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Data analysis and modeling method for indoor human body-shadowing MIMO channels

In recent years, MIMO communication systems such as IMT-Advanced and LTE have been put into practical use. Since MIMO transmission has an advantage in use in the indoor multipath-rich environment, the accurate indoor MIMO channel model is required for evaluating the systems. In the indoor environment, it is known that the channel state changes dynamically due to the human shadowing effect even if the receiver and the transmitter are fixed. In this paper, we propose the data analysis method of measured data for the indoor channel modeling. In our proposal, the propagation parameters of rays are estimated using SAGE algorithm. Then the rays are clustered using K-Power-Means algorithm. Next the human body shadowing of each cluster is estimated according to the resultant power variation of cluster. We carried out the measurements at 3.35GHz in the indoor environment and estimated the human body shadowing of each cluster.