Methods and systems for admission control and resource availability prediction considering user equipment (UE) mobility

• US 10,159,022 B2
• Filed: 07/12/2016
• Issued: 12/18/2018
• Est. Priority Date: 12/13/2012
• Status: Active Grant

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Inventors: Senarath, Nimal Gamini, Cheng, Ho Ting, Zhang, Hang, Stephenne, Alex
• Primary Examiner(s): Patel, Chandrahas B
• Application Number:
  US15/208,471
• Publication Number:
  US 20160366623A1
• Time in Patent Office: 889 Days
• CPC Class Codes: H04W 36/0072 of resource information of target access point
• CPC Class Codes: H04W 36/00835 Determination of neighbour cell lists

Abstract

Predicting mobile station migration between geographical locations of a wireless network can be achieved using a migration probability database. The database can be generated based on statistical information relating to the wireless network, such as historical migration patterns and associated mobility information (e.g., velocities, bin location, etc.). The migration probability database consolidates the statistical information into mobility prediction functions for estimating migration probabilities/trajectories based on dynamically reported mobility parameters. By example, mobility prediction functions can compute a likelihood that a mobile station will migrate between geographic regions based on a velocity of the mobile station. Accurate mobility prediction may improve resource provisioning efficiency during admission control and path selection, and can also be used to dynamically adjust handover margins.

Claims

1. A method comprising:

receiving, by a radio access network (RAN) device, a migration probability table from a network component in a core network, the migration probability table specifying probabilities that mobile stations having certain mobility parameters will migrate from a first bin to a second bin of multiple bins served by an access point over one or more fixed time periods, the probabilities determined based on gathered bin-based statistical information for the access point;

for each mobile station currently located in one of the multiple bins served by the access point;

obtaining at least one current mobility parameter for the each mobile station;

estimating migration probability information for the each mobile station based on the at least one current mobility parameter for the each mobile station and the migration probability table;

estimating, by the RAN device, an aggregate network resource usage of the access point during a future period based on the estimated migration probability information of all the mobile stations currently located in one of multiple bins served by the access point; and

admitting one or more new user sessions to the access point based on the estimated aggregate network resource usage.

2. The method of claim 1, wherein the aggregate network resource usage is estimated based on the migration probability information comprising an access point assignment probability for each bin.

3. The method of claim 1, wherein the aggregate network resource usage is estimated based on the migration probability information and a resource usage for each bin as a function of neighbor access point load.

4. The method of claim 3, wherein the resource usage from each access point for a given bin of the multiple bins is obtained based on the migration probability table.

5. The method of claim 1, wherein the mobility parameters of the each mobile station comprise a specified velocity for the each mobile station, and wherein the migration probability information indicates a probability that the each mobile station will migrate from the first bin and the second bin of the multiple bins served by the access point before an end of the future period.

6. The method of claim 1, wherein the estimating comprises:

determining an expected resource usage of the aggregate network resource usage according to a current user distribution.

7. The method of claim 1, wherein the admitting comprises:

admitting the one or more new user sessions to the access point when an estimated amount of available resources of the access point exceeds the estimated aggregate network resource usage of the access point during a future period by more than a threshold;

or

rejecting the one or more new user sessions to the access point when the estimated amount of available resources of the access point does not exceed the estimated aggregate network resource usage of the access point during the future period by more than the threshold.

8. The method of claim 1, wherein the migration probability information specifies a user profile of the each mobile station, and wherein the user profile indicates historical migration information that is unique to the each mobile station.

9. The method of claim 1, wherein the aggregate network resource usage is estimated based on the migration probability information related to mobile stations in the access point and adjacent access points and a current network load.

10. The method of claim 1, wherein the migration probability information for the each mobile station comprising access assignment probability that each mobile station served by the access point under a particular loading condition of the access point.

11. The method of claim 10, wherein the access assignment probability is based on the mobility parameters of the each mobile station served by the access point, the access assignment probability being gathered during a previous period.

12. A radio access network (RAN) device comprising:

a processor; and

a non-transitory computer readable storage medium storing programming for execution by the processor, the programming including instructions to;

receive a migration probability table from a network component in a core network, the migration probability table specifying probabilities that mobile stations having certain mobility parameters will migrate from a first bin to a second bin of multiple bins served by an access point over one or more fixed time periods, the probabilities determined based on gathered bin-based statistical information for the access point;

for each mobile station currently located in one bin of the multiple bins severed by the access point;

obtain at least one current mobility parameter for the each mobile station;

estimate migration probability information for the each mobile station based on the at least one current mobility parameter for the each mobile station and the migration probability table;

estimate an aggregate network resource usage of the access point during a future period based on the estimated migration information of all the mobile stations currently located in one of the multiple bins served by the access point; and

admit one or more new user sessions based on the estimated aggregate network resource usage.

13. The RAN device of claim 12, wherein the mobility parameters of the each mobile station comprise a specified velocity for the each mobile station, and wherein the migration probability information indicates a probability that the each mobile station will migrate from the first bin to the second bin of the multiple bins served by the access point before an end of the future period.

14. The RAN device of claim 12, wherein the instructions to estimate the aggregate network resource usage in the multiple bins include instructions to:

determine an expected resource usage of the aggregate network resource usage according to a current user distribution.

15. The RAN device of claim 12, wherein the instructions to admit new user sessions to the access point based on the aggregate network resource usage includes instructions to:

admit the one or more new user sessions to the access point when an estimated amount of available resources of the access point exceeds the estimated aggregate network resource usage of the access point during the future period by more than a threshold;

or

reject the one or more new user sessions to the access point when the estimated amount of available resources of the access point does not exceed the estimated aggregate network resource usage of the access point during the future period by more than the threshold.

16. The RAN device of claim 12, wherein the migration probability information specifies a user profile of the each mobile station, and wherein the user profile indicates historical migration information that is unique to the each mobile station.

17. The RAN device of claim 12, wherein the aggregate network resource usage is estimated based on the migration probability information comprising an access point assignment probability for each bin.

18. The RAN device of claim 12, wherein the aggregate network resource usage is estimated based on the migration probability information and a resource usage for each bin as a function of neighbor access point load.

19. The RAN device of claim 12, wherein the aggregate network resource usage is estimated based on the migration probability information related to mobile stations in the access point and adjacent access points and a current network load.

20. A computer program product configured for implementation in a radio access network (RAN) device, the computer program product comprising a non-transitory computer readable storage medium storing programming, the programming including instructions to:

receive a migration probability table from a network component in a core network, the migration probability table specifying probabilities that mobile stations having certain mobility parameters will migrate from a first bin to a second bin of multiple bins served by an access point over one or more fixed time periods, the probabilities determined based on gathered bin-based statistical information for the access point;

for each mobile station currently located in one bin of the multiple bins served by the access point;

obtain at least one current mobility parameter for the each mobile station;

estimate migration probability information for the each mobile station based on the at least one current mobility parameter for the each mobile station and the migration probability table;

estimate an aggregate network resource usage of the access point during a future period based on the estimated migration information of all the mobile stations currently located in one bin of the multiple bins served by the access point; and

admit one or more new user sessions in the first bin based on the estimated aggregate network resource usage.

21. The computer program product of claim 20, wherein the aggregate network resource usage is estimated based on the migration probability information comprising assignment probability for each bin.

22. The computer program product of claim 20, wherein the aggregate network resource usage is estimated based on the migration probability information and a resource usage for each bin as a function of neighbor access point load.