New Technique Of Channel Characterization For Body Centered Wireless Communication

Nowadays,as people pay more and more attention to the quality of life and their own heath,bio-medical health has undoubtedly become one of the hot topics in the world in twenty-first century.As the most essential problem of human existence,it has a bright future for development and research value.At present,we have been able to monitor the body-centered medical health of life through wireless body area network(WBAN).WBAN contains lots of research directions: indoor positioning of human body,fall monitoring,sleep monitoring,heartbeat monitoring and lip recognition.Since the emergence of WBAN,scientists have proposed a number of innovative basis for monitoring life health,such as: received signal strength indicator(RSSI)and channel state information(CSI).Due to the simplicity and low cost of obtaining RSSI,many researchers have selected it for their research.Combined with some specific algorithms,we can carry out a series of topics in WBAN.However,the methods based on RSSI generally have two disadvantages: Firstly,RSSI values usually have a high variability over time for a fixed location due to the multipath effects in indoor environment.Secondly,RSSI values are coarse information,which can't exploit the subcarriers for richer multipath information.In contrast to RSSI,CSI can characterize the multipath propagation in a way.Combine with computer technology,wireless communication technology and the typical disease of medical community---essential tremor(ET),we are able to design a set of systems to identify this type of motion sickness accurately.The transmitter sends signal to receiver at a specific frequency and the receiver obtains real-time varied path gain data of patients in this particular environment with the body posture changing.Compared with the experimental data of normal people,we can extract and analyze the characteristics of this disease and recognize the disease finally.Based on OFDM,we have been able to obtain CSI data at sub-carrier level from some advanced Wi-Fi network interface cards(NICs).Different from RSSI in the MAC layer,CSI contains a lot of channel information which is invisible to MAC layer as the physical layer information.More specifically,CSI describes how a signal propagates from transmitter(s)to the receiver(s)and reveals the combined effect of,for instance,scattering,fading,and power decay with distance.As a kind of new object for research,CSI is introduced into WBAN for identifying motion sickness.The conclusion shows that CSI has higher accuracy and reliability during monitoring the medical health of life.Besides,it also has good robustness in complex environment.We are able to extract better and more robust signature from CSI in order to perceive subtler or broader environment information in the time domain and frequency domain and this can provide a new way for the diagnosis of various types of diseases and unmanned monitoring latterly.