Detecting incorrectly placed access points

• US 9,310,463 B2
• Filed: 11/06/2013
• Issued: 04/12/2016
• Est. Priority Date: 11/06/2013
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Pandey, Santosh Ghanshyam
• Primary Examiner(s): Demeter, Hilina K
• Application Number:
  US14/072,851
• Publication Number:
  US 20150126215A1
• Time in Patent Office: 888 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G01S 5/021 Calibration, monitoring or correction G01S5/0252 takes precedence
• CPC Class Codes: G01S 5/0242 Determining the position of transmitters to be subsequently used in positioning G01S5/0289 takes precedence
• CPC Class Codes: H04W 64/003 locating network equipment

Abstract

Embodiments provide techniques for detecting access points on a position map, particularly incorrectly placed access points. For each access point in a plurality of access points, a subset of the plurality of access points that neighbor the access point are identified. Embodiments estimate a location of the access point, based on a respective indication of signal strength from each neighboring access point in the subset of access points and a respective position of each of the neighboring access points in position map. A difference between a recorded position of the access point in the position map and the estimated location of the access point is calculated. Embodiments then determine that the position within the position map for a first one of the plurality of access points is incorrect, based on the determined difference for the first access point.

Claims

1. A method, comprising:

generating, by operation of one or more computer processors, a set of signal strength and distance data, comprising, for each access point in a plurality of access points;

identifying a subset of the plurality of access points that neighbor the access point;

collecting indications of signal strength for each of the access points in the subset, relative to the access point;

calculate a distance between the access point and each of the access points in the subset, based on a position map;

generating a line of best fit to the set of signal strength and distance data for each of the plurality of access points;

determining a likelihood value for each of the plurality of access points,

by determining a respective average negative log likelihood value based on the line of best fit, the indications of signal strength and the calculated distance for the access point; and

determining the position within the position map for a first one of the plurality of access points is likely to be incorrect, by selecting an access point having the greatest average negative log likelihood value based on the determined likelihood values for each of the plurality of access points.

2. The method of claim 1, wherein generating the line of best fit to the set of signal strength and distance data further comprises:

fitting a path loss model to the set of signal strength and distance data.

3. The method of claim 1, further comprising:

excluding all indications of signal strength and distance information relating to neighbors of the access point from the set of signal strength and distance data,

wherein generating the line of best fit to the set of signal strength and distance data for each of the plurality of access points is based on the set of signal strength and distance data with the neighboring information excluded.

4. The method of claim 1, wherein the indication of signal strength comprises at least one of a received signal strength indication (RSSI) measure, a time of arrival measurement, a one way transit time measurement and a round trip time measurement.

5. The method of claim 4 wherein collecting indications of signal strength for each of the access points in the subset, relative to the access point, comprises:

collecting indications of signal strength across multiple different signal bands.

6. The method of claim 1, wherein the position map specifies a respective position for each of the plurality of access points within a physical environment.

7. The method of claim 6, wherein the position is specified using coordinates specifying a position within the physical environment.

8. The method of claim 1, further comprising:

upon determining the position within the position map for the first access point is likely to be incorrect, generating a notification specifying at least the first access point.

9. A method, comprising:

receiving a position map specifying a respective position for each of a plurality of access points within a physical environment;

collecting indications of signal strength from each of the plurality of access points; and

analyzing, by operation of one or more computer processors, the indications of signal strength and the position map to determine that a position of a first one of the plurality of access points within the position map is likely to be incorrect, in that the position of the first access point within the position map does not correspond to a position of the first access point within the physical environment, comprising;

plotting a line of best fit using a path loss model;

determining a likelihood value for each of the plurality of access points, by determining a respective average negative log likelihood value based on the line of best fit and the indication of signal strength and a calculated distance for the access point; and

selecting an access point having the greatest average negative log likelihood value.

10. The method of claim 9, further comprising:

upon determining that the position within the position map for the first access point is likely to be incorrect, generating a notification specifying at least the first access point.

11. The method of claim 9, where analyzing the indications of signal strength and the position map to determine that the position of the first one of the plurality of access points within the position map is likely to be incorrect, further comprises:

upon determining the likelihood value for each of the plurality of access points, determining that the position of the first access point within the position map is likely to be incorrect based on a determination that the corresponding likelihood value for the first access point exceeds a predefined threshold amount of likelihood.

12. A non-transitory computer-readable medium containing computer program code that, when executed by operation of one or more computer processors, performs an operation comprising:

generating a set of signal strength and distance data, comprising, for each access point in a plurality of access points;

identifying a subset of the plurality of access points that neighbor the access point;

collecting indications of signal strength for each of the access points in the subset, relative to the access point;

calculate a distance between the access point and each of the access points in the subset, based on a position map;

generating a line of best fit to the set of signal strength and distance data for each of the plurality of access points;

determining a likelihood value for each of the plurality of access points, by determining a respective average negative log likelihood value based on the line of best fit, the indications of signal strength and the calculated distance for the access point; and

determining the position within the position map for a first one of the plurality of access points is likely to be incorrect, by selecting an access point having the greatest average negative log likelihood value based on the determined likelihood values for each of the plurality of access points.

13. The non-transitory computer-readable medium of claim 12, wherein generating the line of best fit to the set of signal strength and distance data further comprises:

fitting a path loss model to the set of signal strength and distance data.

14. The non-transitory computer-readable medium of claim 12, the operation further comprising:

excluding all indications of signal strength and distance information relating to neighbors of the access point from the set of signal strength and distance data,

wherein generating the line of best fit to the set of signal strength and distance data for each of the plurality of access points is based on the set of signal strength and distance data with the neighboring information excluded.

15. The non-transitory computer-readable medium of claim 12, wherein the indication of signal strength comprises at least one of a received signal strength indication (RSSI) measure, a time of arrival measurement, a one way transit time measurement and a round trip time measurement.

16. The non-transitory computer-readable medium of claim 15, wherein collecting indications of signal strength for each of the access points in the subset, relative to the access point, comprises:

collecting indications of signal strength across multiple different signal bands.

17. The non-transitory computer-readable medium of claim 12, wherein the position map specifies a respective position for each of the plurality of access points within a physical environment.