Background and objective:
In the Wireless Body Area Network (WBAN) sensors are placed on the human body; which has various mobility patterns like seating, walking, standing and running. This mobility typically assisted with hand and leg movements on which most of the sensors are mounted. Previous studies were largely focused on simulations of WBAN mobility without focusing much on hand and leg movements. Thus for realistic studies on performance of the WBAN, it is important to consider hand and leg movements. Thus, an objective of this paper is to investigate an effect of the mobility patterns with hand movements on the throughput of the WBAN.
Method:
The IEEE 802.15.6 requirements are considered for WBAN design. The WBAN with star topology is used to connect three sensors and a hub. Three types of mobility viz. standing, walking and running with backward and forward hand movements is designed for simulation purpose. The throughput analysis is carried out with the three sets of simulations with standing, walking and running conditions with the speed of 0 m/s, 0.5 m/s and 3 m/s respectively. The data rate was increased from 250 Kb to 10000 Kb with AODV protocol. It is intended to investigate the effect of the hand movements and the mobility conditions on the throughput. Simulation results are analyzed with the aid of descriptive statistics. A comparative analysis between the simulated model and a mathematical model is also introduced to get more insight into the data.
Results:
Simulation studies showed that as the data rate is increased, throughput is also increased for all mobility conditions however, this increasing trend was discontinuous. In the standing (static) position, the throughput is found to be higher than mobility (dynamic) condition. It is found that, the throughput is better in the running condition than the walking condition. Average values of the throughput in case of the standing condition were more than that of the dynamic conditions. To validate these results, a mathematical model is created. In the mathematical model, a same trend is observed.
Conclusion:
Overall, it is concluded that the throughput is decreased due to mobility of the WBAN. It is understood that mathematical models have given more insight into the simulation data and confirmed the negative effect of the mobility conditions on throughput. In the future, it is proposed to investigate effect of interference on the designed network and compare the results.
The QoE Driven Transmission Optimization Based on Cognitive Air Interface Match for Self-Organized Wireless Body Area Network
