Radio Propagation for Modern Wireless Systems
Radio Propagation for Modern Wireless Systems
A Statistical Modeling Approach to Location Estimation
IEEE Transactions on Mobile Computing
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
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The current paper considers the problem of Received Signal Strength (RSS) based Mobile Terminal (MT) positioning in cellular mobile networks like GSM and provides a set of MT-Base Station (BS) distance statistical estimators which improve positioning accuracy. The impact of both MT-BS distance estimation error (based on typical empirical path-loss models, i.e., Hata, Cost231) and trilateration to the MT position estimation accuracy is analyzed. The proposed set of MT-BS distance estimators improves the positioning accuracy by a factor of up to ~50% according to an ideal simulation model. However, even with this improvement, RSS based positioning still provides accuracy similar to plain Cell Global Identity (CGI) technique. The paper then considers techniques which rely on a time-series of RSS measurements (i.e., Statistical Terminal Assisted Mobile Positioning (STAMP) [1] and MT tracking [2]) indicating that the proposed estimators can improve their performance too. To obtain a realistic picture, GSM field measurements are also analyzed indicating that the proposed estimators indeed deliver MT positioning accuracy improvement however, at a lower degree vs. the one theoretically expected.