Mobile location method for WLAN-type systems

• US 20070133487A1
• Filed: 12/12/2005
• Published: 06/14/2007
• Est. Priority Date: 12/12/2005
• Status: Active Grant

• Current Assignee: Nokia Corporation
• Original Assignee: Nokia Corporation
• Inventors: Wang, Shu-Shaw, Green, Marilynn
• Granted Patent: US 7,664,511 B2
• Time in Patent Office: Days
• US Class Current: 370/338
• CPC Class Codes: G01S 5/02524 Creating or updating the radio-map
• CPC Class Codes: H04W 16/225 for indoor or short range network
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

The present invention provides a new and unique method and apparatus for providing an estimate of a mobile location of a wireless node, point or terminal in a wireless local area network (WLAN) or other suitable network, the estimate being based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map. The signal strength database or radio map is built using a signal strength fingerprint algorithm. The signal strength fingerprint algorithm includes selecting and measuring a set of grid points in the wireless local area network (WLAN) or other suitable network.

Claims

1. A method for providing an estimate of a mobile location of a wireless node, point or terminal in a wireless local area network (WLAN) or other suitable network, characterized in that

the estimate is based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map.

2. A method according to claim 1, wherein the signal strength database or radio map is built using a signal strength fingerprint algorithm.

3. A method according to claim 2, wherein the signal strength fingerprint algorithm includes selecting and measuring a set of grid points in the wireless local area network (WLAN) or other suitable network.

4. A method according to claim 2, wherein the signal fingerprint algorithm includes using linear regression parameters to estimate mobile received signal strengths at each assigned grid point.

5. A method according to claim 2, wherein the signal fingerprint algorithm includes recording grid positions and signal strength measurements.

6. A method according to claim 5, wherein the data structure entry for each grid point is defined as

$R_i=\{\begin{array}{c}P\end{array}$

( x i , y i , z i ) SS i , j } ,

where i represents an identification number (ID) for each grid point, R_i is the estimated received information at the i-th grid point, P(x_i, y_i, z_i) is the physical location of the i-th grid point, and SS_i,j is the average received signal strengths from the j-th AP'"'"'s transmission at the i-th grid point.

7. A method according to claim 2, wherein the signal strength fingerprint algorithm includes one or more of the following steps:

placing access points (APs) in the wireless local area network (WLAN) or other suitable network and recording their coordinates;

taking signal strengths measurements in areas of interest in the wireless local area network (WLAN) or other suitable network;

applying a linear regression method to estimate propagation channels;

estimating propagation channels at each grid point; and

/or

processing the results to form the signal strength database or radio map.

8. A method according to claim 7, wherein, in response to request from the wireless node, point or terminal, a gradient search is used to determine the estimate.

9. A method according to claim 1, wherein the grid point includes an access point (AP) in the wireless local area network (WLAN) or other suitable network.

10. A method according to claim 1, wherein the wireless node, point or terminal may include a station (STA), as well as user equipment (UE) such as a mobile terminal, phone, laptop computer, personal digital assistant, etc.

30. A network node, point or element according to claim 1, wherein the wireless node, point or terminal is a station (STA) or other suitable user equipment (UE) such as a mobile terminal, a mobile phone, a laptop computer, a personal digital assistant, etc.

32. A method according to claim 1, wherein the method further comprises implementing the step of the method via a computer program running in a processor, controller or other suitable module in one or more network nodes, points, terminals or elements in the wireless local area network (WLAN) or other suitable network.

11. A wireless local area network (WLAN) or other suitable network having a network node, point or element with a module for providing an estimate of a mobile location of a wireless node, point or terminal therein, characterized in that

the estimate is based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map.

12. A wireless local area network (WLAN) or other suitable network according to claim 11, wherein the signal strength database or radio map is built using a signal strength fingerprint algorithm.

13. A wireless local area network (WLAN) or other suitable network according to claim 12, wherein the signal strength fingerprint algorithm includes selecting and measuring a set of grid points in the wireless local area network (WLAN) or other suitable network.

14. A wireless local area network (WLAN) or other suitable network according to claim 12, wherein the signal fingerprint algorithm includes using linear regression parameters to estimate mobile received signal strengths at each assigned grid point.

15. A wireless local area network (WLAN) or other suitable network according to claim 12, wherein the signal fingerprint algorithm includes recording grid positions and signal strength measurements.

16. A wireless local area network (WLAN) or other suitable network according to claim 15, wherein the data structure entry for each grid point is defined as

$R_i=\{\begin{array}{c}P\end{array}$

( x i , y i , z i ) SS i , j } ,

where i represents an identification number (ID) for each grid point, R_i is the estimated received information at the i-th grid point, P(x_i, y_i, z_i) is the physical location of the i-th grid point, and SS_i,j is the average received signal strengths from the j-th AP'"'"'s transmission at the i-th grid point.

17. A wireless local area network (WLAN) or other suitable network according to claim 11, wherein the signal strength fingerprint algorithm includes one or more of the following steps:

placing access points (APs) in the wireless local area network (WLAN) or other suitable network and recording their coordinates;

taking signal strengths measurements in areas of interest in the wireless local area network (WLAN) or other suitable network;

applying a linear regression method to estimate propagation channels;

estimating propagation channels at each grid point; and

/or

processing the results to form the signal strength database or radio map.

18. A wireless local area network (WLAN) or other suitable network according to claim 17, wherein, in response to a request from the wireless node, point or terminal, a gradient search is used to determine the estimate.

19. A wireless local area network (WLAN) or other suitable network according to claim 11, wherein the grid point includes an access point (AP) in the wireless local area network (WLAN) or other suitable network.

20. A wireless local area network (WLAN) or other suitable network according to claim 11, wherein the wireless node, point or terminal includes a station (STA), as well as user equipment (UE) such as a mobile terminal, phone, laptop computer, personal digital assistant, etc.

21. A network node, point or element for operating in a wireless local area network (WLAN) or other suitable network, the network node, point or element having a module for providing an estimate of a mobile location of a wireless node, point or terminal in the wireless local area network (WLAN) or other suitable network, characterized in that

the estimate is based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map.

22. A network node, point or element according to claim 21, wherein the signal strength database or radio map is built using a signal strength fingerprint algorithm.

23. A network node, point or element according to claim 22, wherein the signal strength fingerprint algorithm includes selecting and measuring a set of grid points in the wireless local area network (WLAN) or other suitable network.

24. A network node, point or element according to claim 22, wherein the signal fingerprint algorithm includes using linear regression parameters to estimate mobile received signal strengths at each assigned grid point.

25. A network node, point or element according to claim 22, wherein the signal fingerprint algorithm includes recording grid positions and signal strength measurements.

26. A network node, point or element according to claim 23, wherein the data structure entry for each grid point is defined as

$R_i=\{\begin{array}{c}P\end{array}$

( x i , y i , z i ) SS i , j } ,

where i represents an identification number (ID) for each grid point, R_i is the estimated received information at the i-th grid point, P(x_i, y_i, z_i) is the physical location of the i-th grid point, and SS_i,j is the average received signal strengths from the j-th AP'"'"'s transmission at the i-th grid point.

27. A network node, point or element according to claim 22, wherein the signal strength fingerprint algorithm includes one or more of the following steps:

placing access points (APs) in the wireless local area network (WLAN) or other suitable network and recording their coordinates;

taking signal strengths measurements in areas of interest in the wireless local area network (WLAN) or other suitable network;

applying a linear regression method to estimate propagation channels;

estimating propagation channels at each grid point; and

/or

processing the results to form the signal strength database or radio map.

28. A network node, point or element according to claim 27, wherein, in response to a request from the node, point or terminal, a gradient search is used to determine the estimate.

29. A network node, point or element according to claim 21, wherein the network node, point or element is an access point (AP) or other suitable grid point in the wireless local area network (WLAN) or other suitable network.

31. A computer program product with a program code, which program code is stored on a machine readable carrier, for carrying out the steps of a method comprising one or more steps for providing an estimate of a mobile location of a wireless node, point or terminal in a wireless local area network (WLAN) or other suitable network, the estimate being based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map, when the computer program is run in a module of either a node, point or terminal, such as an Access Point (AP) or other suitable grid point, in the wireless local area network (WLAN) or other suitable network.

33. A method for building a database using a signal strength fingerprint algorithm for use in providing an estimate of a mobile location of a wireless node, point or terminal in a wireless local area network (WLAN) or other suitable network arranged in a geographic location, the method comprising the following steps:

placing access points (APs) or other suitable grid points in the wireless local area network (WLAN) or other suitable network and recording their coordinates in the geographic location;

taking signal strengths measurements in areas of interest in the wireless local area network (WLAN) or other suitable network;

applying a linear regression method to estimate propagation channels;

estimating propagation channels at each access or other suitable grid point; and

/or

processing the results to form the signal strength database or radio map.

34. A method according to claim 33, wherein the data structure entry for each grid point is defined as

$R_i=\{\begin{array}{c}P\end{array}$

( x i , y i , z i ) SS i , j } ,

where i represents an identification number (ID) for each grid point, R_i is the estimated received information at the i-th grid point, P(x_i, y_i, z_i) is the physical location of the i-th grid point, and SS_i,j is the average received signal strengths from the j-th AP'"'"'s transmission at the i-th grid point.

35. A method according to claim 33, wherein the estimate is based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map.