Transmit opportunity detection

• US 8,787,962 B2
• Filed: 03/26/2010
• Issued: 07/22/2014
• Est. Priority Date: 03/27/2009
• Status: Active Grant

• Current Assignee: Regents of The University of Minnesota (University of Minnesota)
• Original Assignee: Regents of The University of Minnesota (University of Minnesota)
• Inventors: Kundargi, Nikhil, Tewfik, Ahmed H.
• Primary Examiner(s): GESESSE, TILAHUN
• Application Number:
  US13/260,698
• Publication Number:
  US 20120135779A1
• Time in Patent Office: 1,579 Days
• Field of Search: 455/522, 455/63.1
• US Class Current: 455/522
• CPC Class Codes: H04W 52/241 taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo
• CPC Class Codes: H04W 52/343 taking into account loading or congestion level
• CPC Class Codes: H04W 52/362 Aspects of the step size

Abstract

The present application discusses, among other things, apparatus and methods for detecting and using a excess capacity on a wireless network medium. A method embodiment includes calculating a differential metric based on a first metric and a second metric for a primary network. The primary network can have a medium shared with a secondary network. The first metric can be based on a first distribution of traffic on the primary network and can correspond to absence of a perturbation of the medium. The second metric can be based on a second distribution of traffic on the primary network and can correspond to a perturbation of the medium from a node of the secondary network. The method can include selecting a transmission power for the node based on the differential metric.

Claims

1. A method comprising:

calculating a differential metric using a processor of a node on a secondary network, the differential metric based on a first metric and a second metric for a primary network, the primary network having a medium shared with the secondary network, the first metric based on a first distribution of traffic on the primary network and corresponding to absence of a perturbation of the medium, the second metric based on a second distribution of traffic on the primary network and corresponding to a perturbation of the medium from the node; and

selecting a transmission power for the node based on the differential metric.

2. The method of claim 1, further including determining at least one of the first metric and the second metric using the processor of the node and a distributional divergence metric.

3. The method of claim 1, further including iteratively estimating the second metric using the processor of the node.

4. The method of claim 1, wherein selecting the transmission power includes determining a power level that provides a minimum signal-to-noise ratio (SNR) of a node on the primary network using the processor of the node.

5. The method of claim 4, wherein selecting a transmission power includes incrementally increasing the transmission power if the differential metric meets a threshold criteria indicative of an insubstantial divergence between the first distribution and the second distribution.

6. The method of claim 4, wherein selecting a transmission power includes reducing the transmission power if the differential metric does not meet a threshold criteria indicative of an insubstantial divergence between the first distribution and the second distribution.

7. The method of claim 1, wherein calculating the differential metric includes implementing a goodness-of-fit (GOF) test with respect to the first distribution using primary network samples corresponding to the second distribution.

8. The method of claim 7, wherein implementing the GOF test includes executing a sequential Kolmogorov-Smirnov algorithm.

9. The method of claim 8, wherein selecting a transmission power includes incrementally increasing the transmission power if the differential metric meets a threshold criteria indicative of an insubstantial divergence between the first distribution and the second distribution.

10. The method of claim 8, wherein selecting a transmission power includes reducing the transmission power if the differential metric does not meet a threshold criteria indicative of an insubstantial divergence between the first distribution and the second distribution.

11. An apparatus comprising:

a receiver configured to receive information corresponding to a primary network, the primary network having a medium shared with a secondary metric;

a service module to generate a first service metric corresponding to a signal to noise ratio (SNR) of the received information in absence of a perturbation on the medium and to generate a second service metric corresponding to a SNR of the received information in view of a perturbation generated by the apparatus on the network;

a processor configured to generate a result based on a first comparison of the first service metric and the second service metric and configured to select a transmission parameter based on the result; and

a transmitter configured to transmit information using the secondary network and using the transmission parameter, the transmitter configured to provide the perturbation.

12. The apparatus of claim 11, wherein the processor is configured to operate using a Media Access Control (MAC) layer, the MAC layer including the service module.

13. The apparatus of claim 11, wherein the transmission parameter includes a transmission power parameter.

14. The apparatus of claim 13, wherein the processor is configured to incrementally increase the transmission power parameter based on a second comparison of the result and a predetermined criteria.

15. The apparatus of claim 13, wherein the processor is configured to reduce the transmission power parameter based on a second comparison of the result and a predetermined criteria.