Symbol scaling with automatic gain control for wireless communication

• US 8,149,964 B2
• Filed: 06/25/2007
• Issued: 04/03/2012
• Est. Priority Date: 01/05/2007
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Sidi, Jonathan, Patel, Ketan N.
• Primary Examiner(s): Ha, Dac V
• Application Number:
  US11/768,164
• Publication Number:
  US 20080165904A1
• Time in Patent Office: 1,744 Days
• Field of Search: 375/340, 375/345, 455/232.1, 455/234.1, 455/234.2, 455/235.1, 455/239.1, 455/250.1, 455/226.1, 455/226.2
• US Class Current: 375/345
• CPC Class Codes: H03G 1/04 Modifications of control circuit to reduce distortion caused by control modifications to reduce influence of variations of internal impedance of amplifying elements caused by control H03F1/08
• CPC Class Codes: H03G 3/3089 Control of digital or coded signals
• CPC Class Codes: H04B 1/7115 Constructive combining of multi-path signals, i.e. RAKE receivers
• CPC Class Codes: H04B 2201/70706 with means for reducing the peak-to-average power ratio
• CPC Class Codes: H04L 25/067 providing soft decisions, i.e. decisions together with an estimate of reliability H04L25/068 and H04L25/069 take precedence; sequence estimation techniques H04L25/03178
• CPC Class Codes: H04L 27/3809 Amplitude regulation arrangements

Abstract

Techniques for scaling symbols to account for large abrupt changes in received power at a user equipment (UE) are described. The UE performs AGC on received samples to obtain input samples. The UE processes (e.g., CDMA demodulates) the input samples to obtain first symbols. The UE determines the power of the input samples and derives a symbol gain based on (e.g., inversely related to) the power of the input samples. The UE scales the first symbols with the symbol gain to obtain detected data symbols having approximately constant amplitude, even with large abrupt changes in the power of the input samples. The UE estimates signal amplitude and noise variance based on the detected data symbols, computes LLRs for code bits of the detected data symbols based on the signal amplitude and noise variance, and decodes the LLRs to obtain decoded data.

Claims

1. An apparatus comprising:

a processor configured to process input samples to obtain first symbols, to determine power of the input samples, to derive a symbol gain based on the power of the input samples, to scale the first symbols with the symbol gain to obtain second symbols, to estimate signal amplitude and noise variance based on the second symbols, and to compute log likelihood ratios (LLRs) for code bits of the second symbols based on the signal amplitude and noise variance; and

a memory coupled to the processor.

2. The apparatus of claim 1, wherein the processor is configured to perform automatic gain control (AGC) on received samples to obtain the input samples.

3. The apparatus of claim 2, wherein in each of multiple time intervals, the processor is configured to scale received samples in the time interval with an AGC gain to obtain input samples for the time interval, to determine power of the input samples in the time interval, and to update the AGC gain based on the power of the input samples.

4. The apparatus of claim 1, wherein the processor is configured to derive the symbol gain to be inversely related to the power of the input samples.

5. The apparatus of claim 1, wherein the processor is configured to derive the symbol gain further based on a nominal symbol gain and a target power for the input samples.

6. The apparatus of claim 1, wherein the processor is configured to set the symbol gain to a nominal symbol gain if the power of the input samples is within a predetermined range, and to derive the symbol gain to be inversely related to the power of the input samples if the power is outside of the predetermined range.

7. The apparatus of claim 1, wherein the processor is configured to derive the symbol gain to achieve approximately constant amplitude for the second symbols.

8. The apparatus of claim 1, wherein the processor is configured to determine power of the input samples in each of multiple time intervals and obtain multiple power values for the multiple time intervals, and to derive the symbol gain based on the multiple power values for the multiple time intervals.

9. The apparatus of claim 8, wherein the memory is configured to store the multiple power values to time align the symbol gain with the first symbols.

10. The apparatus of claim 8, wherein for each of multiple sets of first symbols, the processor is configured to obtain at least one power value applicable to the set of first symbols from among the multiple power values, and to derive the symbol gain for the set of the first symbols based on the at least one power value.

11. The apparatus of claim 10, wherein each set of first symbols corresponds to one time interval, and wherein the symbol gain for each set of first symbols is derived based on a power value obtained for a corresponding time interval.

12. The apparatus of claim 1, wherein the signal amplitude and noise variance are estimated based on a predetermined number of second symbols, wherein the processor is further configured to determine a scale factor and a scaled threshold based on the signal amplitude and the noise variance, and wherein the log likelihood ratios (LLRs) are computed for code bits of the predetermined number of second symbols based on the scale factor and the scaled threshold.

13. The apparatus of claim 1, wherein the processor is configured to perform demodulation on the input samples to obtain demodulated symbols for at least one multipath, and to combine the demodulated symbols for the at least one multipath to obtain the first symbols.

14. The apparatus of claim 13, wherein for each multipath the processor is configured to descramble the input samples with a scrambling sequence to obtain descrambled samples, to despread the descrambled samples with at least one channelization code to obtain despread data symbols, to despread the descrambled samples with a pilot channelization code to obtain despread pilot symbols, to filter the despread pilot symbols to obtain pilot estimates, and to perform coherent demodulation on the despread data symbols with the pilot estimates to obtain demodulated symbols for the multipath.

15. A method comprising:

processing, at a wireless communications device, input samples to obtain first symbols;

determining, at the wireless communications device, power of the input samples;

deriving, at the wireless communications device, a symbol gain based on the power of the input samples;

scaling, at the wireless communications device, the first symbols with the symbol gain to obtain second symbols;

estimating, at the wireless communications device, signal amplitude and noise variance based on the second symbols; and

computing, at the wireless communications device, log likelihood ratios (LLRs) for code bits of the second symbols based on the signal amplitude and the noise variance.

16. The method of claim 15, further comprising:

performing automatic gain control (AGC) on received samples to obtain the input samples.

17. The method of claim 15, wherein the deriving the symbol gain comprises deriving the symbol gain to be inversely related to the power of the input samples.

18. The method of claim 15, wherein the deriving the symbol gain comprises

setting the symbol gain to a nominal symbol gain if the power of the input samples is within a predetermined range, and

deriving the symbol gain to be inversely related to the power of the input samples if the power is outside of the predetermined range.

19. An apparatus comprising:

means for processing input samples to obtain first symbols;

means for determining power of the input samples;

means for deriving a symbol gain based on the power of the input samples;

means for scaling the first symbols with the symbol gain to obtain second symbols;

means for estimating signal amplitude and noise variance based on the second symbols; and

means for computing log likelihood ratios (LLRs) for code bits of the second symbols based on the signal amplitude and the noise variance.

20. The apparatus of claim 19, further comprising:

means for performing automatic gain control (AGC) on received samples to obtain the input samples.

21. The apparatus of claim 19, wherein the means for deriving the symbol gain comprises

means for deriving the symbol gain to be inversely related to the power of the input samples.

22. The apparatus of claim 19, wherein the means for deriving the symbol gain comprises

means for setting the symbol gain to a nominal symbol gain if the power of the input samples is within a predetermined range, and

means for deriving the symbol gain to be inversely related to the power of the input samples if the power is outside of the predetermined range.

23. A processor-readable medium including instructions stored thereon, comprising:

a first instruction set for processing input samples to obtain first symbols;

a second instruction set for determining power of the input samples;

a third instruction set for deriving a symbol gain based on the power of the input samples;

a fourth instruction set for scaling the first symbols with the symbol gain to obtain second symbols;

a fifth instruction set for estimating signal amplitude and noise variance based on the second symbols; and

a sixth instruction set for computing log likelihood ratios (LLRs) for code bits of the second symbols based on the signal amplitude and the noise variance.

24. The processor-readable medium of claim 23, further comprising:

a seventh instruction set for performing automatic gain control (AGC) on received samples to obtain the input samples.

25. The processor-readable medium of claim 23, wherein the third instruction set comprises:

a seventh instruction set for deriving the symbol gain to be inversely related to the power of the input samples.

26. The processor-readable medium of claim 23, wherein the third instruction set comprises:

a seventh instruction set for setting the symbol gain to a nominal symbol gain if the power of the input samples is within a predetermined range, and

an eighth instruction set for deriving the symbol gain to be inversely related to the power of the input samples if the power is outside of the predetermined range.