Method and apparatus for performing channel assessment in a wireless communication system

• US 20060133543A1
• Filed: 12/21/2004
• Published: 06/22/2006
• Est. Priority Date: 12/21/2004
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: RF Micro Devices Incorporated (Qorvo, Inc.)
• Inventors: Linsky, Joel, Miller, Brian
• Granted Patent: US 7,684,464 B2
• Time in Patent Office: Days
• US Class Current: 375/341
• CPC Class Codes: H04B 1/715 Interference-related aspects
• CPC Class Codes: H04B 17/336 Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
• CPC Class Codes: H04L 25/0204 of multiple channels

Abstract

A system and method for classifying channels in a frequency hopping wireless communication system is provided. A data collection engine operates to obtain channel metrics indicating the level of interference for each channel used by the wireless communication system. A data analysis engine operates to provide a channel map for adaptive frequency hopping (AFH) and/or a channel map for channel avoidance. More specifically, the data analysis engine first operates to filter the channel metrics to remove channel metrics indicative of frequency hopping interference. Next, the channels are divided into a number of channel blocks each including at least two adjacent channels. For each channel block, the channel metrics of the channels within the channel block are combined to provide a metric sum. The data analysis engine then operates to classify each channel as usable or unusable based on the metric sums for each of the channel blocks.

Claims

1. A method of assessing channels in a wireless communication system comprising:

a) obtaining channel metrics for each of a plurality of channels in the wireless communication system, wherein the channel metrics include information representative of interference signals in the plurality of channels;

b) filtering the channel metrics to remove metrics associated with frequency hopped interference to provide filtered channel metrics;

c) to determine a shape of the frequency static interference based on the filtered channel metrics;

i) dividing the plurality of channels into a plurality of channel blocks, each channel block comprising at least two adjacent channels; and

ii) for each of the plurality of channel blocks, combining the channel metrics of the at least two adjacent channels, thereby providing a combined metric for each of the plurality of channel blocks; and

d) classifying each of the plurality of channels based on the combined metrics, thereby identifying usable and unusable channels.

2. The method of claim 1 wherein to determine the shape of the frequency static interference, the method further comprises:

finding a number (N) of the plurality of channel blocks having the worst interference based on the combined metrics of the plurality of channel blocks, wherein N is a predetermined maximum number of channel blocks that are to be classified as unusable.

3. The method of claim 2 wherein finding the number (N) of the plurality of channel blocks having the worst interference comprises:

for each of the plurality of channel blocks;

comparing the combined metric to a previous value of a metric sum peak for the channel block;

if the combined metric is greater than the previous value of the metric sum peak, setting the metric sum peak equal to the combined metric; and

if the combined metric is less than the previous value of the metric sum peak, decrementing the previous value of the metric sum peak by a predetermined value to provide the metric sum peak; and

finding the number (N) of the plurality of channel blocks having the worst interference by finding a number (N) of the plurality of channel blocks having largest ones of the metric sum peak values.

4. The method of claim 2 wherein classifying each of the plurality of channels comprises:

comparing the combined metric for each of the number (N) of the plurality of channel blocks to a predetermined combined metric threshold value.

5. The method of claim 4 wherein classifying each of the plurality of channels further comprises, for each of the number (N) of the plurality of channel blocks, setting a corresponding hangover timer to a predetermined hangover value if the combined metric for the channel block is greater than the predetermined combined metric threshold value.

6. The method of claim 5 wherein classifying each of the plurality of channels comprises classifying each of the plurality of channels based on the corresponding hangover timers for each of the plurality of channel blocks.

7. The method of claim 6 wherein classifying each of the plurality of channels based on the corresponding hangover timers comprises:

classifying channels within each of the number (N) of the plurality of channel blocks as unusable if the corresponding hangover timer is not expired; and

classifying channels within each of the number (N) of the plurality of channel blocks as usable if the corresponding hangover timer is expired.

8. The method of claim 7 wherein classifying each of the plurality of channels further comprises classifying channels within ones of the plurality of channel blocks other than the number (N) of the plurality of channel blocks as usable.

9. The method of claim 1 wherein classifying each of the plurality of channels is further based on remote metrics from one or more external devices.

10. The method of claim 1 wherein to determine the shape of the frequency static interference, the method further comprises:

finding a one of the plurality of channel blocks corresponding to a center frequency of the frequency static interference based on the combined metrics for the plurality of channel blocks; and

classifying each of the plurality of channels comprises;

processing the one of the plurality of channel blocks corresponding to the center frequency of the frequency static interference to determine a one of the plurality of channels corresponding to the center frequency; and

classifying the one of the plurality of channels corresponding to the center frequency and a number of the plurality of channels within a predetermined bandwidth about the one of the plurality of channels corresponding to the center frequency as unusable.

11. The method of claim 10 wherein finding the one of the plurality of channel blocks corresponding to the center frequency comprises:

for each of the plurality of channel blocks;

comparing the combined metric to a previous value of a metric sum peak for the channel block;

if the combined metric is greater than the previous value of the metric sum peak, setting the metric sum peak equal to the combined metric; and

if the combined metric is less than the previous value of the metric sum peak, decrementing the previous value of the metric sum peak by a predetermined value to provide the metric sum peak; and

finding the one of the plurality of channel blocks corresponding to the center frequency by finding a one of the plurality of channel blocks having a largest one of the metric sum peaks.

12. The method of claim 11 wherein processing the one of the plurality of channel blocks corresponding to the center frequency of the frequency static interference comprises filtering the one of the plurality of channel blocks to determine the one of the plurality of channels corresponding to the center frequency.

13. The method of claim 10 wherein the predetermined bandwidth is approximately equal to 22 MHz.

14. The method of claim 1 wherein obtaining the channel metrics for each of the plurality of channels comprises:

initializing the channel metric for each of the plurality of channels;

collecting data representative of the interference for each of the plurality of channels;

for each of the plurality of channels, comparing the data to a series of thresholds;

for each of the plurality of channels, combining a previous value of the channel metric and a value corresponding to a largest one of the series of thresholds that the data for the channel exceeds to provide the channel metric; and

repeating the collecting, comparing, and combining steps until a predetermined number of iterations are performed.

15. The method of claim 1 further comprising periodically initiating the step of obtaining the channel metrics.

16. The method of claim 1 wherein obtaining the channel metrics is initiated upon detecting a packet-error-rate above a predetermined error threshold.

17. A wireless communication system comprising:

a data collection engine adapted to obtain channel metrics for each of a plurality of channels in the wireless communication system, wherein the channel metrics include information representative of interference signals in the plurality of channels; and

a data analysis engine adapted to;

a) filter the channel metrics to remove metrics associated with frequency hopped interference to provide filtered channel metrics;

b) divide the plurality of channels into a plurality of channel blocks, each channel block comprising at least two adjacent channels;

c) for each of the plurality of channel blocks, combine the channel metrics of the at least two adjacent channels to provide a combined metric for each of the plurality of channel blocks; and

d) classify each of the plurality of channels based on the combined metrics, thereby identifying usable and unusable channels.

18. The system of claim 17 wherein the data analysis engine is further adapted to find a number (N) of the plurality of channel blocks having the worst interference based on the combined metrics of the plurality of channel blocks, wherein N is a predetermined maximum number of channel blocks that are to be classified as unusable.

19. The system of claim 18 wherein to determine the number (N) of the plurality of channel blocks having the worst interference, the data analysis engine is further adapted to:

for each of the plurality of channel blocks;

compare the combined metric to a previous value of a metric sum peak for the channel block;

if the combined metric is greater than the previous value of the metric sum peak, set the metric sum peak equal to the combined metric; and

if the combined metric is less than the previous value of the metric sum peak, decrement the previous value of the metric sum peak by a predetermined value to provide the metric sum peak; and

find the number (N) of the plurality of channel blocks having the worst interference by finding a number (N) of the plurality of channel blocks having largest ones of the metric sum peak values.

20. The system of claim 18 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to compare the combined metric for each of the number (N) of the plurality of channel blocks to a predetermined combined metric threshold value.

21. The system of claim 20 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to, for each of the number (N) of the plurality of channel blocks, set a corresponding hangover timer to a predetermined hangover value if the combined metric for the channel block is greater than the predetermined combined metric threshold value.

22. The system of claim 21 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to classify each of the plurality of channels based on the corresponding hangover timers for each of the plurality of channel blocks.

23. The system of claim 22 wherein to classify each of the plurality of channels based on the corresponding hangover timers, the data analysis engine is further adapted to:

classify channels within each of the number (N) of the plurality of channel blocks as unusable if the corresponding hangover timer is not expired; and

classify channels within each of the number (N) of the plurality of channel blocks as usable if the corresponding hangover timer is expired.

24. The system of claim 23 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to classify channels within ones of the plurality of channel blocks other than the number (N) of the plurality of channel blocks as usable.

25. The system of claim 17 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to classify each of the plurality of channels based on remote metrics from one or more external devices.

26. The system of claim 17 wherein the data analysis engine is further adapted to find a one of the plurality of channel blocks corresponding to a center frequency of a frequency static interference based on the combined metrics for the plurality of channel blocks.

27. The system of claim 26 wherein in order to classify each of the plurality of channels, the data analysis engine is further adapted to:

process the one of the plurality of channel blocks corresponding to the center frequency of the frequency static interference to determine a one of the plurality of channels corresponding to the center frequency; and

classify the one of the plurality of channels corresponding to the center frequency and a number of the plurality of channels within a predetermined bandwidth about the one of the plurality of channels corresponding to the center frequency as unusable channels.

28. The system of claim 27 wherein to find the one of the plurality of channel blocks corresponding to the center frequency, the data analysis engine is further adapted to:

for each of the plurality of channel blocks;

compare the combined metric to a previous value of a metric sum peak for the channel block;

if the combined metric is greater than the previous value of the metric sum peak, set the metric sum peak equal to the combined metric; and

if the combined metric is less than the previous value of the metric sum peak, decrement the previous value of the metric sum peak by a predetermined value to provide the metric sum peak; and

find the one of the plurality of channel blocks corresponding to the center frequency by finding a one of the plurality of channel blocks having a largest one of the metric sum peaks.

29. The system of claim 28 wherein the data analysis engine is adapted to process the one of the plurality of channel blocks corresponding to the center frequency of the frequency static interference by filtering the one of the plurality of channel blocks to determine the one of the plurality of channels corresponding to the center frequency.

30. The system of claim 27 wherein the predetermined bandwidth is approximately equal to 22 MHz.

31. The system of claim 17 wherein to obtain the channel metrics for each of the plurality of channels, the data collection engine is further adapted to:

initialize the channel metric for each of the plurality of channels; and

repeatedly collect data representative of the interference for each of the plurality of channels, compare the data for each of the plurality of channels to a series of thresholds for each of the plurality of channels, and, for each of the plurality of channels, combine a previous value of the channel metric and a value corresponding to a largest one of the series of thresholds that the data for the channel exceeds to provide the channel metric until a predetermined number of iterations are performed.

32. The system of claim 17 wherein the data collection engine is periodically triggered to obtain the channel metrics.

33. The system of claim 17 wherein the data collection engine is triggered to obtain the channel metrics upon detecting a packet-error-rate above a predetermined error threshold.

34. A method of assessing channels in a wireless communication system comprising:

a) obtaining channel metrics for each of a plurality of channels in the wireless communication system, wherein the channel metrics include information representative of interference signals in the plurality of channels;

b) determining whether to set a hangover timer to a predetermined hangover value for each of the plurality of channels based on at least one of the channel metrics for the plurality of channels; and

c) classifying each of the plurality of channels based on the hangover timer for each of the plurality of channels, thereby identifying usable and unusable channels.

35. The method of claim 34 wherein determining whether to set the hangover timer to the predetermined hangover value for each of the plurality of channels comprises filtering the channel metrics to remove metrics associated with frequency hopped interference to provide filtered channel metrics.

36. The method of claim 35 wherein determining whether to set the hangover timer to the predetermined hangover value for each of the plurality of channels further comprises determining a shape of a frequency static interference based on the filtered channel metrics, determining the shape of the frequency static interference comprising:

dividing the plurality of channels into a plurality of channel blocks, each channel block comprising at least two adjacent channels; and

for each of the plurality of channel blocks, combining the channel metrics of the at least two adjacent channels, thereby providing a combined metric for each of the plurality of channel blocks.

37. The method of claim 36 wherein determining whether to set the hangover timer to the predetermined hangover value for each of the plurality of channels is further based on the combined metrics for the plurality of channel blocks.

38. The method of claim 36 wherein determining the shape of the frequency static interference further comprises:

finding a number (N) of the plurality of channel blocks having the worst interference based on the combined metrics of the plurality of channel blocks, wherein N is a predetermined maximum number of channel blocks that are to be classified as unusable.

39. The method of claim 38 wherein finding the number (N) of the plurality of channel blocks having the worst interference comprises:

for each of the plurality of channel blocks;

comparing the combined metric to a previous value of a metric sum peak for the channel block;

if the combined metric is greater than the previous value of the metric sum peak, setting the metric sum peak equal to the combined metric; and

if the combined metric is less than the previous value of the metric sum peak, decrementing the previous value of the metric sum peak by a predetermined value to provide the metric sum peak; and

finding the number (N) of the plurality of channel blocks having the worst interference by finding a number (N) of the plurality of channel blocks having largest ones of the metric sum peak values.

40. The method of claim 38 wherein classifying each of the plurality of channels comprises:

comparing the combined metric for each of the number (N) of the plurality of channel blocks to a predetermined combined metric threshold value.

41. The method of claim 40 wherein classifying each of the plurality of channels further comprises, for each of the number (N) of the plurality of channel blocks, setting the hangover timer to the predetermined hangover value if the combined metric for the channel block is greater than the predetermined combined metric threshold value.

42. The method of claim 41 wherein classifying each of the plurality of channels further comprises:

classifying channels within each of the number (N) of the plurality of channel blocks as unusable if the corresponding hangover timer is not expired; and

classifying channels within each of the number (N) of the plurality of channel blocks as usable if the corresponding hangover timer is expired.

43. A system for assessing channels in a wireless communication system comprising:

a) a data collection engine adapted to obtain channel metrics for each of a plurality of channels in the wireless communication system, wherein the channel metrics include information representative of interference signals in the plurality of channels; and

b) a data analysis engine adapted to;

determine whether to set a hangover timer to a predetermined hangover value for each of the plurality of channels based on at least one of the channel metrics for the plurality of channels; and

classify each of the plurality of channels based on the hangover timer for each of the plurality of channels, thereby identifying usable and unusable channels.

44. The system of claim 43 wherein to determine whether to set the hangover timer to the predetermined hangover value for each of the plurality of channels, the data analysis engine is further adapted to filter the channel metrics to remove metrics associated with frequency hopped interference to provide filtered channel metrics.

45. The system of claim 44 wherein to determine whether to set the hangover timer to the predetermined hangover value for each of the plurality of channels, the data analysis engine is further adapted to:

divide the plurality of channels into a plurality of channel blocks, each channel block comprising at least two adjacent channels; and

for each of the plurality of channel blocks, combine the channel metrics of the at least two adjacent channels, thereby providing a combined metric for each of the plurality of channel blocks.

46. The system of claim 45 wherein the data analysis engine is further adapted to determine whether to set the hangover timer to the predetermined hangover value for each of the plurality of channels based on the combined metrics for the plurality of channel blocks.

47. The system of claim 45 wherein to determine whether to set the hangover timer to the predetermined hangover value for each of the plurality of channels, the data analysis engine is further adapted to find a number (N) of the plurality of channel blocks having the worst interference based on the combined metrics of the plurality of channel blocks, wherein N is a predetermined maximum number of channel blocks that are to be classified as unusable.

48. The system of claim 47 wherein to find the number (N) of the plurality of channel blocks having the worst interference, the data analysis engine is further adapted to:

for each of the plurality of channel blocks;

compare the combined metric to a previous value of a metric sum peak for the channel block;

if the combined metric is greater than the previous value of the metric sum peak, set the metric sum peak equal to the combined metric; and

if the combined metric is less than the previous value of the metric sum peak, decrement the previous value of the metric sum peak by a predetermined value to provide the metric sum peak; and

find the number (N) of the plurality of channel blocks having the worst interference by finding a number (N) of the plurality of channel blocks having largest ones of the metric sum peak values.

49. The system of claim 47 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to compare the combined metric for each of the number (N) of the plurality of channel blocks to a predetermined combined metric threshold value.

50. The system of claim 49 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to, for each of the number (N) of the plurality of channel blocks, set the hangover timer to the predetermined hangover value if the combined metric for the channel block is greater than the predetermined combined metric threshold value.

51. The system of claim 50 wherein to classify each of the plurality of channels, the data analysis engine is further adapted to:

classify channels within each of the number (N) of the plurality of channel blocks as unusable if the corresponding hangover timer is not expired; and

classify channels within each of the number (N) of the plurality of channel blocks as usable if the corresponding hangover timer is expired.