Development of a Synchronous Measurement System for WBAN Channel Modeling Considering Human Body Motion

Abstract

Developments of WBAN channel models require a lot of experiments and simulations. To reduce them, our research group has been proposing a concept of WBAN channel modeling using human motions as parameters. In this report, a human motion and received signal strength synchronization measurement system is proposed. Human motion data is collected by a motion capture device (MOCAP) and the received signal strength (RSSI) data is collected by a BLE wireless device. To synchronize MOCAP and BLE data, a gesture-based method is proposed and confirmed by experiments. We also verified the operation of the measurement system and the possibility of path-loss or channel modeling based on human motion parameters. By using the measured human motion and RSSI data, RSSIs of future times are predicted by machine learning methods, RNN (Recurrent neural network), and LSTM (Long short-term memory). In conclusion, it was found that the RSSI in the future can be predicted to some extent from the past values of human body movements. This result would suggest the possibility of the modeling of WBAN channel variation with human motion as parameters.