# Moving Towards Body-to-Body Sensor Networks for Ubiquitous Applications: A Survey
## 4 BBN Design Challenges and Open Issues
### Wireless Channel Propagation
#### 4.1.2 BBN Users in Movement
have conducted a number of experiments in [15] over five wireless channel modeling distributions: Nakagami [88], lognormal [89], Rice [90], Weibull [91], and \(k-\mu\)[92], among which the \(k-\mu\) distribution was proved to better characterize the indoor small-scale fading in body-to-body channels, but this study is earlier than [85]. \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**BBN Scenario** & **Description** & **Human Body Effect** & \(\pi\) & \(\mathbf{P_{0}}\) & \(\mathbf{X_{BS}}\) & \(\mathbf{X_{SM}}\) \\ \hline Stationary LOS & Person \(A\) and person \(B\) are & Increased variability in path loss caused & 2.1 & 39.8 & \(\mu=0.00\) & \(A=1.00\) \\ facing and stationary at a & by slight body movements. & & & \(\sigma=0.05\) & \(s=0.04\) \\ \hline Stationary NLOS & Person \(A\) and person \(B\) have & The path loss significantly increases & 1.9 & 77.9 & \(\mu=0.00\) & \(A=1.00\) \\  & their bodies rotated through & with an extra 40 dB attenuation & & & \(\sigma=0.11\) & \(s=0.04\) \\  & 180\({}^{\circ}\) and keep stationary & compared to the LOS state, due to the & & & & \\  & spread of the \(X_{BS}\) component. & & & & \\ \hline Rotation & Person \(A\) performs a full & Received signal under the noise & - & - & - & \(A=0.96\) \\  & 360\({}^{\circ}\) rotation, turning from & threshold of the receiver. & & & & \(s=0.14\) \\  & LOS to NLOS position & The magnitude of the \(X_{SM}\) increases & & & & \\  & due to the varying propagation links & & & & \\  & transmitting the wireless signal. & & & & & \\ \hline Tilt & Person \(A\) tilts his position & At 1 m, a variation of 10 dB in the signal & - & - & - & \(A=1.00\) \\  & through a 45\({}^{\circ}\) angle & & level is recorded due to the distance & & & \(s=0.04\) \\  & between the two persons. & & & & \\ \hline Walking LOS & Person \(A\) walks at a normal & When person \(A\) is walking, the path & 2.9 & 29.6 & \(\mu=0.00\) & \(A=1.00\) \\  & pace (0.88 m/s) towards & loss component \(n\) increases compared to & & & \(\sigma=0.20\) & \(s=0.05\) \\  & person \(B\) until reaching a distance of 1 m. & & & & & \\ \hline Walking NLOS & Person \(A\) turned 180\({}^{\circ}\) from & The constantly changing propagation & 1.5 & 79.6 & \(\mu=0.02\) & \(A=0.98\) \\  & person \(B\) and walks from an & paths impact the received signal level. & & & \(\sigma=0.28\) & \(s=0.16\) \\  & initial distance of 1 m to 15 & The spread of the standard deviation \(\sigma\) & & & \\  & \(m\). & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: BBN scenarios of the wireless signal propagation in outdoor environment. Figure 7: Scenario 1: walking line-of-sight (LOS)/non-line-of-sight (NLOS) Rx-heart/Tx-right-hand. Scenario 2: rotation Rx-heart/Tx-heart. Furthermore, recent studies [93; 94] evaluated the impact of the body mass index (BMI), which is a function of the height and weight of a person, characterizing the body fat, on the body-to-body signal propagation. A channel measurement campaign was conducted within UWB MIMO array system, in the 2-10 GHz frequency band, to evaluate the BMI-dependence of channel metrics, i.e., the gain, the shadowing and delay spread. It was concluded that parameters obtained with BMI for humans with large body sizes are notably different from those with standard BMI. Definitely, further researches are needed to accurately characterize the impact of the human body on the wireless signal propagation in BBNs.