DEVICES AND METHODS FOR LOCALIZATION
The present invention relates to a computing device and a network device for estimating a location of a terminal device in a wireless network based on channel state information (CSI). In a training phase, the computing device divides a coverage area of the network device into sub-areas, and partitio...
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| creator | YANG, Ganghua LI, Yanchun CHU, Yun Yaw ARVANITAKIS, George |
| description | The present invention relates to a computing device and a network device for estimating a location of a terminal device in a wireless network based on channel state information (CSI). In a training phase, the computing device divides a coverage area of the network device into sub-areas, and partitions labelled CSI datasets into two or more CSI data partitions based on the sub-areas. The CSI data partitions are used to train two or more neural network models. Each CSI data partition corresponds to an area that is smaller than the coverage area, so that trainings of the neural network models are eased. Furthermore, the trained neural network models are robust to environment changes. In an online phase, the network device inputs CSI of the terminal device to at least two neural network models to obtain an optimal estimation based on outputs of the at least two neural network models. |
| format | Patent |
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In a training phase, the computing device divides a coverage area of the network device into sub-areas, and partitions labelled CSI datasets into two or more CSI data partitions based on the sub-areas. The CSI data partitions are used to train two or more neural network models. Each CSI data partition corresponds to an area that is smaller than the coverage area, so that trainings of the neural network models are eased. Furthermore, the trained neural network models are robust to environment changes. 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In a training phase, the computing device divides a coverage area of the network device into sub-areas, and partitions labelled CSI datasets into two or more CSI data partitions based on the sub-areas. The CSI data partitions are used to train two or more neural network models. Each CSI data partition corresponds to an area that is smaller than the coverage area, so that trainings of the neural network models are eased. Furthermore, the trained neural network models are robust to environment changes. In an online phase, the network device inputs CSI of the terminal device to at least two neural network models to obtain an optimal estimation based on outputs of the at least two neural network models.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | ANALOGOUS ARRANGEMENTS USING OTHER WAVES DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES MEASURING PHYSICS RADIO DIRECTION-FINDING RADIO NAVIGATION TESTING TRANSMISSION TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
| title | DEVICES AND METHODS FOR LOCALIZATION |
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