireless signal intensity monitor system was designed.We can get the wireless link transmission loss through measuring signal strength from received node.The test shows that the near-ground wireless signal propagation characteristics still can be characterized by the log distance propagation loss model.These results will conduce to studying the transmission characteristic of Near-Earth wireless signals and will predict the coverage of the earth's surface wireless sensor network.
基金This work is supported by the National Natural Science Foundation of China(No.61631013)National Key Basic Research Program of China(973 Program)(No.2013CB329002)+1 种基金National Major Project(No.2014ZX03003002-002)Program for New Century Excellent Talents in University(No.NCET-13-0321).
文摘Wireless channel modeling has always been one of the most fundamental highlights of the wireless communication research.The performance of new advanced models and technologies heavily depends on the accuracy of the wireless CSI(Channel State Information).This study examined the randomness of the wireless channel parameters based on the characteristics of the radio propagation environment.The diversity of the statistical properties of wireless channel parameters inspired us to introduce the concept of the tomographic channel model.With this model,the static part of the CSI can be extracted from the huge amount of existing CSI data of previous measurements,which can be de ned as the wireless channel feature.In the proposed scheme for obtaining CSI with the tomographic channel model,the GMM(Gaussian Mixture Model)is applied to acquire the distribution of the wireless channel parameters,and the CNN(Convolutional Neural Network)is applied to automatically distinguish di erent wireless channels.The wireless channel feature information can be stored oine to guide the design of pilot symbols and save pilot resources.The numerical results based on actual measurements demonstrated the clear diversity of the statistical properties of wireless channel parameters and that the proposed scheme can extract the wireless channel feature automatically with fewer pilot resources.Thus,computing and storage resources can be exchanged for the nite and precious spectrum resource.
