Abstract
As a cost-effective localization scheme, radio tomographic imaging (RTI) has become a hot topic in the field of indoor positioning. In most previous works, the received signal strength (RSS), which is extremely unstable in indoor multipath environments, is used as the measurement. In this paper, we propose to leverage the fine-grained channel state information (CSI) for RTI. Further, by incorporating the multiple input and multiple output (MIMO) technique, we establish the CSI-MIMO attenuation model which utilizes the benefits of frequency diversity and spatial diversity. In addition, we also change the signal frequency to a higher one which can enhance the shadowing loss. We conduct experiments to evaluate the performance of CSI-MIMO based RTI. Experimental results show that the localization accuracy of the proposed method can be considerably improved compared with the RSS-based RTI methods.
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