RSSI-based localization in cellular networks


This paper presents a novel RSSI based localization scheme that employs an existing cellular network infrastructure to perform trilateration. Traditional localization schemes employ RSSI-based radial distance estimation and trilateration algorithm. However, in a realistic scenario, the RSSI measurements are distorted due to multipath fading thus introducing error in radial distance estimation. Moreover, the selection of the best three anchor cell towers with the lowest localization error is not been explored. The proposed scheme improves localization accuracy using two, novel correcting and evaluating metrics: the Radial Distance Error Indicator (RDEI) and the Localization Error Indicator (LEI). The proposed RDEI metric is derived from the mean square error (MSE) of radial distance estimation in multipath fading channel. In the proposed method, it is employed as a correcting factor for the radial distance estimation. Next, the LEI estimate the combined localization error based on the towers positions, corresponding radial distance estimation and its error. The final position estimation improves localization accuracy as demonstrated through analytical and experimental results.

2012 IEEE 37th Conference on Local Computer Networks Workshops (LCN Workshops)