HIGH PERFORMANCE STATION

• US 20080165874A1
• Filed: 12/28/2007
• Published: 07/10/2008
• Est. Priority Date: 01/05/2007
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Steele, Gregory C., van Nee, D.J. Richard
• Granted Patent: US 9,253,009 B2
• Time in Patent Office: Days
• US Class Current: 375/261
• CPC Class Codes: H04B 7/0413 MIMO systems
• CPC Class Codes: H04L 1/0003 by switching between different modulation schemes
• CPC Class Codes: H04L 1/0009 by adapting the channel coding H04L1/1812 takes precedence
• CPC Class Codes: H04L 1/0026 Transmission of channel quality indication
• CPC Class Codes: H04L 1/206 for modulated signals
• CPC Class Codes: H04L 2025/03426 transmission using multiple-input and multiple-output channels
• CPC Class Codes: H04L 2027/0016 Stabilisation of local oscillators
• CPC Class Codes: H04L 25/0204 of multiple channels
• CPC Class Codes: H04L 25/0216 with estimation of channel length
• CPC Class Codes: H04L 25/061 providing hard decisions only; arrangements for tracking or suppressing unwanted low frequency components, e.g. removal of dc offset removal of dc offset in coupling arrangements H04L25/029, H04L25/0296
• CPC Class Codes: H04L 27/2647 Arrangements specific to the receiver only equalisation H04L27/01
• CPC Class Codes: H04L 27/3863 Compensation for quadrature error in the received signal

Abstract

Systems and methodologies are described for processing information at a device operating in a wireless communication system. Techniques for in-phase and quadrature (I/Q) calibration, interference cancellation, channel estimation, and signal-to-noise ratio (SNR) and rank metric calculation are provided herein. As provided herein, one or more of the described techniques can be used to adjust the performance of a wireless station in the presence of impairments to the wireless station and/or a communication link used by the wireless station.

Claims

1. A method for processing data at a wireless station, comprising:

obtaining samples related to a radio link utilized by a wireless station for communication;

identifying one or more impairments from the obtained samples;

computing one or more parameters based at least in part on the obtained samples and the identified impairments, the parameters comprising one or more items selected from a list, the list including an in-phase and quadrature (I/Q) imbalance correction factor, an interference cancellation coefficient, a channel estimate truncation point, a constellation signal-to-noise ratio (SNR) metric, and a multiple-input multiple-output (MIMO) channel rank metric; and

adjusting the wireless station based on the one or more computed parameters.

2. The method of claim 1, wherein the obtaining samples comprises generating a tone at a selected subcarrier and sampling a resulting signal, the identifying comprises identifying an amplitude imbalance between an I component and a Q component of the resulting signal, and the computing comprises estimating an I/Q amplitude imbalance correction factor at least in part by dividing a real part of a root mean square (RMS) value of the I component of the resulting signal by an RMS value of the Q component of the resulting signal.

3. The method of claim 1, wherein:

the obtaining samples comprises transmitting a first signal having a tone at an I component and a silent Q component, measuring a resulting signal of the first signal, transmitting a second signal having a tone at a Q component and a silent I component, and measuring a resulting signal of the second signal;

the identifying comprises identifying an amplitude imbalance between the resulting signal of the first signal and the resulting signal of the second signal; and

the computing comprises estimating an I/Q amplitude imbalance correction factor at least in part by dividing an RMS value of the resulting signal of the first signal by an RMS value of the resulting signal of the second signal.

4. The method of claim 1, wherein:

the identifying comprises identifying I/Q phase imbalance associated with the wireless station;

the computing comprises approximating the I/Q phase imbalance using a finite impulse response (FIR) filter, the FIR filter having associated FIR coefficients, and computing the associated FIR coefficients; and

the adjusting comprises applying the FIR coefficients to an I/Q modulator or an I/Q demodulator associated with the wireless station.

5. The method of claim 4, wherein the FIR coefficients comprise a mean phase imbalance FIR coefficient and a slope phase imbalance FIR coefficient, and the computing further comprises determining the mean phase imbalance FIR coefficient by computing a mean of the I/Q phase imbalance across frequency and selecting the slope phase imbalance FIR coefficient to represent an approximately linear variation in the I/Q phase imbalance across frequency around the mean of the I/Q phase imbalance.

6. The method of claim 5, wherein the identifying further comprises selecting a set of subcarriers such that no two subcarriers in the set of subcarriers are an equal distance from a zero subcarrier and identifying I/Q phase imbalances for pairs of positive and negative subcarriers in the set of subcarriers, and the selecting the slope phase imbalance FIR coefficient comprises selecting the slope phase imbalance FIR coefficient at least in part by computing averages of the I/Q phase imbalances for the pairs of positive and negative subcarriers in the set of subcarriers.

7. The method of claim 1, wherein the obtaining samples comprises sampling respective input signals from one or more antennas, the identifying comprises identifying interference present in the respective input signals, and the computing comprises estimating one or more cross-correlation values and one or more cancellation coefficients based on the respective input signals.

8. The method of claim 7, wherein the adjusting comprises canceling the identified interference based on the estimated cross-correlation values and cancellation coefficients.

9. The method of claim 8, wherein the computing further comprises comparing the cross-correlation values to a threshold and the canceling the identified interference based on the estimated cross-correlation values and cancellation coefficients is performed if one or more cross-correlation values exceeds the threshold.

10. The method of claim 8, wherein the adjusting further comprises determining a cancellation signal and injecting the cancellation signal to a receiver chain prior to an automatic gain control block or a receiver block.

11. The method of claim 7, wherein the adjusting comprises balancing lnposelstartpower levellnposelends of the respective input signals.

12. The method of claim 11, wherein the computing further comprises estimating a minimum output power level and calculating power correction factors based on combined noise and interference levels of the respective input signals and the minimum output power level, and the adjusting further comprises balancing the power levels of the respective input signals based at least in part on the power correction factors.

13. The method of claim 7, wherein the computing further comprises maintaining respective moving averages of samples obtained from the respective input signals and calculating cross-correlation values and cancellation coefficients based on the respective moving averages.

14. The method of claim 7, wherein the computing further comprises estimating the one or more cancellation coefficients to maximize a signal-to-interference-plus-noise ratio (SINR) of packets received from an identified source.

15. The method of claim 1, wherein the obtaining samples comprises obtaining raw channel estimates and the computing comprises multiplying the raw channel estimates by a windowing function to obtain windowed channel estimates, generating an inverse FFT (IFFT) of the windowed channel estimates to obtain channel impulse response estimates, determining a power-delay profile from the channel impulse response estimates by squaring the channel impulse response estimates and summing the squared estimates over one or more receivers, calculating a positive cutoff point and a negative cutoff point based on the power-delay profile, truncating the channel impulse response estimates using the positive cutoff point and the negative cutoff point, and converting the truncated impulse response estimates to adjusted channel estimates.

16. The method of claim 15, wherein the computing further comprises estimating a DC offset present in the channel impulse response estimates and correcting the DC offset by adjusting the channel impulse response estimates.

17. The method of claim 15, further comprising comparing a length between the positive cutoff point and the negative cutoff point to a maximum truncation length and the truncating the channel impulse response estimates is performed if the length between the positive cutoff point and the negative cutoff point is less than or equal to the maximum truncation length.

18. The method of claim 15, further comprising comparing a length between the positive cutoff point and the negative cutoff point to a minimum truncation length and adjusting at least one of the positive cutoff point and the negative cutoff point if the length between the positive cutoff point and the negative cutoff point is less than the minimum truncation length

19. The method of claim 15, wherein the computing further comprises replacing band edge tones in the adjusted channel estimates with band edge tones in the raw channel estimates.

20. The method of claim 1, wherein the obtaining samples comprises sampling data relating to received constellation points and distances from the received constellation points to nearest sliced constellation points corresponding to one or more symbols and the computing comprises summing the received constellation points for respective symbols to obtain respective signal power estimates, summing the distances from the received constellation points to the nearest sliced constellation points for the respective symbols to obtain respective noise power estimates, averaging the signal power estimates and the noise power estimates over the respective symbols, and determining a constellation signal-to-noise ratio (SNR) as a ratio of the average signal power to the average noise power.

21. The method of claim 20, wherein the averaging comprises averaging the signal power estimates and the noise power estimates using a one-pole low pass filter and a programmable averaging constant.

22. The method of claim 20, wherein the identifying comprises identifying a maximum packet error probability and the adjusting comprises selecting a data rate for communication based on the maximum packet error probability and the constellation SNR.

23. The method of claim 1, wherein the obtaining samples comprises estimating multiple-input multiple-output (MIMO) channel matrices for respective subcarriers and the computing comprises multiplying the respective MIMO channel matrices by their respective Hermitians to obtain respective intermediate square matrices, computing rank metrics for the respective subcarriers based on the intermediate square matrices, and averaging the computed rank metrics over the respective subcarriers to obtain an average MIMO rank metric.

24. The method of claim 23, wherein the computing further comprises performing QR decomposition for the respective MIMO channel matrices to obtain corresponding intermediate upper triangular matrices and computing the rank metrics for the respective subcarriers based on the intermediate upper triangular matrices.

25. The method of claim 23, wherein the identifying comprises identifying a maximum packet error probability and the adjusting comprises selecting a number of spatial streams for communication based on the maximum packet error probability and the average MIMO rank metric.

26. A wireless communications apparatus, comprising:

a memory that stores data relating to a radio link utilized for communication by the wireless communications apparatus and one or more samples relating thereto; and

a processor configured to identify adjustments to be performed at the wireless communications apparatus based on the one or more samples;

to select one or more parameters for the adjustments from a list, the list comprising an I/Q correction coefficient, an interference cancellation factor, a channel estimate cutoff point, and a channel quality indicator; and

to perform the identified adjustments.

27. The wireless communications apparatus of claim 26, wherein the memory further stores data relating a signal resulting from generation of a tone at a predetermined subcarrier and the processor is further configured to identify an amplitude imbalance between an I component and a Q component of the signal and to compute an amplitude correction factor at least in part by dividing an RMS value of the I component of the signal by an RMS value of the Q component of the signal.

28. The wireless communications apparatus of claim 26, wherein the memory further stores data relating to an I signal resulting from a signal generated using an I-component tone and a Q signal resulting from a signal generated using a Q-component tone, and the processor is further configured to identify an amplitude imbalance between the I signal and the Q signal and to compute an amplitude correction factor at least in part by dividing an RMS value of the I signal by an RMS value of the Q signal.

29. The wireless communications apparatus of claim 26, wherein the memory further stores data relating to a signal resulting from generation of tones at a group of subcarriers selected such that no subcarriers in the group of subcarriers share a common distance from a zero subcarrier, and the processor is further configured to identify a phase imbalance between an I component and a Q component of the signal and to approximate the phase imbalance using a FIR filter having a mean phase correction factor and a pair difference phase correction factor.

30. The wireless communications apparatus of claim 29, wherein the processor is further configured to determine the mean phase correction factor as a mean of the phase imbalance across frequency and to select the pair difference phase correction factor as an approximation of a linear phase imbalance variation with respect to frequency.

31. The wireless communications apparatus of claim 30, wherein the processor is further configured to select the pair difference phase correction factor at least in part by computing respective averages of phase imbalances for pairs of positive and negative subcarriers in the group of subcarriers.

32. The wireless communications apparatus of claim 26, wherein the memory further stores data relating to signals received at one or more antennas and the processor is further configured to identify interference in the respective signals and to estimate cross-correlation values and cancellation coefficients based on the respective signals.

33. The wireless communications apparatus of claim 32, wherein the processor is further configured to apply the cancellation coefficients to the signals to cancel the identified interference.

34. The wireless communications apparatus of claim 33, wherein the processor is further configured to monitor the cross-correlation values in relation to a threshold and to apply the cancellation coefficients to the signal upon determining that a cross-correlation value exceeds the threshold.

35. The wireless communications apparatus of claim 32, wherein the processor is further configured to apply the cancellation coefficients to the signals by generating one or more cancellation signals and injecting the cancellation signals into respective receiver chains corresponding to the signals.

36. The wireless communications apparatus of claim 32, wherein the processor is further configured to balance respective power levels of the signals.

37. The wireless communications apparatus of claim 36, wherein the processor is further configured to estimate a minimum power output level, to calculate power correction factors based on combined noise and interference levels of the respective signals and the minimum power output level, and to balance the power levels of the respective signals based on the power correction factors.

38. The wireless communications apparatus of claim 32, wherein the processor is further configured to maintain moving averages of samples obtained from the input signals and to calculate the cross-correlation values and cancellation coefficients based at least in part on the maintained moving averages.

39. The wireless communications apparatus of claim 26, wherein the memory further stores data relating to one or more raw channel estimates and the processor is further configured to window the raw channel estimates based on a windowing function, to perform an IFFT for windowed channel estimates to obtain channel impulse response estimates, to determine a power-delay profile from the channel impulse response estimates by squaring the channel impulse response estimates and summing the squared estimates over one or more receivers, to truncate the channel response estimates based on the power-delay profile, and to convert the truncated impulse response estimates to adjusted channel estimates.

40. The wireless communications apparatus of claim 39, wherein the processor is further configured to estimate and correct a DC offset present in the channel impulse response estimates.

41. The wireless communications apparatus of claim 39, wherein the processor is further configured to null unused tones in the raw channel estimates.

42. The wireless communications apparatus of claim 39, wherein the memory further stores data relating to a positive truncation value and a negative truncation value and the processor is further configured to truncate the channel impulse response estimates at the positive truncation value and the negative truncation value.

43. The wireless communications apparatus of claim 26, wherein the memory further stores data relating to received constellation points corresponding to one or more symbols and distances from the received constellation points to respective nearest sliced constellation points and the processor is further configured to sum the received constellation points for the one or more symbols to obtain respective signal power estimates, to sum the distances from the received constellation points to the respective nearest sliced constellation points to obtain respective noise power estimates, to obtain an average signal power estimate and an average noise power estimate over the one or more symbols, and to divide the average signal power estimate by the average noise power estimate to obtain a constellation SNR metric.

44. The wireless communications apparatus of claim 43, wherein the processor is further configured to obtain the average signal power estimate and the average noise power estimate using a one-pole low pass filter.

45. The wireless communications apparatus of claim 43, wherein the memory further stores data relating to a maximum packet error probability and the processor is further configured to set a data rate based on the maximum packet error probability and the constellation SNR metric.

46. The wireless communications apparatus of claim 26, wherein the memory further stores data relating to MIMO channel matrices for respective subcarriers and the processor is further configured to obtain Hermitian matrices for respective MIMO channel matrices, to multiply the respective MIMO matrices by their respective Hermitian matrices to obtain intermediate matrices, to compute metrics for respective subcarriers based on the intermediate matrices, and to compute a MIMO rank metric by averaging the rank metrics computed for the respective subcarriers over the subcarriers.

47. The wireless communications apparatus of claim 46, wherein the processor is further configured to perform QR decomposition for the respective MIMO channel matrices to obtain corresponding intermediate upper triangular matrices and to compute the rank metrics for the respective subcarriers based on the intermediate upper triangular matrices.

48. The wireless communications apparatus of claim 46, wherein the memory further stores data relating to a maximum packet error probability and the processor is further configured to set a number of spatial streams to be used for communication based on the maximum packet error probability and the MIMO rank metric.

49. An apparatus that facilitates signal processing in a wireless communication system, comprising:

means for obtaining data relating to operating characteristics of the apparatus;

means for identifying one or more adjustments to be performed at the apparatus based on the obtained data;

means for computing parameters selected from a group to be used in connection with the identified adjustments, the group comprising I/Q correction factors, interference cancellation coefficients, channel estimate cutoff points, constellation SNR metrics, and MIMO rank metrics; and

means for performing the identified adjustments at the station based on the computed parameters.

50. A computer-readable medium, comprising:

code for causing a computer to acquire information relating to a radio link used for communication, the information indicating one or more impairments;

code for causing a computer to determine a set of parameters to be computed based on the impairments, the set of parameters selected from a list, the list comprising I/Q calibration coefficients, interference cancellation weights, channel truncation values, and channel quality indicators; and

code for causing a computer to compute the set of parameters based on the acquired information to enable adjustment for the impairments based on the set of parameters.

51. An integrated circuit that executes computer-executable instructions, the instructions comprising:

identifying one or more adjustments to be made at a wireless station;

selecting one or more adjustment parameters from a list for the adjustments, the list comprising an I/Q correction coefficient, an interference cancellation factor, a channel estimate truncation point, a constellation SNR, and a MIMO rank metric;

computing the selected adjustment parameters; and

performing the identified adjustments based on the computed adjustment parameters.