Equivalent-time sampling systems, such as those within oscilloscopes, are used to reconstruct the waveforms of electrical and optical signals. Within an equivalent-time sampling system, samples of an applied signal are acquired by a sampler. A time base within the equivalent-time sampling system establishes the timing of acquired samples. This allows reconstruction of a waveform of an applied signal. The reconstruction of the waveform can be displayed or stored for later use.
When reconstructing waveforms, it is sometimes desirable to perform linear feedforward equalization. A desired impulse response is achieved by use of uniformly spaced, weighted and summed samples from the input signal. The sampling durations used for sampling are typically identical and the tap spacing is commonly set to the bit period for digital data. For example, shift registers controlled by timing based on a data clock extracted from the input signal are typically used to provide the delay.
In accordance with embodiments of the present invention, a signal sampling system includes an input signal and a plurality of samplers. The plurality of samplers produces a plurality of sample output signals. Each sampler from the plurality of samplers samples the input signal to produce a corresponding sample output signal from the plurality of sample output signals. Each sampler samples the input signal with a sampling pulse having a sampling aperture. A first sampling aperture used by a first sampler from the plurality of samplers to sample the input signal differs in duration from a second sampling aperture used by a second sampler from the plurality of samplers to sample the input signal.
Each sampler in the matrix of samplers is individually controlled by a separate strobe. For example, as shown in
By separately controlling the timing characteristics of strobes 11 through 14, this allows flexibility in the sampling intervals at which input signal is sampled. For example, for a typical linear feedforward equalizer, an input signal is sampled at uniformly spaced time taps. Strobes 11 through 14 can be adjusted to allow for such uniformly spaced time samples of input signal 11. On the other hand, for some applications, it is desirable to vary the sampling interval between performing samples. For such applications, the sampling intervals between which strobes 11 through 14 generate pulses can be varied to achieve optimal intervals between performing samples.
Similarly, separately controlling the sampling aperture used by each of samplers 21 through 24, allows flexibility in the sampling duration at which each of samplers 21 through 24 perform samples. For example, for a typical linear feedforward equalizer, each time an input signal is sampled, it is sampled for a uniform sampling duration. The sampling apertures used by samplers 21 through 24 can be adjusted to allow for each sample duration to be equal. In this case, the sampling apertures used by samplers 21 through 24 all have the same value. On the other hand, for some applications, it is desirable to vary the sampling duration for which each of samplers 21 through 24 takes samples. For such applications, the sampling apertures used by samplers 21 through 244 can be varied to achieve optimal and varied sampling durations.
In the serial topology shown in
As each sampler samples input signal 20 at sampling intervals and sampling durations, a sample output signal is generated. For example, as sampler 21 samples input signal 20 at sampling intervals and sampling durations, a sample output signal 31 is generated. As sampler 22 samples input signal 20 at sampling intervals and sampling durations, a sample output signal 32 is generated. As sampler 23 samples input signal 20 at sampling intervals and sampling durations, a sample output signal 33 is generated. As sampler 24 samples input signal 20 at sampling intervals and sampling durations, a sample output signal 34 is generated.
A signal processor 10 performs, for example, a scaled summation of the sample output signals. For example, the scaled summation is performed in software. Alternatively, signal processor 10 can be any hardware and/or software that is able to process signals in some fashion. For example, signal processor 10 digitizes sample output signals 31 through 34 and stores the digitized signals for operations performed by signal processor 10.
For example, the scaled summation produces a sum (s) in accordance with equation 1 set out below:
In Equation 1 above, SOi is the sample output signal of a sampler i. ki is a scaling constant by which sample output signal SOi is scaled for a particular application.
Signal processor 10 performs scaled summation of sample output signals 31 through 34 to produce an output signal 30.
The ability to vary timing characteristics (e.g., sampling aperture and sampling intervals) used for samplers 21 through 24, the ability to in software select scaling constants for each generated sample output and the ability to vary resolution, sensitivity and/or range by selecting the number of samplers provides for an abundance of flexibility making it practical to use the matrix of samplers for a variety of applications. For example, the matrix of samplers can be used in an equivalent time oscilloscope for equalization on live data, channel response shaping and filtering. It can also be used in serial data triggering on live data, time interval and jitter analysis and so on.
While for the majority of applications, signal processor 10 will perform a scaled summation, other types of mathematical operations, such as multiplication, may be performed on the captured sample output signals. As will be understood by persons of ordinary skill in the art, when the sample output signals are digitized and stored for operations performed in software, there are a wide variety of types of calculations that can be performed using information from the digitized intermediate signals.
Strobes 11 through 44 (shown in
As can be seen from
As can be seen from
Within a sampling sequence, sampling intervals are the intervals of time between samples being taken of input signal 20. For example, as shown in
Alternative to the serial matrix sampler topology, different topologies can be used in accordance with other embodiments of the invention. For example,
Each sampler in the matrix of samplers is individually controlled by a separate strobe. For example, as shown in
In the parallel topology shown in
A signal processor 49 performs, for example, a scaled summation of the sample output signals from each of samplers 41 through 44. For example, the scaled summation is performed in software. For example, signal processor 49 digitizes the sample output signals and stores the digitized signals for operations performed by signal processor 49.
For example, the scaled summation produces a sum (S) in accordance with equation 1 set out above.
Signal processor 49 performs scaled summation of sample output to produce an output signal 50.
The ability to vary timing characteristics (e.g., sampling aperture and sampling intervals) used for strobes 51 through 54, the ability to in software select scaling constants for each generated sample output and the ability to vary resolution, sensitivity and/or range by selecting the number of samplers provides for an abundance of flexibility making it practical to use the matrix of samplers for a variety of applications, as further discussed above.
While for the majority of applications, signal processor 49 will perform a scaled summation, other types of mathematical operations may be performed on the captured sample output signals. As will be understood by persons of ordinary skill in the art, when the sample output signals are digitized and stored for operations performed in software, there are a wide variety of types of calculations that can be performed using information from the digitized intermediate signals.
When using a serial matrix topology, such as shown in
For some applications, a combination topology can present the best way to provide the input signal to a large number of samplers. One example of a combined serial-parallel matrix topology is shown in
As shown in
An input signal 60 is received by a signal fanout 70. Signal fanout 70 provides input signal 60 to samplers 61, 71, 81 and 91. Input signal 60 gets passed through sampler 61, 62 and 63 to termination 64. Similarly, input signal 60 gets passed through sampler 71, 72 and 73 to termination 74. Input signal 60 gets passed through sampler 81, 82 and 83 to termination 84. Input signal 60 gets passed through sampler 91, 92 and 93 to termination 94.
Each sampler in the matrix of samplers shown in
A signal processor 80 performs, for example, a scaled summation of the sample output signals from each of samplers shown in
For example, the scaled summation produces a sum (S) in accordance with equation 1 set out above.
Signal processor 80 performs scaled summation of sample output to produce an output signal 90.
While for the majority of applications, signal processor 80 will perform a scaled summation, other types of mathematical operations may be performed on the captured sample output signals, as further discussed above.
The foregoing discussion discloses and describes merely exemplary methods and embodiments of the present invention. As will be understood by those familiar with the art, the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. Accordingly, the disclosure of the present invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
Number | Name | Date | Kind |
---|---|---|---|
3843926 | Espenlaub et al. | Oct 1974 | A |
4353057 | Bernet et al. | Oct 1982 | A |
4956568 | Sue et al. | Sep 1990 | A |
5815101 | Fonte | Sep 1998 | A |
6438366 | Lindfors et al. | Aug 2002 | B1 |
6564160 | Jungerman et al. | May 2003 | B2 |
6573761 | MacDonald et al. | Jun 2003 | B1 |
6650101 | MacDonald et al. | Nov 2003 | B2 |
6700516 | MacDonald | Mar 2004 | B1 |
6756775 | Jungerman | Jun 2004 | B2 |
6856924 | MacDonald | Feb 2005 | B2 |
7015842 | Gupta et al. | Mar 2006 | B1 |
7132965 | Gupta et al. | Nov 2006 | B2 |
20070109159 | Stein | May 2007 | A1 |
Number | Date | Country | |
---|---|---|---|
20070257825 A1 | Nov 2007 | US |