Methods and apparatus for partitioning wireless network cells into time-based clusters

• US 10,003,981 B2
• Filed: 02/08/2016
• Issued: 06/19/2018
• Est. Priority Date: 11/08/2011
• Status: Active Grant

• Current Assignee: Viavi Solutions, Inc. (Lumentum Holdings Inc.)
• Original Assignee: Viavi Solutions, Inc. (Lumentum Holdings Inc.)
• Inventors: Tarraf, Osama, Ansari, Arif, Bergner, Emil
• Primary Examiner(s): Tsegaye, Saba
• Application Number:
  US15/017,721
• Publication Number:
  US 20160295425A1
• Time in Patent Office: 862 Days
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: H04W 72/12 Wireless traffic scheduling

Abstract

In some embodiments, an apparatus includes a cluster partitioning module and an optimization module. The cluster partitioning module receives a first performance indicator set for a first instance of a time period set. The cluster partitioning module defines a recurring schedule set, where each time period from the recurring schedule set is associated with a performance indicator from the first performance indicator set and within a predefined range of a performance indicator associated with the remaining time periods from the recurring schedule set. The optimization module receives a second performance indicator set for a second instance of the time period set. The optimization module defines a metric value based on the second performance indicator set, and causes a change in a network implementation based on the metric value at each time period from a third instance of the time period set and from the recurring schedule set.

Claims

1. A device comprising:

one or more processors to;

receive a first set of values for indicators indicating a performance of a plurality of network devices during a first instance of a period of time including a plurality of time periods;

determine a cluster of network devices, from among the plurality of network devices, based on the first set of values for the indicators;

determine a recurring schedule that includes a first recurring time period, of the plurality of time periods, and a second recurring time period, of the plurality of time periods;

receive a second set of values for the indicators from the plurality of network devices based on a second instance of the period of time, which includes the first recurring time period and the second recurring time period;

determine a metric value, at each of the first recurring time period and the second recurring time period, for a parameter of the cluster of network devices based on the second set of values for the indicators; and

transmit an instruction signal indicating the metric value, at each of the first recurring time period and the second recurring time period, to the cluster of network devices,

the instruction signal instructing the cluster of network devices to change an implementation of a network, at a third instance of the period of time, which includes the first recurring time period and the second recurring time period, based on the metric value for the parameter at each of the first recurring time period and the second recurring time period.

2. The device of claim 1, where the one or more processors, when receiving the first set of values, are to:

receive characteristic patterns of the indicators for the plurality of network devices; and

where the one or more processors, when determining the cluster of network devices, are to;

determine the cluster of network devices based on the characteristic patterns.

3. The device of claim 1, where, when determining the cluster of network devices, the one or more processors are to:

determine the cluster of network devices based on a particular threshold for an indicator of the indicators,

the indicator including at least one of a throughput in a unit of time, an average transmission rate, or a total quantity of dropped calls during a time period.

4. The device of claim 1, where, when determining the cluster of network devices, the one or more processors are to:

determine the cluster of the network devices based on time or date information.

5. The device of claim 1, where, when determining the cluster of network devices, the one or more processors are further to:

determine the cluster of network devices based on geographic locations of the cluster of network devices.

6. The device of claim 1, where the one or more processors, when determining the metric value, are to:

determine the metric value based on at least one of load balancing, coverage improvement, capacity optimization, interference reduction, or self healing.

7. The device of claim 1, where the first recurring time period and the second recurring time period are each associated with the indicators.

8. A non-transitory computer-readable medium storing instructions, the instructions comprising:

one or more instructions that, when executed by one or more processors, cause the one or more processors to;

receive a first set of values for indicators indicating a performance of a plurality of network devices during a first instance of a period of time including a plurality of time periods;

determine a cluster of network devices, from among the plurality of network devices, based on the first set of values for the indicators;

determine a recurring schedule that includes a first recurring time period, of the plurality of time periods, and a second recurring time period, of the plurality of time periods;

receive a second set of values for the indicators from the plurality of network devices based on a second instance of the period of time, which includes the first recurring time period and the second recurring time period;

determine a metric value, at each of the first recurring time period and the second recurring time period, for a parameter of the cluster of network devices based on the second set of values for the indicators; and

provide an instruction signal indicating the metric value, at each of the first recurring time period and the second recurring time period, to the cluster of network devices,

the instruction signal instructing the cluster of network devices to change an implementation of a network, at a third instance of the period of time, which includes the first recurring time period and the second recurring time period, based on the metric value for the parameter at each of the first recurring time period and the second recurring time period.

9. The non-transitory computer-readable medium of claim 8, where the one or more instructions, when determining the cluster of network devices, cause the one or more processors to:

determine the cluster of network devices based on a particular threshold for an indicator of the indicators,

the indicator including at least one of a throughput in a unit of time, an average transmission rate, or a total quantity of dropped calls during a time period.

10. The non-transitory computer-readable medium of claim 8, where the one or more instructions, when determining the cluster of network devices, cause the one or more processors to:

determine the cluster of network devices based on at least one of morphological areas or population density.

11. The non-transitory computer-readable medium of claim 8, where the one or more instructions, when determining the cluster of network devices, cause the one or more processors to:

determine the cluster of network devices based on geographic locations of the cluster of network devices.

12. The non-transitory computer-readable medium of claim 8, where the one or more instructions, when determining the metric value, cause the one or more processors to:

determine a set of particular parameter settings for the cluster of network devices.

13. The non-transitory computer-readable medium of claim 8, where the one or more instructions, when determining the metric value, cause the one or more processors to:

determine the metric value based on at least one of load balancing, coverage improvement, capacity optimization, interference reduction, or self healing.

14. The non-transitory computer-readable medium of claim 8, where the parameter is a tilt of an antenna of a network device of the cluster of network devices.

15. A method comprising:

receiving, by a device, a first set of values for indicators indicating a performance of a plurality of network devices during a first instance of a period of time including a plurality of time periods;

determining, by the device, a cluster of network devices, from among the plurality of network devices, based on the first set of values for the indicators;

determining, by the device, a recurring schedule that includes a first recurring time period, of the plurality of time periods, and a second recurring time period of the plurality of time periods;

monitoring, by the device, a second set of values for the indicators from the plurality of network devices based on a second instance of the period of time, which includes the first recurring time period and the second recurring time period;

determining, by the device, a metric value, at each of the first recurring time period and the second recurring time period, for a parameter of the cluster of network devices based on the second set of values for the indicators; and

transmitting, by the device, an instruction signal indicating the metric value, at each of the first recurring time period and the second recurring time period,to the cluster of network devices,

the instruction signal instructing the cluster of network devices to change an implementation of a network, at a third instance of the period of time, which includes the first recurring time period and the second recurring time period, based on the metric value for the parameter at each of the first recurring time period and the second recurring time period.

16. The method of claim 15, where receiving the first set of values comprises:

receiving characteristic patterns of the indicators for the plurality of network devices; and

where determining the cluster of network devices includes;

determining the cluster of network devices based on the characteristic patterns.

17. The method of claim 15, where determining the cluster of network devices comprises:

determining the cluster of network devices based on a time or date information.

18. The method of claim 15, where determining the cluster of network devices comprises:

determining the cluster of network devices based on at least one of morphological areas or population density.

19. The method of claim 15, where determining the metric value comprises:

determining a set of particular parameter settings for the cluster of network devices.

20. The method of claim 15, where the parameter is a tilt of an antenna of a network device of the cluster of network devices.