hence, a signal loss of the HBC channel can be measured accurately. A signal loss of the HBC channel has a property of subject-dependency: each HBC user has a different signal loss due to different in the volume ratio of the body tissues that each HBC user has. Using the proposed measurement method, a signal loss was measured with respect to each of multiple human subjects and the subject-dependency of a signal loss was then investigated. Using the measured signal losses, a signal loss model was derived. To be an accurate model, a signal loss model should be able to represent the subject-dependency; however, the subject-dependency has not been modeled in previous signal-loss models. In this study, the subject-dependency was modeled using an impulse response having a random variable. Along with the subject-dependency, correlated amplitudes that occur in the im-pulse response due to capacitive coupling of the HBC channel were also modeled.
The human body functions as an antenna in a low frequency band under 100 MHz; such antenna function of the human body generates a noise signal in the HBC channel when an HBC user is exposed to electromagnetic (EM) waves radiated from electronic devices or wireless services. Several studies have con-ducted measurement of a noise signal in the HBC channel; however, noise signals were measured only in a laboratory, which is significantly different from a general electromagnetic interference (EMI) environment. In this study, a noise signal was measured in a general EMI environment, where noise sources are randomly lo-cated. Using the measured noise signals, a noise model was derived. Power of a noise signal is affected by a load effect. During derivation of the noise model, such a load effect was compensated; consequently, the noise model in this study can be applied to any load condition.
Along with generation of a noise signal, the antenna function of the human body causes co-channel interference. When multiple HBC users exist in proximity to each other, data signals are radiated from HBC users owing to the radiating characteristic of the human body; the radiated signals are propagated through the air medium to an HBC user experiencing interference and then become an interference signal causing the co-channel interference. Although the co-channel interference in HBC should be well understood to achieve a reliable communication, the co-channel interference has not yet been studied. In this study, the co-channel interference was measured and simulated respectively; a co-channel interference model was then proposed to model characteristics of an interference signal caused by the co-channel interference.
After modelling each transmission property, BER degradation was investigated with respect to a signal transmission supporting HBC PHY of the IEEE 802.15.6 standard. The BER performance was simulated using the signal loss and noise models respectively. To prevent BER degradation caused by a noise signal, a noise-reduction filter was designed; the filter design was conducted under the condition that a signal loss had variation due to the subject-dependency. To model BER degradation caused by the co-channel interference, SIR and BER parameters were newly introduced. Unlike an existing SIR, SIR in this study is easily obtainable using a distribution of HBC users; hence, after the distribution of HBC users is determined, BER degradation can be easily estimated using the BER degradation model. The selective simulation method was proposed to obtain the BER parameter with the less number of BER samples.
The channel and BER degradation models presented in this study can be effectively used to achieve reliable data communication using HBC. The BER degradation model can be used to estimate BER perfor-mance of an HBC receiver; the estimated results can then be used to obtain system requirements for reliable data communication. The methods to measure and model the HBC channel are valid even when location of HBC transmitter and receiver is changed; hence, those methods can be applied to various HBC applications.; Human Body Communication (HBC) uses the human body, whose tissues have the features of a los-sy dielectric material, as a transmission channel to transmit data from one device to another one, allowing devices to communicate without wired or wireless connections. As a transmission channel for a data signal, the human body has unique transmission properties that have not been observed in wire or wireless channels. This study presents a model for an HBC channel. For this, the transmission properties of a signal loss, noise, and co-channel interference were modeled respectively. The IEEE 802.15.6 working group has published a standard of a physical layer (PHY) for HBC. Along with the HBC channel model, this study presents a model for BER degradation that occurs in a signal transmission following the standard. For this, using the HBC channel model, BER degradation that is experienced by an HBC receiver supporting HBC PHY of the IEEE 802.15.6 standard was simulated.
A coupling condition between ground planes of HBC transmitter and receiver significantly affects a signal loss of the HBC channel. To measure such a signal loss, the ground-isolated measurement method was proposed. Unlike previous measurement methods, the measurement setup in the proposed method does not affect the coupling that occurs in an HBC application, for which a signal loss is measured