Predictive spectral allocation in mobile networks
First Claim
1. A method to analyze sub-carrier allocation data to categorize clusters for predictive spectral allocation in a wireless network, the method comprising:
- receiving information on device location, time slots, at least one sub-carrier allotted for each time slot, and quality indicators from a plurality of mobile devices;
grouping the time slots to form analysis intervals;
dynamically adjusting a length of the analysis intervals based on an expected population change within a geographic area that encompasses the plurality of mobile devices;
identifying a time-frequency vector for each analysis interval, wherein the time-frequency vector associates the analysis interval with the device location;
computing a goodness indicator for each time-frequency vector;
identifying clusters of time-frequency vectors; and
categorizing the clusters of time-frequency vectors into two or more categories.
2 Assignments
0 Petitions
Accused Products
Abstract
Technologies are generally described for discerning patterns in the “goodness” or “badness” of time-frequency slots to allow predictive allocation of spectral resources that may be appropriate for a wireless user. According to some examples, information on device location, time slots, sub-carrier(s) allotted for each time slot, and quality indicators may be received from mobile devices. The time slots may be grouped by location to form analysis intervals. A time-frequency vector may then be identified for each analysis interval and a unit of geographic grid. A “goodness” indicator may be computed for each time-frequency vector. Clusters of time-frequency vectors may be categorized for each analysis interval and associated unit of geographic grid such that mobile devices can be assigned “good” clusters through sub-carrier allocation.
-
Citations
21 Claims
-
1. A method to analyze sub-carrier allocation data to categorize clusters for predictive spectral allocation in a wireless network, the method comprising:
-
receiving information on device location, time slots, at least one sub-carrier allotted for each time slot, and quality indicators from a plurality of mobile devices; grouping the time slots to form analysis intervals; dynamically adjusting a length of the analysis intervals based on an expected population change within a geographic area that encompasses the plurality of mobile devices; identifying a time-frequency vector for each analysis interval, wherein the time-frequency vector associates the analysis interval with the device location; computing a goodness indicator for each time-frequency vector; identifying clusters of time-frequency vectors; and categorizing the clusters of time-frequency vectors into two or more categories. - View Dependent Claims (2, 3, 4, 5, 6, 7)
-
-
8. An analysis server to analyze sub-carrier allocation data to categorize clusters for predictive spectral allocation in a wireless network, the analysis server comprising:
-
a memory configured to store instructions; and a processor coupled to the memory, the processor configured to execute a communication application in conjunction with the stored instructions, the communication application comprising; an analysis module configured to; evaluate information on device location, time slots, at least one sub-carrier allotted for each of the time slots, and quality indicators received from a plurality of mobile devices; group the time slots by location to form analysis intervals; dynamically adjust a length of the analysis intervals based on an expected population change within a geographic area that encompasses the plurality of mobile devices; identify a time-frequency vector for each analysis interval, wherein the time-frequency vector associates the analysis interval with the device location; and compute a goodness indicator for each time-frequency vector; and a support vector machine (SVM) module configured to; identify clusters of time-frequency vectors; and categorize clusters of time-frequency vectors into two or more categories. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16)
-
-
17. A computer readable memory device with instructions stored thereon to analyze sub-carrier allocation data to categorize clusters for predictive spectral allocation in a wireless network, the instructions being executable by a computing device to perform or cause to be performed:
-
identifying information on device location, time slots, at least one sub-carrier allotted for each time slot, and quality indicators from a plurality of mobile devices; grouping the time slots to form analysis intervals; dynamically adjusting a length of the analysis intervals based on an expected population change within a geographic area that encompasses the plurality of mobile devices; identifying a time-frequency vector for each analysis interval, wherein the time-frequency vector associates the analysis interval with the device location; computing a goodness indicator for each time-frequency vector; identifying clusters of time-frequency vectors based on the computed goodness indicator for each time-frequency vector; and categorizing the clusters of time-frequency vectors into two or more categories. - View Dependent Claims (18, 19, 20, 21)
-
Specification