Method and apparatus for spectral shaping in signal-point limited transmission systems

• US 6,192,087 B1
• Filed: 11/15/1996
• Issued: 02/20/2001
• Est. Priority Date: 11/15/1996
• Status: Expired due to Term

• Current Assignee: Modern Telecom Systems, LLC (Ideahub, Inc.)
• Original Assignee: Conexant Systems Incorporated (Synaptics Incorporated)
• Inventors: Olafsson, Sverrir, Zhou, Zhenyu, Zhang, Xuming
• Primary Examiner(s): Bocure, Tesfaldet
• Application Number:
  US08/746,731
• Time in Patent Office: 1,558 Days
• Field of Search: 375/253, 375/254, 375/285, 375/242, 375/295, 375/296, 375/346, 375/222, 341/55, 341/59, 379/93.01
• US Class Current: 375/296
• CPC Class Codes: H04L 25/4927 using levels matched to the quantisation levels of the channel

Abstract

A method and apparatus for performing spectral shaping transmitted samples with a set of predetermined frequency characteristics and a predetermined set of allowable transmitted signal levels are disclosed. The method first calculates, for each of the transmitted samples, a running measure of unwanted components upto the current sample. It then computes, for each block of the transmitted samples, an objective function based on the running measure previously calculated. It then selects, for each block of the transmitted samples, at least one redundant sample to be added or at least one transmitted sample to be modified, at structured or randomized location within the block to optimize the objective function. The location of the dependent sample can further be fixed, scrambled (pseudo random) or randomized. The method of computing can be any one of the following: a Running Filter Sum, a Running Fourier Transform (“RFT”) or Fast FT (“RFFT”), or an RDS, for each transmitted sample.

Claims

1. A method of spectrally shaping transmitted samples with a set of predetermined frequency characteristics and a predetermined set of allowable transmitted signal levels, wherein a transmitted sample is either of an unmodified source sample or a dependent sample, comprising the steps of:

a) calculating, for each of the transmitted samples, a running measure of unwanted components up to the current sample;

b) computing, for each block of the transmitted samples, an objective function based on the running measure calculated in Step a), wherein said objective function shapes the source samples to a predetermined spectrum characterized by a set of filter coefficients associated with a transmitter of said transmitted samples;

c) selecting, for each block of the transmitted samples, at least one redundant sample to be added or at least one transmitted sample to be modified, at structured or randomized location within the block to optimize the objective function in Step b).

2. A method as in claim 1, wherein the location of the dependent sample can be one of fixed, scrambled (pseudo random) or randomized.

3. The method according to claim 1, wherein the Step b) of computing comprises computing one of the following:

a) a Running Filter Sum;

b) a Running Fourier Transform (“

RFT”

) or Fast FT (“

RFFT”

);

c) a RDS, for each transmitted sample.

4. The method according to claim 1, wherein the Step b) of computing comprises computing a Running Filter Sum.

5. The method according to claim 1, wherein the Step b) of computing comprises computing either a Running Fourier Transform (“

RFT”

) or Fast FT.

6. The method according to claim 1, wherein the Step b) of computing comprises computing a RDS, for each transmitted sample.

7. A method as in claim 1, wherein the Step of selecting comprising jointly selecting redundant samples or redundant signs to optimize the objective function.

8. A method of lossless spectral shaping or coding of source samples to transmitted samples based on a set of predetermined characteristics of a frequency spectrum, where the allowable signal levels of the transmitted samples are limited to a predescribed set, comprising the steps of:

a) for each source sample, calculating any one of the following;

i) an RDS, to obtain a measurement of the DC component of the source sample up to this block;

ii) a RDFT or RFFT, to obtain a measure of unwanted signal components of the source sample up to this block;

iii) a Running Filter Sum, to obtain a measure of unwanted signal components of the source sample up to this block;

b) for every block of a determined plurality (“

N”

) of source samples, computing an objective function based on the measure obtained from Step a), wherein said objective function shapes the source samples to a predetermined spectrum characterized by a set of filter coefficients associated with a transmitter of said transmitted samples;

c) for every block of said determined plurality (“

N”

) of source samples, selecting one of;

i) at least one redundant sample,

ii) at least one redundant sign or

iii) both of at least one redundant sample and at least one redundant sign,

to optimize the objective function in Step b).

9. A method according to claim 8, further comprising the step of quantizing the redundant sample where the signal set is limited.

10. A method according to claim 8, wherein the objective function is computed based on any one of the following methods:

d) L-2 Norm (Least Square) of the measure obtained in Step a);

e) L1 Norm (Absolute Value) of the measure obtained in Step a);

f) L-alpha Norm (where 1<

α

,

     2) of the measurement obtained in a), where L-alpha Norm is represented as;

|x|^α

=Σ

|x_i|^α

, for i=1, . . . , N

g) a weighted version of d);

h) a weighted version of e);

i) a weighted version of f).

11. A method according to claim 8, where the objective function is to create at least one null at at least one arbitrary frequency.

12. A method according to claim 8, where the objective function shapes the source samples to a predetermined spectrum, where the spectrum is described by a set of filter coefficients.

13. In a transmitter for data communications with a limited number of signal points, a method of spectral shaping transmitted samples, wherein each transmitted sample is either of an unmodified source sample or a dependent sample comprising the steps of:

a) for each transmitted sample x_n, calculating K values of c_n^(k);

$c_n^{\left(k\right)}=\underset{m=0}{\overset{n}{\sum <br><br>}}<br><br>x_m<br><br>{\mathrm{<br><br>}}^{-{\mathrm{j\omega <br><br>}}_k<br><br>m}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\mathrm{\omega <br><br>}}_k=2<br><br>\mathrm{\pi <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>f_k<br><br>T,k=0,1,\mathrm{\dots <br><br>}<br><br>\text{\hspace{1em}<br><br>},K-1,K\ge <br><br>1;<br><br>$

b) calculating a measure of unwanted signal components $C_n=\frac{1}{K}<br><br>\underset{k=0}{\overset{K-1}{\sum <br><br>}}<br><br>{<br><br>c_n^{\left(k\right)}<br><br>}^2;<br><br>$

c) minimizing C_n by selecting at least one dependent sample;

d) spectrally shaping, using said transmitter, said transmitted samples in accordance with said at least one dependent sample.

14. A method as in claim 13, wherein K>

1 or K=1, f₀>

0 Hz.

15. A method as in claim 13, wherein K=2, f₀=0, f₁=60 Hz.

16. A method as in claim 13, wherein K=2, f₀=0, f₁=50 Hz.

17. A method as in claim 13, wherein K>

2, f_k≦

60 Hz, k=0,1, . . . ,K−

1.

18. A method as in claim 13, wherein the Step of minimizing is performed by selecting every L^th sample as a dependent sample based on C_n and independent of input data, and the other L-1 samples not dependent on C_n, and either K>

1 or f₀>

0 for K=1.

19. A method as in claim 18, wherein K=1, f₀≠

0.

20. A method as in claim 18, wherein K=2, f₀=0, f₁=60 Hz.

21. A method as in claim 18, wherein K=2, f₀=0, f₁=50 Hz.

22. A method as in claim 18, wherein K>

2, f_k≦

60 Hz, k=0,1, . . . ,K−

1.

23. A method as in claim 18, wherein L=8.

24. A method as in claim 18, wherein L=16.

25. A method as in claim 18, wherein the Step of minimzing is performed by selecting the sign of every L^th sample based on C_n and independent of input source data, and the other L-1 samples not dependent on C_n.

26. A method as in claim 25, wherein either K>

1 or K=1, f₀>

0 Hz.

27. A method as in claim 25, wherein K=2, f₀=0, f₁=60 Hz.

28. A method as in claim 25, wherein K=2, f₀=0, f₁=50 Hz.

29. A method as in claim 25, wherein K>

2, f_k≦

60 Hz, k=0,1, . . . ,K−

1.

30. A method as in claim 25, wherein L=1,2 or 4.

31. A method as in claim 18, wherein N dependent samples are selected jointly based on N(L-1) independent samples and C_n.

32. A method as in claim 31, where K=1.

33. A method as in claim 31, where K=2, f₀=0, f₁=60 Hz.

34. A method as in claim 31, where K=2, f₀=0, f₁=50 Hz.

35. A method as in claim 31, where K>

2, f_k≦

60 Hz, k=0,1, . . . ,K−

1.

36. A method as in claim 31, where L=8 or 16, N=2 or 3 or 4.

37. A method as in claim 13, where the Step of minimizing is performed by for each N output samples, selecting N positive samples based on input data, then selecting a M-element subset of the 2^N possible sign combinations based on input data, and then selecting one of the M sign combinations from the subset to minimize C_n and independent of input data, then using the selected sign combination to determine the sign of the output data.

38. A method as in claim 37, where the M-element subsets are selected in such a way as to maximize the Hamming distance between the subsets, considering the signs as 0'"'"'s and 1'"'"'s of a binary codeword.

39. A method as in claim 37, where M is a power of 2.

40. A method as in claim 37, where N=2,4, or 8, M=2^N−

1.

41. A method as in claim 37, where N=2,4, or 8, M=2^N.

42. A method as in claim 37, where K=1.

43. A method as in claim 37, where K=2, f₀=0, f₁=60 Hz.

44. A method as in claim 37, where K=2, f₀=0, f₁=50 Hz.

45. A method as in claim 37, where K>

2, f_k≦

60 Hz, k=0,1, . . . ,K−

1.

46. In a transmitter for data communications with a limited number of signal points, a method of arbitrary spectral-shaping of transmitted samples according to a predetermined filter characteristics G(z), wherein the transmitted sample is either of an unmodified source sample or a dependent sample, comprising the steps of:

a) computing a plurality of filter coefficients {ƒ

_m} of the inverse filter of G(z);

b) for each transmitted sample x_n, calculating unwanted signal component measure c_n based on $c_n=\underset{m=0}{\overset{n}{\sum <br><br>}}<br><br>x_m<br><br>f_{n-m};<br><br>$

c) minimizing c_n by selecting at least one dependent sample x_n;

d) spectrally shaping, using said transmitter, said transmitted samples in accordance with said at least one dependent sample x_n.

47. A method according to claim 46, wherein the at least one dependent sample is a dependently selected redundant sample.

48. A method according to claim 46, wherein the at least one dependent sample is a dependently modified source sample, either sign-modifed or sign-and-magnitude modified.

49. A method according to claim 46, where f₁=1, for all m≧

0.

50. A method according to claim 46, where f_m=α

, for all m≧

0,0<

α

<

1.

51. A method according to claim 46, where G(z)=1−

α

z<sup>−

2</sup>, 0<

α

≦

1.