A dynamic pilot interval adjustment scheme for HBC channel estimation

As one important part of Internet of Things (IoT), wireless body area networks (WBANs) get rapid development in recent years. The majority of current WBAN researchers focus on the radio frequency (RF) solutions. However, there are still some intrinsic defects in the RF-based WBANs. Recently, human body communication (HBC) has been proposed in which the body itself is used as the propagation medium. To achieve high spectrum efficiency and power efficiency by HBC, one critical work is to acquire the channel information. In this paper, the HBC channel fading characteristics are measured and summarized. It is shown that the HBC channel is influenced by the body shape instead of the outside environment. When human body is in movement, normal random process can be used to describe the variations of HBC channel fading. Then, we propose a dynamic pilot interval adjustment scheme for HBC channel estimation. By applying this scheme, the pilot intervals in time domain can be adjusted along with the time-varying channel fading. The performance of the proposed scheme is evaluated by using measurement-based HBC channel fading model. It is proved that this scheme can substantially reduce the number of pilots without losing much accuracy and it can be beneficial for saving energy in the HBC networks.