Vector processor having instruction set with sliding window non-linear convolutional function

1. A method performed by a processor, comprising:

obtaining at least one software instruction that performs at least one non-linear convolution function for a plurality of input delayed signal samples;

in response to said at least one software instruction for said at least one non-linear convolution function, performing the following steps:

generating a weighted sum of two or more of said input delayed signal samples, wherein said weighted sum comprises a plurality of variable coefficients defined as a sum of one or more non-linear functions of a magnitude of said input delayed signal samples; and

repeating said generating step for at least one time-shifted version of said input delayed signal samples to compute a plurality of consecutive outputs, wherein said at least one software instruction for said at least one non-linear convolution function is part of an instruction set of said processor.

2. The method of claim 1 , wherein said processor comprises a vector processor.

3. The method of claim 1 , wherein said plurality of variable coefficients defined by a non-linear function of a magnitude of said input delayed signal samples are implemented using one or more look-up tables.

4. The method of claim 1 , wherein said non-linear convolution function models a non-linear system with memory.

5. The method of claim 4 , wherein said non-linear system with memory comprises one or more of a power amplifier model and a digital pre-distortion function.

6. The method of claim 1 , wherein said at least one non-linear convolution function is implemented using one or more look-up tables having linear interpolation.

7. The method of claim 1 , wherein said at least one non-linear convolution function is implemented using one or more look-up tables having polynomial interpolation.

8. The method of claim 1 , further comprising the step of loading at least one user-specified parameter from memory into at least one register file.

9. The method of claim 8 , wherein said user-specified parameter comprises a look-up table storing values of said non-linear convolution function for one or more input values.

10. The method of claim 1 , further comprising the step of reading said plurality of input delayed signal samples directly from memory into functional units for said non-linear convolution function.

11. A processor configured to implement a signal processing function in software, comprising:

a memory; and

at least one hardware device, coupled to the memory, operative to:

obtain at least one software instruction that performs at least one non-linear convolution function for a plurality of input delayed signal samples;

in response to said at least one software instruction for said at least one non-linear convolution function:

generate a weighted sum of two or more of said input delayed signal samples, wherein said weighted sum comprises a plurality of variable coefficients defined as a sum of one or more non-linear functions of a magnitude of said input delayed signal samples; and

repeat said generating step for at least one time-shifted version of said input delayed signal samples to compute a plurality of consecutive outputs, wherein said at least one software instruction for said at least one non-linear convolution function is part of an instruction set of said processor.

12. The processor of claim 11 , wherein said processor comprises a vector processor.

13. The processor of claim 11 , wherein said plurality of variable coefficients defined by a non-linear function of a magnitude of said input delayed signal samples are implemented using one or more look-up tables.

14. The processor of claim 11 , wherein said non-linear convolution function models a non-linear system with memory.

15. The processor of claim 14 , wherein said non-linear system with memory comprises one or more of a power amplifier model and a digital pre-distortion function.

16. The processor of claim 11 , wherein said at least one non-linear convolution function is implemented using one or more look-up tables having linear interpolation.

17. The processor of claim 11 , wherein said at least one non-linear convolution function is implemented using one or more look-up tables having polynomial interpolation.

18. The processor of claim 11 , further comprising the step of loading at least one user-specified parameter from memory into at least one register file.

19. The processor of claim 18 , wherein said user-specified parameter comprises a look-up table storing values of said non-linear convolution function for one or more input values.

20. The processor of claim 11 , further comprising the step of reading said plurality of input delayed signal samples directly from memory into functional units for said non-linear convolution function.

21. An article of manufacture, comprising a non-transitory machine readable recordable medium containing one or more programs which when executed by a processor implement the steps of:

obtaining at least one software instruction that performs at least one non-linear convolution function for a plurality of input delayed signal samples;

in response to said at least one software instruction for said at least one non-linear convolution function, performing the following steps:

generating a weighted sum of two or more of said input delayed signal samples, wherein said weighted sum comprises a plurality of variable coefficients defined as a sum of one or more non-linear functions of a magnitude of said input delayed signal samples; and

repeating said generating step for at least one time-shifted version of said input delayed signal samples to compute a plurality of consecutive outputs, wherein said at least one software instruction for said at least one non-linear convolution function is part of an instruction set of said processor.