Increasing the reliability of wireless body area networks based on compressed sensing theory

Abstract

A Wireless Body Area network (WBAN) is a special purpose of Wireless Sensor Networks (WSNs) to connect various Biomedical Wireless Sensors (BWSs) located inside and outside of the human body to collect and transmit vital signals. The collected biomedical data send out via Gate Way (GW) to external databases at the hospitals and medical centers for diagnostic and therapeutic purposes. To increase the reliability of WBANs the power consumption and sampling-rate should be minimized in the Multipath Fading Channels (MFCs) between BWSs and GW. That is why an improving of MFCs as well as a low sampling-rate channel model is inevitably required for WBANs to expand WBANs to important applications such as Electronic Health (EH) and Mobile Health (MH). With this in mind, Compressed Sensing (CS) theory, as a new sampling procedure, is employed to MFCs in order to minimize power consumption and sampling-rate. The MFCs and the collaboration from an important platform for CS theory in order to provide lowpower and low sampling-rate WBANs expected to increase a lot in the future. Advance WBANs with MFCs based on CS theory will be able to deliver healthcare not only to patients in hospital and medical centers; but also in their homes and workplaces thus offering cost saving, and improving the quality of life. The simulation results confirm that detection probability of biomedical signals at GW increases by 25%, which will result in an increment in the received signal amplitude at GW. Our simulation results also illustrate that satisfying quality for Bit Error Rate (BER) can be achieved with CS.