Joseph Lyles

US Patent:

8611302, Dec 17, 2013

Filed:

Oct 31, 2007

Appl. No.:

11/982004

Inventors:

Eric Van Den Berg - Hoboken NJ, US
Joseph Bryan Lyles - Bedminster NJ, US
Praveen Gopalakrishnan - Hillsboro OR, US
Byungsuk Kim - Kyunggi-do, KR

Assignee:

TTI Inventions A LLC - Wilmington DE

International Classification:

H04W 4/00

US Classification:

370331, 370328

Abstract:

A method for determining whether to perform vertical handoff between multiple network. The method comprises obtaining a plurality of selection metrics for each network, calculating, for each of the other communication networks, a predicted utility value from at least the corresponding plurality of selection metrics using a variable kernel regression function, obtaining, for the current communication network, a second plurality of selection metrics; calculating a second predicted utility value for the current communication network from at least the corresponding second plurality of selection metrics using a second variable kernel regression function, comparing each of the predicted utility values for each of the plurality of other communication networks with the second predicted utility value and switching to one of the other communication networks having the highest predicted utility value, if the highest predicted utility value is greater than the second predicted utility value.

US Patent:

20140098794, Apr 10, 2014

Filed:

Dec 11, 2013

Appl. No.:

14/102782

Inventors:

- Wilmington DE, US
Joseph Bryan Lyles - Bedminster NJ, US
Praveen Gopalakrishnan - Hillsboro OR, US
Byunsuk Kim - Kyunggi-do, KR

Assignee:

TTI Inventions A LLC - Wilmington DE

International Classification:

H04W 36/30

US Classification:

370332

Abstract:

A method for determining whether to perform vertical handoff between multiple network. The method comprises obtaining a plurality of selection metrics for each network, calculating, for each of the other communication networks, a predicted utility value from at least the corresponding plurality of selection metrics using a variable kernel regression function, obtaining, for the current communication network, a second plurality of selection metrics; calculating a second predicted utility value for the current communication network from at least the corresponding second plurality of selection metrics using a second variable kernel regression function, comparing each of the predicted utility values for each of the plurality of other communication networks with the second predicted utility value and switching to one of the other communication networks having the highest predicted utility value, if the highest predicted utility value is greater than the second predicted utility value.