TECHNIQUES TO MANAGE A MOBILE DEVICE BASED ON NETWORK DENSITY

• US 20110153805A1
• Filed: 12/18/2009
• Published: 06/23/2011
• Est. Priority Date: 06/01/2009
• Status: Active Grant

• Current Assignee: Palm, Inc. (TCL Technology Group Corp.)
• Original Assignee: Palm, Inc. (TCL Technology Group Corp.)
• Inventors: Kasten, Welly, Hendin, Neil, Ngo, William, Beninghaus, James
• Granted Patent: US 9,693,390 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: H04B 17/309 Measuring or estimating channel quality parameters
• CPC Class Codes: H04B 17/382 for resource allocation, admission control or handover
• CPC Class Codes: H04W 52/346 distributing total power among users or channels
• CPC Class Codes: H05B 1/0202 Switches

Abstract

Techniques to manage a mobile device based on network density are described. An apparatus may comprise a mobile computing device having a radio module operative to receive radio signals, a resource detector operative to collect a sample for one or more wireless resources based on the received radio signals, a network density module operative to estimate a network density for an operating environment of the mobile computing device based on the sample and a probability density function, and a parameter management module operative to manage one or more operational parameters of the mobile computing device based on the estimated network density. Other embodiments are described and claimed.

Claims

1. A mobile computing device, comprising:

a radio module operative to receive radio signals;

a resource detector operative to collect a sample for one or more wireless resources based on the received radio signals;

a network density module operative to estimate a network density for an operating environment of the mobile computing device based on the sample and a probability density function; and

a parameter management module operative to manage one or more operational parameters of the mobile computing device based on the estimated network density.

2. The mobile computing device of claim 1, the probability density function to receive as input the sample, and output a probability value representing an estimated network density for the operating environment of the mobile computing device.

3. The mobile computing device of claim 1, the estimated network density comprising a density level falling within a lower network density category or a higher network density category, each category representing an amount of wireless resources located within a defined geographic area.

4. The mobile computing device of claim 1, the network density module operative to update the estimated network density according to subsequent samples using a Bayesian inference algorithm.

5. The mobile computing device of claim 1, the sample comprising a measurable characteristic of the one or more wireless resources.

6. The mobile computing device of claim 1, the sample comprising a received signal strength indication derived from the received radio signals of the one or more wireless resources.

7. The mobile computing device of claim 1, the sample comprising a number of the one or more wireless resources derived from the received radio signals of the one or more wireless resources.

8. The mobile computing device of claim 1, the parameter management module operative to modify an operational parameter comprising a network scanning threshold parameter, a radio-frequency channel parameter, an access point parameter, a rate selection parameter, a frame size parameter, an aggregation size parameter, a packet retry limit parameter, a power level parameter, a component parameter, a protocol parameter, a radio parameter, an application parameter, or an alarm parameter.

9. The mobile computing device of claim 1, comprising a location detector operative to determine a location for the mobile computing device as a current location based on location information for the mobile computing device.

10. The mobile computing device of claim 1, comprising a location detector operative to determine a location for the mobile computing device as a predicted location based on current location information, velocity information and direction information for the mobile computing device.

11. The mobile computing device of claim 1, comprising a resource database to store a resource profile having resource information for one or more wireless resources accessible from a current location or a predicted location of the mobile computing device, the resource information comprising the one or more operational parameters.

12. The mobile computing device of claim 1, comprising a thumb board, an omni-directional antenna and a touch screen display.

13. A method, comprising:

collecting a sample for one or more wireless resources;

estimating a network density for an operating environment of a mobile computing device based on the sample and a probability density function; and

managing one or more operational parameters of the mobile computing device based on the estimated network density.

14. The method of claim 13, comprising estimating the network density as a density level falling within a lower network density category or a higher network density category, each category representing an amount of wireless resources located within a defined geographic area.

15. The method of claim 13, comprising updating the estimated network density according to previous samples or subsequent samples relative to the current sample using a Bayesian inference algorithm.

16. The method of claim 13, comprising modifying an operational parameter comprising a network scanning threshold parameter, a radio-frequency channel parameter, an access point parameter, a rate selection parameter, a frame size parameter, an aggregation size parameter, a packet retry limit parameter, a power level parameter, a component parameter, a protocol parameter, a radio parameter, an application parameter, or an alarm parameter.

17. The method of claim 13, comprising storing a resource profile having resource information for one or more wireless resources accessible from a current location or a predicted location of the mobile computing device, the resource information comprising the one or more operational parameters.

18. An article of manufacture comprising a computer-readable storage medium containing instructions that when executed by a processor enable a system to:

collecting a sample for one or more wireless resources;

estimating a network density for an operating environment of a mobile computing device based on the sample and a probability density function; and

managing one or more operational parameters of the mobile computing device based on the estimated network density.

19. The article of manufacture of claim 21, further comprising instructions that when executed by the processor enable the system to estimate the network density as a density level falling within a lower network density category or a higher network density category, each category representing an amount of wireless resources located within a defined geographic area.

20. The article of manufacture of claim 21, further comprising instructions that when executed by the processor enable the system to update the estimated network density according to previous samples or subsequent samples relative to the current sample using a Bayesian inference algorithm.