Locating mobile stations with statistical directional propagation model

Abstract

Recently, mobile location estimation is drawing considerable attention in the field of wireless communications.Among different mobile location estimation methods, the one which estimates the location of mobile stations with reference to the wave propagation model is drawing much attention. This approach, in principle, makes use of the most primitive property of wave propagation -signal strength, to perform location estimation. Hence this approach should be able to apply to different kinds of cellular network. We found out that in estimating mobile location with reference to signal strength, the azimuth gain of directional antenna and environmental factors can help to improve the accuracy. In this paper, we report our study of a Directional Propagation Model (DPM) which enhanced the traditional propagation model with these factors. We experimented our model with 3,703 sets of real life data collected from a major mobile phone operator of Hong Kong. Results show that the DPM models have significant improvement over other existing location methods in terms of accuracy and stability.

Detecting, Locating, and Tracking Hacker Activities within a WLAN Network

“…In previous years, our research group had done quite a number of work on mobile phone positioning and results are astounding [19][20][21][22][23][24][25][26][27][28][29][30]. Although theoretically we can use the same or similar location estimation algorithms for the mobile phone network to be applied to the WLAN, there is relatively few researches on WLAN positioning [31][32][33][34] in the literature.…”

Location management scheme with WLAN positioning algorithm for integrated wireless networks

“…The RADAR system adopts the nearest neighborhood schemes to infer the user position. Conversely, probabilistic schemes maintain signal strength distributions to establish radio map for positioning [4,16,19,21]. However, issues of additional hardware cost, low position accuracy and interoperability with other different communication systems still must be addressed.…”

“…Indoor positioning algorithms have been extensively studied in recent years [15][16][17][18][19][20]. An indoor sensor network with infrared or ultra-sound can provide the correct positioning information, while increasing the system cost [7].…”

A probabilistic approach to determine mobile station location with application in cellular networks

“…Probabilistic algorithms [15][16][17][18][19][20] treat input information about the mobile station position as spatial probability density functions and combine the probability density functions to improve the information about the mobile station's possible location. The probability density functions are combined applying continuous Bayes theorem [21].…”

“…The probability density functions are combined applying continuous Bayes theorem [21]. Special attention to probabilistic modeling of the received signal level data are given in [17][18][19][20], where the base transceiver station antenna directional properties are used to improve the propagation model. Implementation of probabilistic algorithms is analyzed in this paper.…”