Joint, adaptive control of equalization, synchronization, and gain in a digital communications receiver
Various aspects and embodiments of the present invention derive statistics of received signal quality and use these statistics to jointly control operation of timing recovery, carrier recovery, automatic gain control, and equalization functions.
1. A wireless communications receiver comprising:
a first receiver component configured to form soft decision samples corresponding to a received signal;
a second receiver component configured to form hard decision samples corresponding to the received signal; and
a signal processing and control block;
wherein the signal processing and control block is configured to derive control signals from the soft decision samples and the hard decision samples;
wherein the control signals include an error term; and
wherein the control signals include a combining weight based on a normalized difference between the soft decision samples and the hard decision samples, or based on indexing a programmable array of stored combining weight values, or on both; and
wherein the communication receiver is configured to use the control signals to operate a timing recovery module, a carrier recovery module, an automatic gain control module, and an equalization module.
2. The communication receiver of claim 1 , further configured to adjust a sampling phase and frequency of the received signal.
3. The communication receiver of claim 1 , wherein the combining weight is further based on comparing the soft decision sample to an element in a source constellation.
4. The communication receiver of claim 1 , wherein the combining weight is further based on a prior value of the combining weight.
5. The communication receiver of claim 1 , further configured to derive an in_box signal that indicates the instantaneous proximity of the soft decision sample to the hard decision sample.
6. The communication receiver of claim 1 , further configured to derive an in_region signal generated based on the position of a hard decision sample in a source constellation conditioned upon a prescribed template.
7. The communication receiver of claim 1 , further configured to derive a training sequence indicator valid when a current sample is part of a training sequence.
8. The communication receiver of claim 1 , wherein the communications receive is configured to operate in one or more adaptation modes including a Least Mean Squares (LMS) mode, a Constant Modulus Algorithm (CMA) mode, a combination LMS and CMA mode, and a halt mode.
9. The communication receiver of claim 1 , wherein the combining weight is utilized to adaptively combine soft decision samples and hard decision samples to form alternative hard decision samples.
10. The communication receiver of claim 1 , wherein quadrant mapping of the soft decision samples is used to form alternative hard decision samples.
11. The communication receiver of claim 1 , wherein the soft decision samples are quantized to a reduced constellation to form alternative hard decision samples.
12. The communication receiver of claim 1 , wherein end points of the soft decision samples are rounded and saturated to a bit-width wider than the hard decision samples to form alternative hard decision samples.
13. The communication receiver of claim 1 , wherein alternative hard decision samples are generated according to an arbitrary nonlinear curve.
14. The communication receiver of claim 1 , further comprising a phase detector configured to receive hard decision samples or alternative hard decision samples.
15. The communication receiver of claim 1 , wherein the error term is a Least Mean Squares (LMS) term, a Constant Modulus Algorithm (CMA) term, or a combination LMS and CMA term.
16. A system, comprising:
a control signal calculator configured to derive control signals from soft decision samples and hard decision samples,
wherein the control signals
include an error term, and
include a combining weight based on a normalized difference between the soft decision samples and the hard decision samples, or on indexing a programmable array of stored combining weight values, or on both;
wherein the control signal calculator is configured to receive the soft decision samples and the hard decision samples from a receiver configured to form the soft decision samples and the hard decision samples corresponding to the received signal; and
wherein the control signal calculator is configured to send the control signals to the receiver to operate a timing recovery module of the receiver, a carrier recovery module of the receiver, an automatic gain control module of the receiver, and an equalization module of the receiver.
17. The system of claim 16 , wherein the receiver is further configured to adjust a sampling phase and frequency of the received signal.
18. The system of claim 16 , wherein the combining weight is further based on comparing the soft decision sample to an element in a source constellation.
19. The system of claim 16 , wherein the combining weight is further based on a prior value of the combining weight.
20. The system of claim 16 , wherein the receiver is further configured to derive an in_box signal that indicates the instantaneous proximity of the soft decision sample to the hard decision sample.
21. The system of claim 16 , wherein the receiver is further configured to derive an in_region signal generated based on the position of a hard decision sample in a source constellation conditioned upon a prescribed template.
22. The system of claim 16 , wherein the receiver is further configured to derive a training sequence indicator valid when a current sample is part of a training sequence.
23. The system of claim 16 , wherein the system is further configured to operate in one or more adaptation modes including a Least Mean Squares (LMS) mode, a Constant Modulus Algorithm (CMA) mode, a combination LMS and CMA mode, and a halt mode.
24. The system of claim 16 , wherein the combining weight is utilized to adaptively combine soft decision samples and hard decision samples to form alternative hard decision samples.
25. The system of claim 16 , wherein quadrant mapping of the soft decision samples is used to form alternative hard decision samples.
26. The system of claim 16 , wherein the soft decision samples are quantized to a reduced constellation to form alternative hard decision samples.
27. The system of claim 16 , wherein end points of the soft decision samples are rounded and saturated to a bit-width wider than the hard decision samples to form alternative hard decision samples.
28. The system of claim 16 , wherein alternative hard decision samples are generated according to an arbitrary nonlinear curve.
29. The system of claim 16 , wherein the receiver includes a phase detector configured to receive hard decision samples or alternative hard decision samples.
30. The system of claim 16 , wherein the error term is a Least Mean Squares (LMS) term, a Constant Modulus Algorithm (CMA) term, or a combination LMS and CMA term.
31. In a wireless communications receiver, a system comprising:
means for forming soft decision samples corresponding to a received signal and hard decision samples corresponding to the received signal;
means for deriving control signals from the soft decision samples and the hard decision samples, wherein the control signals comprise an error term and a combining weight, wherein the combining weight is based on a normalized difference between the soft decision samples and the hard decision samples, or on indexing a programmable array of stored combining weight values, or on both; and
means for using the control signals to jointly operate of a timing recovery module of the communications receiver, a carrier recovery module of the communications receiver, an automatic gain control module of the communications receiver, and an equalization module of the communications receiver.
32. The system of claim 31 , further comprising means for adjusting a sampling phase and frequency of the received signal.
33. The system of claim 31 , wherein the combining weight is further based on comparing the soft decision sample to an element in a source constellation.
34. The system of claim 31 , wherein the combining weight is further based on a prior value of the combining weight.
35. The system of claim 31 , further comprising means for deriving an in_box signal that indicates the instantaneous proximity of the soft decision sample to the hard decision sample.
36. The system of claim 31 , further comprising means for deriving an in_region signal generated based on the position of a hard decision sample in a source constellation conditioned upon a prescribed template.
37. The system of claim 31 , further comprising means for deriving a training sequence indicator valid when a current sample is part of a training sequence.
38. The system of claim 31 , further comprising means for operating in one or more adaptation modes including a Least Mean Squares (LMS) mode, a Constant Modulus Algorithm (CMA) mode, a combination LMS and CMA mode, and a halt mode.
39. The system of claim 31 , wherein the combining weight is utilized to adaptively combine soft decision samples and hard decision samples to form alternative hard decision samples.
40. The system of claim 31 , wherein quadrant mapping of the soft decision samples is used to form alternative hard decision samples.
41. The system of claim 31 , wherein the soft decision samples are quantized to a reduced constellation to form alternative hard decision samples.
42. The system of claim 31 , wherein end points of the soft decision samples are rounded and saturated to a bit-width wider than the hard decision samples to form alternative hard decision samples.
43. The system of claim 31 , wherein alternative hard decision samples are generated according to an arbitrary nonlinear curve.
44. The system of claim 31 , further comprising means for providing hard decision samples or alternative hard decision samples to a phase detector.
45. The system of claim 31 , wherein the error term is a Least Mean Squares (LMS) term, a Constant Modulus Algorithm (CMA) term, or a combination LMS and CMA term.