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Improvement of GSM E-CITA localization algorithms' accuracy based on velocity estimation and further restriction of serving cell areas

IP.com Disclosure Number: IPCOM000012768D
Published in the IP.com Journal: Volume 3 Issue 6 (2003-06-25)
Included in the Prior Art Database: 2003-Jun-25
Document File: 3 page(s) / 926K

Publishing Venue

Siemens

Related People

Juergen Carstens: CONTACT

Abstract

There are many reasons for determining the position of mobile users in GSM networks, e.g. intercellular traffic distribution, location dependent services and emergency calls. A key factor for the success of any localization technology is its accuracy. Within the network based solutions, which means that the mobile equipment remains unchanged, one can determine the following methods: At first there is the method of using the plain Cell ID (CI), which just returns the weighted center of the serving cell as a position estimate. Cell ID plus Timing Advance (CI + TA) based methods also take into account an estimate of the mobile's distance to the Base Transceiver Station (BTS) but not the direction. Last there is the Enhanced Cell ID Timing Advance (E-CITA) method which also uses the signal strength RXLEV (Reception Level). For estimating the position of a Mobile Station (MS) using E-CITA every cell is divided into small squares called pixels (e.g. 5x5 m or 25x25 m) and must have a so-called prediction file associated with it that contains the predicted field strength or predicted path loss for every position (pixel) inside the cell. Beside the field strength of the serving cell the algorithm also relies on the predicted field strength of max. 6 out of up to 32 neighboring cells, so the predicted field strength of these cells are also needed for every pixel in the serving cell. An RF (Radio Frequency) planning tool calculates these values.

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Improvement of GSM E-CITA localization algorithms' accuracy based on velocity estimation and further restriction of serving cell areas

Idea: Mario Palma-Serrano, DE-Muenchen

There are many reasons for determining the position of mobile users in GSM networks, e.g. intercellular traffic distribution, location dependent services and emergency calls. A key factor for the success of any localization technology is its accuracy.

Within the network based solutions, which means that the mobile equipment remains unchanged, one can determine the following methods: At first there is the method of using the plain Cell ID (CI), which just returns the weighted center of the serving cell as a position estimate. Cell ID plus Timing Advance (CI + TA) based methods also take into account an estimate of the mobile's distance to the Base Transceiver Station (BTS) but not the direction. Last there is the Enhanced Cell ID Timing Advance (E- CITA) method which also uses the signal strength RXLEV (Reception Level).

For estimating the position of a Mobile Station (MS) using E-CITA every cell is divided into small squares called pixels (e.g. 5x5 m or 25x25 m) and must have a so-called prediction file associated with it that contains the predicted field strength or predicted path loss for every position (pixel) inside the cell. Beside the field strength of the serving cell the algorithm also relies on the predicted field strength of max. 6 out of up to 32 neighboring cells, so the predicted field strength of these cells are also needed for every pixel in the serving cell. An RF (Radio Frequency) planning tool calculates these values.

The Timing Advance and RXLEV values of the serving cell and up to six different cells are included in the measurement reports sent by the mobile device. The E-CITA algorithms then map these reports onto the pixel that matches best with the pre-calculated prediction data after reducing the search area by means the of CI and TA.

Field trials in the USA showed that most emergency calls come from suburban and rural areas where the current E-CITA algorithms perform worst. The following suggestion especially increases the accuracy of E-CITA for rural and suburban areas, where most emergency calls are made from a car, by taking into the account a velocity estimation of the mobile station. If the velocity exceeds a certain threshold (for example 20 km/h) we can determine that the measurement reports have been generated from a moving car. This gives us additional information to reduce the search area as only positions around roads and highw...