Use of a Simplified Maximum Likelihood Function in a WLAN-Based Location Estimation

Abstract

In a location estimation with the received signal strength indication (RSSI) of a wireless signal in an area, the maximum likelihood (ML) function should match the real statistical property of the RSSI in the area. For a wireless local area network (WLAN)-based RSSI location estimation with a wideband signal in an office environment, the wideband signal experiences frequency selectively Rayleigh fading, so a complicated ML function containing several channel parameters needs to be derived in the environment. This paper shows that a simplified ML function containing only two channel parameters, which is optimum for a narrowband signal, is also applicable to an IEEE 802.11 g WLAN-based location estimation with a wideband signal. Computer simulation and experimental results show that the use of the simplified ML function introduces almost no degradation in the location estimation performance in typical office environments, as compared with the use of an exact ML function.