Specific velocity estimation of wireless network devices

• US 9,883,347 B2
• Filed: 12/06/2016
• Issued: 01/30/2018
• Est. Priority Date: 06/24/2015
• Status: Active Grant

• Current Assignee: The Florida International University Board of Trustees (State University System of Florida)
• Original Assignee: The Florida International University Board of Trustees (State University System of Florida)
• Inventors: Merwaday, Arvind, Guvenc, Ismail
• Primary Examiner(s): TAYLOR, BARRY W
• Application Number:
  US15/370,213
• Publication Number:
  US 20170094472A1
• Time in Patent Office: 420 Days
• CPC Class Codes: H04W 36/00833 Handover statistics
• CPC Class Codes: H04W 36/0088 Scheduling hand-off measurements
• CPC Class Codes: H04W 36/32 by location or mobility data, e.g. speed data
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 64/006 with additional information processing, e.g. for direction or speed determination
• CPC Class Codes: H04W 72/51 based on terminal or device properties

Abstract

Techniques are disclosed for determining a specific velocity of a device attached to a wireless network. The specific velocity can be determined using a handover count of the base station boundary transitions over a time window and/or using a set of sojourn time samples that each denote the duration the device remains in the zone of a particular base station. Techniques operate effectively in cellular networks having high base station densities. The specific velocity estimates may be inputs to components on the device or network to adjust a local device function or performance behavior.

Claims

1. A method of determining the velocity of a device in a wireless network, the method comprising:

generating a handover count (H) of base station boundary transitions by the device;

receiving the handover count (H) made by the device over a predefined time window (T);

determining a specific velocity estimate based on the handover count (H), the predefined time window (T), and a base station density (λ

) as inputs to a velocity estimator; and

returning the specific velocity estimate to the device itself and a wireless network controller through a base station,

the base station density (λ

) being periodically retrieved from the wireless network, and

the velocity estimator being selected from the group consisting of a minimum variance unbiased estimator, a best linear unbiased estimator, a maximum likelihood estimator, a least squares estimator, a method of moments estimator, and a Bayesian estimator.

2. The method of claim 1, further comprising receiving the predefined time window (T) from the wireless network.

3. The method of claim 1, wherein the predefined time window (T) is from 25 seconds to 35 seconds.

4. The method of claim 1, further comprising receiving the base station density (λ

) for a particular wireless network zone, wherein the device is located in the particular wireless network zone.

5. The method of claim 1, wherein (λ

) is from 1000 to 10000 base stations per square kilometer.

6. The method of claim 1, further comprising:

receiving the specific velocity estimate at a component of the device, wherein the component modifies a local function of the device.

7. The method of claim 1, further comprising:

receiving the specific velocity estimate at the wireless network controller; and

adjusting a performance behavior of the wireless network using the specific velocity estimate.

8. The method of claim 1, wherein the wireless network comprises phantom cells.

9. A method of determining the velocity of a device in a wireless network, the method comprising:

receiving a vector T of N sojourn time samples, wherein each sojourn time sample denotes the duration the user device remains in a zone of a particular base station;

determining a specific velocity estimate based on a sojourn time by using the vector T and a base station density (λ

) as inputs to a velocity estimator; and

returning the specific velocity estimate to the device itself and a wireless network controller through a base station,

the base station density (λ

) being periodically retrieved from the wireless network, and

the velocity estimator being selected from the group consisting of a minimum variance unbiased estimator, a best linear unbiased estimator, a maximum likelihood estimator, a least squares estimator, a method of moments estimator, and a Bayesian estimator.

10. The method of claim 9, further comprising receiving the base station density (λ

) for a particular wireless network zone, wherein the device is located in the particular wireless network zone.

11. The method of claim 9, further comprising:

receiving the specific velocity estimate at a component of the device, wherein the component adjusts a local parameter of the device.

12. The method of claim 9, further comprising:

receiving the specific velocity estimate at the wireless network controller; and

adjusting a performance behavior of the wireless network using the specific velocity estimate.

13. The method of claim 9, wherein the wireless network comprises one or more of a cellular network, a heterogeneous network, and a hyper-dense network.

14. The method of claim 9, wherein the wireless network comprises phantom cells.