Systems, circuits and methods for adapting parameters of components in a receiver
A receiver is optimized by adapting parameters of components within the receiver. Various component parameters are adapted by using either a least means squared algorithm or a steepest descent algorithm. The taps of a decision feedback equalizer can be adapted by using either a least means squared algorithm or a steepest descent algorithm. The gain value of a linear equalizer and the input of a digital to analog converter coupled to the linear equalizer are also adapted through the least means squared algorithm or a steepest descent algorithm. A variable gain amplifier is also capable of being adapted through the use of the least means squared algorithm. Clock offsets are also configured by use of a steepest descent algorithm.
1. A method for adapting parameters of components in a receiver, comprising:
adapting a plurality of taps of a decision feedback equalizer by using a least means squared algorithm;
configuring a parameter of a linear equalizer by using a steepest descent algorithm to select a value of the parameter that minimizes a signal error rate;
varying a gain of a variable gain amplifier by using the least means squared algorithm; and
adjusting a clock offset by using the steepest descent algorithm to select a value of the clock offset that minimizes the signal error rate, wherein the adjusting of the clock offset changes a sampling point of a data slicer and an error slicer.
2. The method of claim 1 , wherein configuring a parameter of a linear equalizer comprises configuring an input of a digital to analog converter coupled to the linear equalizer, the output of the digital to analog converter for injecting into the linear equalizer.
3. The method of claim 1 , wherein configuring a parameter of a linear equalizer comprises configuring a gain value of the linear equalizer.
4. The method of claim 1 , wherein using the steepest descent algorithm comprises a gradient function to determine a direction which decreases the signal error rate most rapidly.
5. The method of claim 1 , wherein the least means squared algorithm and the steepest descent algorithm are performed by a microcontroller.
6. The method of claim 1 , wherein the signal error rate is measured by counting a number of margin hits, wherein a margin hit is counted by sampling an output signal eye from a summer.
7. The method of claim 1 , further comprising calibrating a slicer within the decision feedback equalizer when the receiver is reset, wherein the calibration comprises the injection of a current from a second digital to analog converter into the slicer.
8. A system for adapting parameters of components in a receiver, comprising:
a decision feedback equalizer comprising a plurality of taps for adaptation by using a least means squared algorithm;
a linear equalizer comprising a parameter for configuration by using a steepest descent algorithm to select a value of the parameter that minimizes a signal error rate;
a variable gain amplifier comprising a gain value for varying by using the least means squared algorithm; and
a clock offset module for adjusting a clock offset value by using the steepest descent algorithm to select a value for the clock offset that minimizes the signal error rate, wherein the adjusting of the clock offset value changes a sampling point of a data slicer and an error slicer.
9. The system of claim 8 , wherein the parameter of the linear equalizer comprises an input of a digital to analog converter coupled to the linear equalizer, the output of the digital to analog converter injected into the linear equalizer.
10. The system of claim 8 , wherein the parameter of the linear equalizer comprises a gain value of the linear equalizer.
11. The system of claim 8 , wherein the steepest descent algorithm comprises a gradient function to determine a direction which decreases the signal error rate most rapidly.
12. The system of claim 8 , wherein the least means squared algorithm and the steepest descent algorithm are performed by a microcontroller.
13. The system of claim 8 , wherein the signal error rate is measured by counting a number of margin hits, wherein a margin hit is counted by sampling an output signal eye from a summer.
14. The system of claim 8 , further comprising calibrating a slicer within the decision feedback equalizer when the receiver is reset, wherein the calibration comprises the injection of a current from a second digital to analog converter into the slicer.
15. A method for adapting parameters of components in a receiver, comprising:
adapting a tap of a decision feedback equalizer by using a steepest descent algorithm to select a value for the tap that minimizes a signal error rate;
configuring a parameter of a linear equalizer by using a steepest descent algorithm to minimize the signal error rate;
varying a gain of a variable gain amplifier by using a least means squared algorithm; and
adjusting a clock offset by using the steepest descent algorithm to minimize the signal error rate, wherein the adjusting of the clock offset changes a sampling point of a data slicer and an error slicer.
16. The method of claim 15 , wherein configuring a parameter of a linear equalizer comprises configuring an input of a digital to analog converter coupled to the linear equalizer, the output of the digital to analog converter for injecting into the linear equalizer.
17. The method of claim 15 , wherein using the steepest descent algorithm comprises using a gradient function to determine a direction which decreases the signal error rate most rapidly.
18. The method of claim 15 , wherein the least means squared algorithm and the steepest descent algorithm are performed by a microcontroller.
19. The method of claim 15 , wherein the signal error rate is measured by counting a number of margin hits, wherein a margin hit is counted by sampling an output signal eye from a summer.