SYSTEMS AND METHODS FOR USAGE-BASED RADIO RESOURCE MANAGEMENT OF SELF-OPTIMIZING CELLS

• US 20100216477A1
• Filed: 02/22/2010
• Published: 08/26/2010
• Est. Priority Date: 02/24/2009
• Status: Active Grant

• Current Assignee: Nokia Solutions and Networks US LLC (Nokia Corporation)
• Original Assignee: Eden Rock Communications LLC (Nokia Corporation)
• Inventors: Ryan, David J.
• Granted Patent: US 8,543,121 B2
• Time in Patent Office: Days
• US Class Current: 455/449
• CPC Class Codes: H04W 16/04 Traffic adaptive resource partitioning
• CPC Class Codes: H04W 48/16 Discovering, processing access restriction or access information
• CPC Class Codes: H04W 72/0453 Resources in frequency domain, e.g. a carrier in FDMA
• CPC Class Codes: H04W 72/541 using the level of interference
• CPC Class Codes: H04W 92/20 between access points
• CPC Class Codes: Y02D 30/70 in wireless communication networks

Abstract

Systems and methods are described for allocating frequency resources based on historical usage data in a wireless communication system. A base station tracks its local usage pattern to generate a set of historical usage statistics. The base station may share those statistics with another base station node in the same network and with a server. The server may generate a frequency resource allocation plan to allocate shared resources most efficiently to various base stations based on historical usage information. Allocating frequency resources in this manner reduces the probability of cochannel interference between nearby cells and optimizes power solutions for local and regional radio access networks.

Claims

1. A networked computing system utilizing historical usage information for optimizing communications resources, comprising:

a first transceiver device;

a second transceiver device;

at least one user equipment;

a server computer; and

a data communications network facilitating data communication amongst the first transceiver device, the second transceiver device, the at least one user equipment, and the server computer,

wherein the first transceiver device is configured to;

track a local access node usage pattern to generate a first set of usage pattern metrics;

receive a frequency resource allocation plan; and

allocate at least one frequency resource based at least in part on the first set of usage pattern metrics and the frequency resource allocation plan.

2. The networked computing system of claim 1, wherein the first transceiver device is further configured to share the first set of usage pattern metrics with the second transceiver device and with the server computer.

3. The networked computing system of claim 1, wherein the server computer is configured to generate the frequency resource allocation plan based on historical usage data received from the first transceiver device and the second transceiver device.

4. The networked computing system of claim 1, wherein the first set of usage pattern metrics is selected from the group consisting of:

daily peak and mean usage times;

typical mean and peak channel data bandwidth utilization per session; and

typical mean and peak number of simultaneous active sessions.

5. The networked computing system of claim 1, wherein the frequency resource allocation plan is generated dynamically based on actual historical usage patterns of the first transceiver device and the second transceiver device.

6. The networked computing system of claim 1, wherein the first transceiver device is further configured to:

receive a second set of usage pattern metrics from the second transceiver device;

predict a probability of cochannel interference based on the first set of usage pattern metrics and the second set of usage pattern metrics; and

determine a preferred channel list based on the predicted probability.

7. The networked computing system of claim 1, wherein the first transceiver device is selected from the group of a microcell, a picocell, and a femtocell, and wherein the second transceiver device is selected from the group of a macrocell, a microcell, a picocell, and a femtocell.

8. A computer-implemented method for allocating at least one frequency resource based on historical usage data, the method comprising:

tracking a local access node usage pattern to generate a first set of usage pattern metrics at a first transceiver device in a network;

receiving a frequency resource allocation plan; and

allocating the at least one frequency resource based at least in part on the first set of usage pattern metrics and the frequency resource allocation plan.

9. The computer-implemented method of claim 8, further comprising sharing the first set of usage pattern metrics with a second transceiver device and with a server computer.

10. The computer-implemented method of claim 8, further comprising generating the frequency resource allocation plan based on historical usage data received from the first transceiver device and a second transceiver device at a server computer.

11. The computer-implemented method of claim 8, wherein the first set of usage pattern metrics is selected from the group consisting of:

daily peak and mean usage times;

typical mean and peak channel data bandwidth utilization per session; and

typical mean and peak number of simultaneous active sessions.

12. The computer-implemented method of claim 8, wherein the frequency resource allocation plan is generated dynamically based on actual historical usage patterns of the first transceiver device and a second transceiver device.

13. The computer-implemented method of claim 8, further comprising:

receiving at the first transceiver device a second set of usage pattern metrics from a second transceiver device;

predicting a probability of cochannel interference based on the first set of usage pattern metrics and the second set of usage pattern metrics; and

determining a preferred channel list based on the predicted probability.

14. A computer-readable medium comprising computer-executable instructions for allocating at least one frequency resource based on historical usage data, which when executed, performs the method comprising:

tracking a local access node usage pattern to generate a first set of usage pattern metrics at a first transceiver device in a network;

receiving a frequency resource allocation plan; and

allocating the at least one frequency resource based at least in part on the first set of usage pattern metrics and the frequency resource allocation plan.

15. The computer-readable medium of claim 14, further comprising sharing the first set of usage pattern metrics with a second transceiver device and with a server computer.

16. The computer-readable medium of claim 14, further comprising generating the frequency resource allocation plan based on historical usage data received from the first transceiver device and a second transceiver device at a server computer.

17. The computer-readable medium of claim 14, wherein the first set of usage pattern metrics is selected from the group consisting of:

daily peak and mean usage times;

typical mean and peak channel data bandwidth utilization per session; and

typical mean and peak number of simultaneous active sessions.

18. The computer-readable medium of claim 14, wherein the frequency resource allocation plan is generated dynamically based on actual historical usage patterns of the first transceiver device and a second transceiver device.

19. The computer-readable medium of claim 14, further comprising:

receiving at the first transceiver device a second set of usage pattern metrics from a second transceiver device;

predicting a probability of cochannel interference based on the first set of usage pattern metrics and the second set of usage pattern metrics; and

determining a preferred channel list based on the predicted probability.

20. A transceiver device for utilizing historical usage information for optimizing communications resources, comprising:

at least one memory;

at least one processor operatively coupled to the memory,

wherein the transceiver device is configured to;

track a local access node usage pattern to generate a first set of usage pattern metrics;

receive a frequency resource allocation plan; and

allocate at least one frequency resource based at least in part on the first set of usage pattern metrics and the frequency resource allocation plan.