Automatic WBAN area recognition using P2P signal strength in office environment

Abstract

The distance estimation between mobile devices is a fundamental issue for a lot of applications of indoor wireless body area network (WBAN). The RSSI have been used to estimate the distance based on the received signal strength from another mobile device. Theoretically, the signal strength is inversely proportional to squared distance, and there is a known radio propagation model that is used to convert the signal strength into distance. However, in real environments, it is hard to measure distance using RSSI because of noises, obstacles, and the type of antenna. Distance estimation using RSSI in real-world applications is still questionable because of inaccuracy. However, RSSI could become the most used technology of distance estimation from the cost/precision viewpoint because of low cost. Mobile devices need to recognize each other in office environment automatically. However, distance estimation using the RSSI of Bluetooth is difficult because of large deviation of RSSI value. This paper provides the experimental results of RSSI measurement between mobile devices in office environment. And it applies the Low Pass Filter (LPF) to reduce the deviation of RSSI value. This paper shows that the distance estimation to recognize WBAN area is possible clearly when Bluetooth RSSI LPF data are used.