CA1087693A - Frequency domain automatic equalizer utilizing the discrete fourier transform - Google Patents

Frequency domain automatic equalizer utilizing the discrete fourier transform

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Publication number
CA1087693A
CA1087693A CA275,215A CA275215A CA1087693A CA 1087693 A CA1087693 A CA 1087693A CA 275215 A CA275215 A CA 275215A CA 1087693 A CA1087693 A CA 1087693A
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Prior art keywords
sample
components
discrete fourier
fourier transform
values
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CA275,215A
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French (fr)
Inventor
Donald A. Perreault
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Xerox Corp
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Xerox Corp
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Priority claimed from US05/706,703 external-priority patent/US4100604A/en
Priority claimed from US05/706,702 external-priority patent/US4106103A/en
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Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B3/00Line transmission systems
    • H04B3/02Details
    • H04B3/04Control of transmission; Equalising
    • H04B3/14Control of transmission; Equalising characterised by the equalising network used
    • H04B3/141Control of transmission; Equalising characterised by the equalising network used using multiequalisers, e.g. bump, cosine, Bode

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)
  • Filters That Use Time-Delay Elements (AREA)

Abstract

FREQUENCY DOMAIN AUTOMATIC EQUALIZER
UTILIZING THE DISCRETE FOURIER TRANSFORM
ABSTRACT

An automatic equalizer for calculating the equal-ization transfer function and applying same to equalize received signals. The initial calculation as well as the equalization proper are conducted entirely within the frequency domain.
Overlapping moving window samplings are employed together with the discrete Fourier transformation and a sparse inverse discrete Fourier transformation to provide the equalized time domain output signals.

Description

1~87~

~C~GlIO~ND OF Tll~ INV~NTION
The invention pertains to frequency-domain automatic equalization for electrical signals used in transmission of information.
- Ideally, it is desirable to transmit electrical signals such that no interference occurs between successive savmbols. In practice, however, transmission channels are bandlimited and intersymbol interference is controlled utilizin~ clocked systems with equalization conventionally perforrmed in the time domain.
~0 Most conventional automatic equalizers operate in a feedback mode so that the effects of changes in the equalizer transfer function are monitored and used to produce further changes in the transfer function to obtain the best output signals. In such systems, the measurements of the output signal are made in the time domain. Typically, the transfer function may be constructed in the time domain by adjusting the tap gains of a tapped delay line during an initial training period prior to actual message transmission.
Examples of such systems are shown in U.S. ~atents 3,37~,473 and 3,292,110.
Frequency domain equalization utilizing time domain adjustments are shown, for example, in the U.S. Patent 3,614, 673 issued to George Su Kang. Kang utilizes frequency domain measurement and calculations to product the time domain impulse response of a transversal filter. The impulse response of the transversal filtcr is applied to set the weights of the transversal filter.
SUMM~RY Ol~ Tl~ INVFNTION
Thc principal object of thc invcntion is to provide an automa~ic cqualizcr, operable complctely in the frequcl-~Y
-2~

1087~9~

domain, to providc both frequency domain measurcments o~ the transmittcd signal and frequency domain corrections to cqualize channel amplitude and phase distortion.
A significant feature of the invention is in the utilization of sliding window samplings of the input waveform to provide a plurality of sample sets each time displaced from successive sets by an amount T/N, where T is the sample set window or time frame and N is the number of samples within a sample set of the input waveform. Each sample set forms a discrete data set which is transformed by an analog discrete Fourier transform (AD~T) into the frequency domain.
The spectral coefficients are corrected in the frequency domain employing component-by-component multiplication using previously calculated correction coefficients computed during an initial tra~ing period where ideal or test pulses are transmitted. The corrected spectral coefficients are inverse transformed using an analog inverse discrete Fourier transform (AIDFT) to provide an output value correspondin~ to one sample within the input waveform sample set. The frequency domain corrected spectral coefficients are computed for each window such that the sliding window sampling produces a new output value of the AID~T N times during the sample period T.
Another significant feature of the invention is in the utilization of time shared multiplying circuits to achieve both the correction factor measurements and subsequent frequency domain adjustment or equalization.
Another objcct of the invention is to provide a method and apparatus for continuously gcnerating thc DFT
cocfficicnts from ovcrlapping sliding window samplc sets of ' - ' ' ' ' , ' ' ' . ' 1(~87~9~
the incoming signal.
Yet another object of the invention is to provide a method and apparatus for producing the effect of an aperiodic convolution of the incoming signal sample sets with the im-pulse response of an equalizer wherein an overlapping sliding window sampling is utilized in conjunction with a sparse - inverse DFT apparatus providing a single time domain output for each incoming sample set.
Thus, in accordance with the present teachings, a frequency domain equalizer is provided for automatically equalizing the discrete Fourier transform components Xn of a received electrica] signal x(t) which comprises:
a) means for storing equalizer transfer components Cn b) means for sampling the received electrical signal x(t) to provide a set of signal samples Xk, k being a sample time index having a value 0, 1 .... N-l, and N being an integer, c) means for calculating the discrete Fourier trans-form of the sample value xk to provide the discrete Fourier components Xn, n = O, 1 ...N-l, d) means for calculating equalized components Yn where Y = C . X n = O, 1 ... N-l, n n n and e) means for calculating the inverse discrete Fourier transform of the set of components Y to provide an output signal corresponding to one sample time index of the received electrical signal.
In accordance with a further aspect of the present teachings, a method is provided of equalizing the discrete Fourier transform components X of a received electrical signal x(t) which comprises the steps of:

108~7~93 a) storing equalizer transfer component Cn, b) sampling the received electrical signal x(t) to provide a set of signal sample values Xk, k being a sample time index having values 0, 1 ... N-l, n being an integer, c) calculating the discrete Fourier transform of the sample values xk~ k=0, ... N-l to provide the discrete Fourier component Xn, n=0, ... N-l, d) multiplying each component Xn by the corresponding component Cn thereby producing equalized components n n n n=0, 1 ........ N-l, e) calculating the inverse discrete Fourier transform of the set of aDmponents Y to provide an output signal corresponding to one sample time index of the received electrical signal.
BRIEF DESCRIPTION OF THE DRAWINGS
These and other features and advantages of the invention :
will become apparent when taken in conjunction with the following ~ specification and drawings wherein:
: FIGURE 1 is a block diagram of the overall theoretical model used in the instant invention;
FIGURE 2 is an analog circuit for performing the discrete Fourier transform of a sample set;
FIGURE 3 is a vector diagram of the DFT components for eight sample points;
FIGURE 4 is a folded vector diagram of the DFT
components of FIGURE 3;
FIGURES 5A-5C are vector diagrams indicating step-by-step operations upon the vectors shown in FIGURE 4;
FIGURE 6 is a tree diagram summarizing the step-by-step operations of FIGURES 5A-5C;

FIGURE 7A illustrates a tree graph for the inverse discrete Fourier transform; :

-f~' -4a-~ .

108769~
FIGURE 7B illustrates a tree graph for the sparse inverse discrete Fourier transform;
FIGURE 7C is an analog implementation of the tree graph algorithm of FIGURE 7B;

-4b-~1 , . ,:.~ . .,`: . , ~0~'7~9~

,, .
~IGUNE 8 is a tree ~raph for the complcte equalization;
~IGURE 9 is an illustration comparing results of an aperiodic convolution with a periodic convolution;
~IGURE 10Ais a schematicfor ~ complex multiplication and holding circuits used in the invention;
; FIGURE 10B illustrates a circuit for producing reference voltages used in the invention;
FIGU~E 11 is a schematic for computing and storing a multiplication parameter used in the invention;
FIGURE 12 is an analog implementation of FIGURE 8 showing the time sharing circuits of the invention;
~IGVRE 13A illustrates a block diagram for providing the DFT coefficients of FIGURE 12 to output means;
~IGURE 13B is a block schematic diagram showing the generation of a power spectrum for thecomponents of the discrete Fourier transformation; and FIGURE 13C is a block schematic diagram showing the generation of a phase spectrum for the components of the dis-crete Fourier transformation.
~20 DETAILED DESCRIPTION OF THE ILLUSTRATIVE EMBODI~FNT ~ -A block diagram of the model of the transmission ~-~
system is shown in FIGURE 1. The system is assumed linear and it is therefore theoretically immaterial where in the system the distorting elements are located. The transfer function H(w) is a composite of all the ideal elements of -tl-e system and is shown in cascade with D(w~, which is a com-posite of all the linear distorting elcments of the system.
It is assumcd that the impulse response h(t) is the ideal symbol and that the information is rcprcsen~ed by the magnitude ~30 and/or polarity of impulscs at the input to ~(w) which impulscs ~ .
-.. ~ .
-`\ -~

` 1~)~7ti~ -are spaced in time according to the requiremcnts o~ h(t) and the detcction proccss. The output of the system is the ~ourier transform of H(w) x D(w), or the convolution of H(t) and d(t), and is no longer ideal. The equalizer is connected in cascade with the distortion network and functions to eliminate the effects of D(w), i.e., the transfer function of the equalizer is l/D(W). The equalizer precedes the decision point at the receiver, and the system is capable of determining D(w) and then producing the transfer function l/D(w) in the ~ 10 transmission path.
'~ ~IGURE 2 shows an analog discrete Fourier transform (ADFT) circuit which produces a set of electrical signals which represent the real and imaginary coef-icients respectively t .
. o samples of the Fourier transform, i.e., frequency spectrum, of the input signal. The input to the ADFT circuit comprises a discrete sample set of, for example,eight samples xO, xl,...x7 of the received signal x(t). The sample set may be taken, for example, from terminals of a tapped delay line 5. The i discrete ith sample set [X]i=xo(i), ~l(i),.. x7(i) is trans-formed by the ADFT circuit into the frequency domain and represented by vectors Xn which are generally complex. Real and imaginary parts of the vector are designated RX and IX
n n respectively. Similarly, RH, IH and RD, ID designate the real and imaginary parts of the transfer frunctions H(w) and D(w).
FIGURE 2 shows a plurality of operational amplifiers 10 having input terminals markcd "+" or "-" for indicating thc additive or su~tractive function perform~d therein. The gain of the amplifiers is indicatcd by the multiplication factor ~30 shown. ~11 amplificrs havc unity gain cxcept thosc having .

~ ' .
' ' ~ -11)~769;~

gain .707 or 0.5. Tlle ADFT circuit shown in FIGUR~ 2 receivcs N samplcs (N=~) of a real input function x(t). For real time samples of x(t), the frequency components Xn for n ~N/2 are the complex conjugates of Xn for n ~ N/2.
Additionally, X0 and XN/2 are real. Consequently, X0 and X4 have real components on]y. Non-redundant information is obtained using the folded spectral coefficients which com-prises vectors X0 and X4 and vectors Xl, X2 and X3. The complex vectors Xl, X2 and X3 specify six parameters, and the real vectors X0, X4 give t~o more parameters yielding a total of eight parameters consistent with the number of sample points of x(t). (Alternatelv, of course, the real values X , X4 and complex values X , X6, X may be used to form the eight required parameters.) A~FT circ~itry is , 15 described more generally, for example, in U.S. Patent 3,851,j 162 to Robert Munoz.
The circuitry arrangement shown in FIGURE 2 is not unique and alternate matrix arrangements may be developed.
The circuit arrangement of FIGURE 2 is derived from an analysis of the vector diagram of the discrete Fourier spectral com-ponents. The DFT components may be defined by Xn = ~ xk wnk (1) where, W = e~i2'~r/N
Equation (1) may be written in terms of real and imaginary components as follows:

N-l , ~Xo Ak-O Xk N-l ~XN/2 = ~ Xk Cost-~rk) (2) . -7-10~7~93 ,......................................................... .

n B ~ xk cos ( 2~rkn ) IX = B x sin (-2~Ykn-) n k=0 k N
;.
~: 5 Assuming that the input time dependent signal x(t) is real, the spectral components may be folded and equation (2) will hold for A = 1, B = 2 inasmuch as the folded coefficlent spectxum will double the magnitude of all frequency components t except the band edges X0 and X / .
FIGURE 3 illustrates a vector diagram for the general - case (x(t) complex) of a N = 8 sample set. The frequency index "n" runs horizontally and the time sample index "k" runs verti-cally with the older sample taken at the zero time reference, ~; k = 0. Each vector represents one term in the summation of equations (1) or (2) for a given value of n. The phase of the vectors is shown by the phase angle, ~ = -2 kn/N, where the vertical direction is taken as the zero phase reference.
Thus, vertical components are rea~ (RXn) and horizontal com-i ponents are im~ginary (IXn). The sample weightings are simply the sample values xk of the time signal x(t) and these samples are used to label each row of the vector diagram to indicate that the magnitude of each vector in the corresponding row has a value Xk. For simplicity of illustration, each vector row is shown as having the same magnitude, i.e., x2 = X3, although in general different magnitudes would be present.
The vertical vector sum for each column, n, gives the spectral component Xn as indicated in ~FIGU~E 3.
To produce the folded spectrum of equation (2) with A = 1, B = 2, the conjugatcs of frequcncics n ~ ~ are addcd to thcir imagcs in the lower range. This folding doublcs thc .~ . --7~

.. . ~.... . . .

EF -F~ -~ 108769~
~ .
ma~nitude o~ all the frequencics except the band edges and ~ results in the single-sided spectrum as shown in FIGU~E 4.
!~ In order to reduee the number o~ operations requirued by equation (2) it is desired to operate on thc m~gnitudes S of the vectors in PIGURE 4 prior to resolving them into their real and imaginary eomponents. The proeess is outlined . . in Table 1 below with speeifie reference to FIGURE 5.
~ ..
. . . .

~ ' .
~, , ' ', .

.

'. _ ::
' 1t)~7~'~3 T~LE 1 :
Stage Ste~ Operation Figure A Add pairwise every fourth 5A
sample.
B Subtract pairwise every 5A
fourth sample.
C Add pairwise every other 5B
result of Step A.
D Subtract pairwise every other 5B
result of Step A.
2 ~2 and I2 are produced- , E Subtract pairwise the odd results SB
of Step B.
F Add pairwise the odd results of 5B
Step B.
G Add pairwise the results of 5C
~- Step C.
~0 is produced.
H Subtract pairwise the results 5C
of Step C.
R4 is produced.
I Multiply result of Step E by 5C
cos 45.
J Miultipoy result of Step F by 5C

K Add result of Step I to (0-4). 5C
Rl is produced.
.i ' ~;~ L Stubract result of Step 1 from 5C
~; (0-4).
R3 is produced.
M Subtract result of Step J from 5C
,;. (2-6).
, 25 I3 is produced.
N Subtract result of Step J from ' negative of (2-6).
~1 is produced. SC

.~ , .

~; .
., .
. -7C-. .

1~ .
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~or ease o~ illustration, the sum of two in-phase vectors in FIG~R~ 5 is shown normalized, i.e., the resulting magnitude is divided by 2.
The operations listed in Table 1 and shown step-by-step in FIGUR~S 5A-5C are summarized in FIGURE 6. In FIGURE
6 each node represents a varia~le and each arrow indicates by its source the variable which contributes to the node at its arrowhead. The contribution is additive. Dotted arrows indicate that the source variable is to be negated before adding, i.e., it is to be subtracted. Change in weighting, i.e., multiplication, is indicated by a constant written close to an arrowhead. For N = 8 only one value is needed for trigonometric we ghting since sin 45 = cos 45 = .707.
It is convenient, however, to muItiply RX and RX by 1/2 rather than multiply all the other components by 2 as indicated in e~uation (2). Thus, equation (2) is effectively taken with A = 1/2 and B = 1. The tree diagram of FIGURE 6 is implemented by the circuitry shown in FIGURE 2, where operational amplifiers 10 replace the various nodes.
The inverse of the DFT may be performed quite straight-forwardly by reversing the DFT of FIGURE 6. The tree graph for the IDFT is shown in FIGURE 7A where the inputs are the real and imaginary spectral components of the non-redundant vectors Xn. In the overlapping sliding window sampling of the instant invention significant circuit simplicity is pro-vided in using only a single output of the IDFT. The simplest approach is to utilize the inverse transforms which require only real inputs thus eliminating complex multiplication.
Accordingly, FIGU]~ 7B shows a "sparse" IDFT ~or,the 4th time sampling, and FIGUR~ 7C 5hows an analog implcmentation of .;~ .

, . -8-,. ~ . .

" ' ' ' ' ~ ' ~ ` ~
~ '7f~9~

FIGU~ 7B. The output signal at thc 4th time sampling is represcntative of the input signal sample X3, for an input sample set xO...xN 1 A subsequent input sample set is taken later, shifted in time by a fixed amount to where S 0 C toG N to provide a sample set xO.. XN 1' and the 4 output sample is again representative of the 4th input tLme sampling, namely X3. The input sample is again taken, shifted by to and the process repeated to provide an overlapping sliding window input. There is therefore a one-to-one cor-respondence between the numbers of samples from the IDFT and the number of signal sample sets. Thus, the output signal can be continuous if the input is continuous, as for example, in utilizing an analog delay line, or the output can be sampled if the input is sampled, as, for example, in utilizing an input shift register.
FIGU~E 8 illustrates a tree graph for the complete ~` equalization process. The DFT of the input sample set xO...xN 1 for N = 8 is computed ir. section 7. The frequency domain equalization is computed in section 9 and the inverse DFT in section 11. As is readily apparent, sections 7 and 11 are identical to FIGURE 2 and FIGURE 7B respectively. The ~; frequency domain equaliztion is achieved by multiplying each ¦ spectral coefficient Xn by a correction factor Cn which is simply a component of the transfer function of the equalizer C ~w) . Thus, i n n n n = 0, 1........... N/2 ~3) Tl-e equalized spectral coef~icients, Yn, are thcn inverse transformed by thc IDFT to provide the time domain representation o~ the input sample set.
The multiplication in equation (3) is pcr~ormcd componcnt-~

-!1 . ~ ' :

E
1~ 1()~7~i9~ :

by-component. Indccd, within the frequency domain the equivalent transf~r function of two transf~r functions in series is the component-by-component product of the two Punc~ions, and there are not cross products as in the case of convolutions. The equalization process of FIGURE 8 takes place entirely in the frequency domain and provides an in-line system for automatically equalizing the incoming signals.
I~ is noted that for an input sample set stored in an input storage means such as a shift register, the samples within a window or sample time frame are designated xO...xk..;
XN 1~ and each subsequent sample se' is shifted relative to the preceding set. Thus, taking the upper ~oundary case (where the sample sets are shifted in time by to = T/N) as an example, if ~Xk~ represents the i-l h sample set and [xlk]
the i sample set, one may write, x' z X +1 k = 0, l...N-2 X'k = new sample k = N-l ' The sample sets overlap and in forming a new sample set, the 20 oldest sample is discarded, intermediate samples shifted, and a new sample taken into the window. This overlapping sampling technique in combination with the sparse inverse DFT is appro-priate as opposed to a complete replacement o~ samples x~...xN 1 ~ by a non-overlapping sample set xN.. x2 inasmuch as multi- - ~
s 25 plication in the frequency domain corresponds to a convolution -in the time domain. Normal message transmission involves apexiodic time functions (the message signal x(t) for example) so that one needs the countcrpart of an aperiodic convolution of the message signal with thc impulsc response of the equalizer.
Thc inhcrent pcriodicity of thc DFT would lcad to a pcriodic .~ :

108'7~3 or circular convolution i~ non-ovcrIapping samples wcre employcd.
The rclationship betwcen the overlapping sampling technique in co~bination with the sparse IDFT and the aperiodic convolution may be seen by way of the example illustrated in - 5 ~IGU~E 9, where, for simplicity, N is taken to be 4. The terms aO...a3 represent the impulse response of the equalizer in the time domain, and the terms xO...x3 represent the samples of the incoming signal x(t). Section A of FIGURE 9 represents the desired aperiodic convolution in the time domain where~s section B represents the periodic convolutions resulting fromthe implied periodicity of the DFT. Section B of FIGURE 9 shows the four distinct product surmations which result from convolving the first sample set which appears in the sampling window, namely, sample set xO,0,0,0 shown at the top of FIGURE 9 with the impulse response of the equalizer aO...a3.
In forming the "results" of the convolution, the terms aO...a3 are reversed and shifted past the incoming pattern which is shown as periodic, namely, OOOxOOOOxO. The second pattern for the convolution is similarly formed using sample set OOxOxl which is made periodic as, OOxOxlOOxOxl. The other - patterns are similarly produced to represent the various results of a periodic convolution of the incoming sample set as it progresses sequentially through the sampling window which is physically the incoming delay line or input shift register.
The "results" of the aperiodic convolution shown in Section A of FIGU~E 9 are formed by cxtending with zeros the incomin~ sequence xO,xl,x2,x3 so that no periodicity is present, i.e., N-l zero values are addcd to thc sample set.
It is sccn that one term o~ the "rcsults" o~ thc apcriodic .. . . . .

, ~08~7~93 convolu~ion i5 idcntical with onc ~ixcd-time index term of a corresp~ndinc3 "result" of a periodic convolution.
Thus, one may uti]ize the DFT together with its inherent implied periodicity to efcctuate the desired aperiodic convolution if one utilizes an overlapping sliding window samplin~ of the incoming signal in combination Wit;l the production of one term of the IDFT. The "sparse" inverse transform is utilized to generate the one time domain output signal as desired.
In general, the number of terms N in the window of the equalizer, i.e., the number of taps on the incoming delay line or the number of stages in the input s~ift register, need not be equal to the number Nl of sa~ple values of the incoming signal. Let the actual input to the 15 equalizer be x(i), i = 0, l,Nl-l where Nl may be greater than N. Let x(i) be extended by at least N-l zero valued samples (we use N for convenience) to form x'(i), i = 0, 1,2---(N+Nl-l). Extending by zeros is equivalent to restricting any repetition of the input signal so that the non-zero re-sponse is separated by at least the length of the equalizer.
Referring again to the boundary case (to = T/N) such that the input sampling rate equals the transform sampling rate, if the signal x'(i) is shifted one sample at a time through an N sample equalizer, N+Nl subsets of N samples each are formed according to:
xk(i) = x'~i+k) i = 0,1,2---(N-l) k = 0,1,2---(N~Nl-l) This relationship can also be written x'~i) ~ N ~ xk(i-k) ~ 0;1;2---(N-l) Sinca thc discrate Fouricr ~ransform is lincar . -12-~ Xk~i-k)~_~ ~ Xk(n)WR nk where xk(i)~-~Xk~n) and WR = exp( Ri). Then k=0 ) k(i k)~ o Cn Xk(n)W nk -5 where c(i) is the IDFT of the frequency domain correction factors Cn, i.e., c(i)~-~Cn, where "~-~" represents the DFT/IDFT operation.
The left side of this result is a summation of periodic con-volutions, but it has already been shown that one element of a periodic convolution is identical to the corresponding element of an aperiodic convolution. By choosing only this single output of the IDFT, the result can be written y'(i) = c'(i)*x'(i) = ~ Fs [Cn Xk(n)WR ]
where Fs indicates a discrete inverse Fourier transform wit;
a single output and c'(i) is c(i) extended with at least Nl-l zero valued samples as implied by an aperiodic convolution.
The phase shift factor WR nk, in the frequency domain indicates that the subsets of the input are taken sequentiaIly, i.e., there is a time shift of the output relative to the transform.
The factor N is eliminated because only one of the N outputs of the inverse transform is taken.
Thus, in the running mode the equalizer is performing an aperiodic convolution of an input signal of arbitrary ~ength with the impulse response of the equalizer, which is the inverse discrete Fourier transform of the frequency domain correction factors, C~. In practice, thc input signal is real so that the negative requencics associated with the Fourier trans~orm are the complcx conjugates of the positivc frequcncics and do not contain any additional information.
Thercore, the discrctc Fouricr transorm is implcmcntcd to .. - :

:
.

1()87~93 produce only positive frequcncies. Thus, the transformation of N san~ples results in N real and imaginary coefficients of N positive frcqucncics, plus dc. The inverse transform is implemented to prodicc only one output and furthermore it is the one which requires only rcal coefficients namely the oth or (2)th output of the inverse transform.
In order to determine the desired equalizer transfer function C(w), one may assume that an isolated impulse or test signal of known magnitude and polarity is transmitted.
This test signal is transmitted during a training period prior to message transmission. In the following description, two test signals are sequentially transmitted to $et up or initialize the equa.'izer to provide the coefficients Cn.
The ideal received signal is h(t), the impulse response of H(W) . However, the actual received test signal is f(t), the impulse response of F(w) = H(w)~D(w). It is intended that C(w) should equal l/D(w) or be the best approximation possible. For the test pulses f(t) one can write the following for each frequency component n.
F(w) = RF + jIF
= (RH + jIH) (RD + jID) = (~IRD - IHID) + j(RHID + RDIH), j =
and l_ = H(w) D(w) F(w) = RH + jIH
~F ~ jIF
= (RH + jIII) s(RF jIF) (~F)2 + (IF)2 = RHT~F + IIIIF + j(T~FIII - ~TIIF) (~F) + (IF) , .

1~)8769;~

The ~D~T performcd at thc receiver can producc a set of coefficients for each input sample sct i reprcsenting RF and IF at discrete frequcncies. The cocfficients of specific interest for set-up or equalizer training purposes are those - 5 which are derived by carrying out the ADFT on the sample set which is found to peak closest in point of time to the peak of the assumed impulse response characteristic h~t), it being understood that the underlying assumption is that a single sample set contains essentially the entire test signal f(t). Of course, since h(t) is known, the coefflcients RH and IH can easily be determined for the frequencies of the coefficieints selected to represen~ RF and IF. With this information a sample version of l/D(w) can be produced and used to equalize any signal which is subsequently transmitted through D(W). The equalization function l/D(w) can be written as 1/D (W) = C (Wj = RC + ;IC where RHRF ~ I3~IF
(RF) + ( IF) RFIH - RHIF
IC = 2 2 (RF) ~ (IF) : (4) RF and IF for each frequency can be obtained by performing the ADFT on the input test signal as shown in FIGURE 2 for an eight frequency discrete spectrum. In order to obtain a result that is not a function of time, f(tj and h(t) must either by synchronized or sampled. If one assumes that samples of f(t), f (k=O...N~l), are used to obtain the R~'s and IF's , then the Rl3 ~ S and I~3 I S can be trcated as constants. Precise phasing of the sampling is not rcquircd bu~ all non-zero samplcs o~ f(t) should be included.

. ~15-1~)87~93 shif~ in the sample phasing merely rcsults in a time sllift in ~he output of the equalization proccss. The circuitry utilized to implement equations (4) is shown in FIGURES lQA, lOB
and 11. A two pass system is utilized in which two ideal or test pulses h(t) are transmitted and received in succession.
The pulses are separated sufficiently in time so as to avoid mutual interference, but are sampled at the same relative instance.
The numerators of RC and IC are obtained using the circuit shown in FIGU~E lOA. The circuit comprises a plurality of switches 12a, 12b, 13a, 13b and a plurality of multipliers 14a, 14b, and 16a, 16b. ~atio~ amplifiers 18 and 20 are shown connected to ~he multiplier outputs and are used to provide signals to two holding circuits 22 and 24. During pass 1, when the first ideal pulse is received, switches 12 and 13 are placed at position 1, designated Pl in the figures, and constant voltages corresponding to RH, IH are connected to multipliers 14 and 16. The resulting outputs of operational amplifiers 18 and 20 are stored in holding circuits 22 and 24.
Holding circuit 22 stores a value corresponding to RFIH - IFRH
and holding circuit 24 stores a value corresponding to RFRH +
IFIR. During pass 2, the second ideal pulse is received and switches 12 and 13 are placed at position 2, designated P2 in the figures. The values stored in the holding circuits 22 and 24 are then connected to multipliers 14 and 16.- The subsequent output of the operational amplifiers 18 and 20 is given respectively by RII((RF) + (IF)2) and IH((RF) + (IF) ).
~hcse valucs nced only be multiplied by the factor l/((RF) +
,(IF) ) to obtain thc desircd equalized frequcncy domain :30 valuc5 o thc ideal si~nal Rll an~

-lG-.

1~:)87693 The constant values for the ideal test signal h(t) may be provided as outputs of potentiometers as shown in ~IGURE l~;. Only the circuit for Hl and H2 is illustrated in FIGURE 10~ although any required number of values may be provided.
The multiplying factor l/((RF) + (IF) ) is obtained during the pass 2 operation of the system -taking the output from operational amplifiers 18 and 20 and using the circuitry shown in FIGURE 11. FIGURE 11 shows a servo and hold circuit 26 and a multiplier 30. The servo and hold circuit 26 com-prises an operational amplifier 32, motor 33, and adjustable potentiometer 34, switch 35 and holding circuit 36 all of which are connected in seriatim for connect~on back to multi-plier 30. Potentiometer 34 is controlled in a divider network by motor 33 to provide a cont~olled voltage through switch 35 and holding circuit 36to multiplier 30. Inasmuch as the known ideal pulse is again received during pass 2, - the output of operational amplifier 32 is forced to the desired multiplication factor using the servo gain control arrangement shown with RH as a reference voltage. This circuit automatically provides the multiplying factor l/~(RF) + (IF)2) which is stored in holding circuit 36.
With RC and IC available any signal subsequently transmitted through the system, i.e., the message signal x(t), can be equalized for the distortion D(w) by again employing the same basic circuit of FIGuRElQ~ having switches 12 and 13, operable at position P2, and the circuitry of FIGVRE 11 having ~-switch 35 operable at position Pl. llolding circuits 22, 24 and 36 storc values which corrcspond, for each frequcncy, to ~xact cqualizatlon transfer ~unctions. Thus, the incoming ~ ~ -17-lV8'76~

message signal xlt) is samplcd to produce the samples x~
wherc k = 0... N-l . The samplcs xk are tr~nsformcd by a DFT to provide spectral components X for n = 0...N-l.
The spectral components are equalized toproduce equalized spectral components Yn = Cn Xn, n = 0.. N-l and the sparse inverse DFT is taken for Yn to produce a single time domain output sample Yk corresponding to the original input sample Xk. Employing non-redundant frequency components for the discrete Fourier transforms, where N is an even integer, simplifies the equalization in that circuitry need only be provided for N/2 spectral components. Thus, the DFT cir-cuitry provides components X for n = 0, l...N/2 and, similarly the components Cn and Yn need only be provided for n = 0, l...N/2. Sliding window sampling of the input signal x(t)i wherein samples are taken every T/N h interval along the delay line 5 (FIGURE 2), allows utilizing a single output from the IDFT corresponding to each sample set for each window. Consequently, N output signals are provided at the output of the IDFT for each N input sample sets.
The circuitry shown in FIGURE 12 represents the analog circuit implementation of the flow diagram of FIGURE
8, and incorporates therein the circuits of FIGURES 7C, 10 and 11. Specifically, the input sample data is taken off a delay line 40 and sample sets i, i + 1... are taken shifted in time relative to one another to provide the sliding window.
The DFT, frequency adjustment and sparese inverse DFT are performed for cach sample set i, i ~ 1... Operational ampli~icrs 41 are similar to those shown in FIGURE 2, and the output signals corresponding to the discretc frcquency componcnts of tl~c transform X arc providcd as inputs to the ;

~-- .

1(!~'76~

equaliz~r proper. For each r~al and imaginary pair, RX
IXn, circuits similar to that shown in FIGURE:S lOA and 11 are provided. The operational amplifier 2-0 and the multipliers 16a, 16b of FIGURE lOA`may be time shared for frequency components n = 1, 2 and 3 so that only multipliers 14a, 14b, operational amplifiers 18 and holding circuits 22, 24 need to be separately provided for each frequency channel. FIGURE 12 shows a time-shared circuit 42 comprising multipliers 44a, 44b and operational amplifier 46 connected equivalently and corresponding to multipliers 16a, 16b and operational amplifier 20 of FIGURE lOA. The output of circuit 42 is fed to a multiplexer 50 for sequential application of the signal values RXnR~In + IXnIHn to corresponding holding circuits 24-1, 24-2 and 24-3 during a pass 1 operation.
These holding circuits correspond to the holding circuit 24 of the single frequency embodiment of FIGURE lOA. Similarly, holding circuit 22 of FIGURE lOA corresponds to holding circuits 22-1, 22-2 and 22-3 of FIGURE 12, aiid-mu~tip~;Iers 14a and 14b of FIGURE 10 correspond to multipliers 14a-1 -through 14a-3 and 14b-1 through 14b-3 of FIGURE 12. A
plurality of servo and hold circuits 26 and multipliers 30 are also provided in FIGVRE 12 to correspond to the apparatus of ~IGU~E 11.
The inputs to time-shared circuit 42 are provided by another multiplexer 52 which provides the appropriate con-stant reference voltages Il~n and Rl~n for n = 1, 2 and 3.
Signals RXn and IXn for n = 1, 2, 3 are also fed to the input of multiplexer 52 although, for simplicity, only the signal IXl is explicil:ly so illustratcd. The multiplcxcrs 50 and ~-52 arc controllcd by initializing circuit means comprising ~. .

7~93 set-up switch 54, a peak detcctor 56, c-~unter 58, switch actuating means 60 and, clock means 62. The counter 58 may be a simple two stage counter serving to actuate the - clock means 60 and pxovide enabling pulses to multiplexers 50 and 52 upon detection of the first of the two test pùlses. The clock means 62 provides a clock pulse to the switch actuating means 60 and multiplexers 50 and 52.
These clock pulses are typically delayed with respect to the peak of the incoming test signal to allow the test signal to be positioned, for example, near the middle of the delay line 40. Switch actuating means 60 controls sets of switches 64, 66 and 68. Switch set 64 correspond$ to switches 12a and 13a in FIGURE lQA which are shown in position P2 for the "run" mode. Switch set 66 corresponds to switch 13b of FIGURE 10 and is similarly shown in position P2.
Switch set 68 corresponding to switch 35 of FIGURE 11, and position Pl, is here identical to the "run" position.
During pass 1, the first test pulse is received in the equalizer, set-up switch 54 is closed and all switch sets 64, 66 and 68 are set to position Pl. During pass 2, the second test pulse is received and all switches are placed in position P2. Subsequently, all switches are set in their run position and set-up switch 54 is open. For switch sets 64 and 66, the run position is identical with position P2 of the switches, whereas for switch set 68, the run position is idcntical with position Pl.
The DFT coefficients RXn and IXn may be fed directly to output mcans shown in FIGURE 13 which may comprise for examplc an oscilloscopc display or appropria~e recoxding or proccssing mcans. In such a case, overlapping sliding window ~ -20-1087~93 sampling enables continuous display, recordation or pro-cessing of the spectral coefficients. In addition, the com-ponent powcr spectrum may be generated and provided to output means using the multiplying and summing apparatus of FIGU~E
13B. Further, the spectral coefficients RX and IX of n n FIGURE 12 may be fed to a component phase spectrum apparatus - as shown by FIGURE 13C to provide a phase display, recordation ~r processing thereof.
. The switches utilized in the instant invention may comprise solid state switching devices such as, for example, transistors. In such a case the switch actuating means 60 comprises appropriate driving circuits. Additionally, the two phases of the equalization process could be performed with one set cf time samples if they (or their corresponding frequency coefficients) are stored instead of two successive pulses, as discussed above. If the received signals are noisy, the average of a number of received pulses may be -~
used to reduce noise effects. Averaging can be applied either to the time samples or to their corresponding frequency coefficients during the set-up interval (passes 1 and 2).
An averaging circuit (not shown), for example a pair of low pass filters, could be time dhared between the fre~uencies.
In a facsimile system the sync pulses used to achieve line synchronization of the scanning and printing mechanisms can provide an ideal set of known pulses for the purpose of setting up the automatic equalizer. Fur~hermore, if the sync pulses are continucd ~-hrought the transmission of facsimile information thc automatic equalizcr settings can be rcgularly updated. ~hc systcm can thus bc adap~ivc in the sense that the equalizcr can be madc to track changcs in channcl charac-~ . -21-.

10~69;~

teristies whieh oceur during the transmission o a doeument.
In utilizin~ an analog tapped delay line to provide tl)e input sets Xk, the equalizer bandwidth is dctermined by the tap or sample spaeing,~r = -, and is given ~y BW = 1/2r =
2T. In such systems filterin~ may be used to limit the band-width of the incoming sample to BW to avoid aliasing. Images do not occur in an analog delay line since samples are conti~-uously available and the sampling rate may be thought of as infinite. If the input sample set is taken from stages of a shift reglster, for example, the sampling rate must be at least the Nyquist rate to avoid aliasing. It is important to note that the input sampling rate may not necessarily be the same as the samp ing rate seen by the DFT since one could ..
eonnect, for example, every other stage of the input shift register to the DFT input eireuitry. The input sampling rate determines the rate at which the output samples appear and the image loeations of the output signal spectrum. The transform sampling rate determines the equalizer transfer funetion whieh is eontinuous in the analog delay line case sinee the transform sampling frequency, -, is twice the band-width BW = 2T. The equalization transfer function may also be made eontinuous with shift registers or sample and holding eireuits at the input if the transform sample interval is taken at N seconds using a total of N inputs and if the transform sampling rate, -, is seleeted (eonsistent with the Nyquist eriteria) to be 21W ~ where Wmax is the maximum frequency eomponent of the incoming signal x(t). If the . .. .. . . . .
~ number of samples taken during time T is N, then the equal-_ .. ~ . . .. . .... . . ... .
ization will exactly cancel the distor~ion of N/2 positive .
requencies, plus de,evenly space by -, and the impulse 1087~;93 responsc of thc equalizcd systcm will be exactly corrcct at N equally spaced points. This type of equalizer is thus ideally suitcd to digital transmission; howcver, the equal-ization function will be a smooth curve between the sample frequencies so that it is also well suited for non-digital transmîssion such as facsimile and video. Thus, although control of the equalizer occurs at discrete points, the transfer function itself is continuous from dc to BW = 2T
and beyond, as an image, where - is the transform sample spacing. The response in between the control frequencies is a result of the continuous overlapping "windowing" in the time domain.
If the sample set does not include all the non-zero samples of the unequalized system response, the equalization between the sample frequencies will not be good enough to - eliminate intersymbol interference in the digital sense. If the samples are not close enough the equalization bandwidth will be too narrow. The equaliz-tion function is periodic in the frequency domain with period of 1/~-. The sample spacing is easily changed without changing the system complexity.
However, if the number of samples is increased the circuit complexity increases faster than linearly, since the number of nodes in the discrete Fourier transform algorithm used is N Lg2N-While the invention has been described with reference to a particular cmbodiment thereof it is apparent that modifi-cations and improvcments may be made by those of skill in the art without departing from the spirit and scope of the invcntion.

~23--. . . .. . ,, . . . . - . .. . . .
. .

Claims (26)

WHAT IS CLAIMED IS:
1. A frequency domain equalizer for automatically equalizing the discrete Fourier transform components Xn of a received electrical signal x(t) comprising:
a) means for storing equalizer transfer components Cn, b) means for sampling said received electrical signal x(t) to provide a set of signal sample values Xk, k being a sample time index having values 0, 1,...N-1, and N
being an integer, c) means for calculating the discrete Fourier transform of said sample values xk to provide said discrete Fourier components Xn, n = 0, 1...N-1, d) means for calculating equalized components Yn where Yn = Cn . Xn n = 0, 1...N-1, and e) means for calculating the inverse discrete Fourier transform of the set of components Yn to provide an output signal corresponding to one sample time index of said received electrical signal.
2, A frequency domain equalizer as recited in Claim 1 further comprising:
a) means for sampling said signal x(t) to provide a plurality of sets, i, of sample values Xk, k = 0, 1...N-1, said values xk corresponding to samples of the signal x(t) time displaced by an amount ? from one another where T is a sample time frame and N is an integer, b) said sampling means providing the ith sample set time delayed from the i-1th sample set by an amount t0 where, 0< t0 ? ? , thereby providing an overlapping sliding window sampling of said signal x(t), and c) means for generating the discrete Fourier trans-form components corresponding to each sample set of values Xk of said plurality of sample sets.
3. A frequency domain equalizer as recited in Claim 2, wherein said sampling means comprises an analog delay line having taps spaced an amount ? from one another, said sample values Xk provided at said taps.
4. A frequency domain equalizer as recited in Claim 3, further comprising means for displaying said generated discrete fourier transform components.
5. A frequency domain as recited in Claim 3, further comprising means for generating a phase spectrum from said generated discrete fourier transform components and means for dis-playing same.
6. A frequency domain as recited in Claim 2, wherein said sampling means comprises a shift register for storing said i-1th sample set of values xk, said ith sample set of values, x'k, formed by shifting said values xk in said shift register such that, X'k = xk+1 k = 0, 1...N-2 and x'N-1 is a new sample value of the signal x(t) displaced in time from the sample value x'N-2.
7. Apparatus as recited in Claim 2, wherein said values xk are real, N is an even integer and the discrete fourier transform components, xn, are generated for n belonging to one of the groups n = 0, 1...N/2 and n = 0, N/2, ? + 1, ? + 2,...N-1.
8. Apparatus as recited in Claim 2, wherein the sampling rate of said sampling means is given by N/T, and said sampling rate is greater than or equal to , where Wmax is the maximum frequency component of the signal x(t).
9. A frequency domain equalizer as recited in Claim 1 further comprising:
a) means for replacing the sample set Xk, k = 0,1...N-1 by a sample set shifted in time an amount tO, O < tO ? ? where T is the sample set time frame, b) means for calculating the discrete Fourier transform components xn of the shifted sample set, c) means for calculating equalized components Yn for said shifted sample set, d) means for calculating the inverse discrete Fourier transform of the set of components Yn for said shifted set to provide another output signal corresponding to said one sample time index of said received electrical signal.
10. A frequency domain equalizer as recited in Claim 9, wherein said sample values have only real values, N
is an even integer and said discrete Fourier transform, said inverse discrete Fourier transform and said equalized components are calculated for n ranging in one of the groups n = 0, 1...N/2 and n = 0, N/2, ? + 1, ? + 2,...N-1.
11. A frequency domain equalizer as recited in Claim 10, wherein said means. for calculating said inverse discrete Fourier transform comprises means for calculating only one output signal per sample set.
12. A frequency domain equalizer as recited in Claim 11, wherein said one output signal of the inverse dis-crete Fourier transform corresponds to either the Oth or the n/2th time sample index.
13. A frequency domain equalizer as recited in Claim 11 wherein said means for calculating said inverse discrete Fourier transform comprises a sparse inverse dis-crete Fourier transform circuit having only real parts of said components Yn as inputs thereto.
14. A frequency domain equalizer as recited in Claim 9 where N/T is selected to be greater than or equal to where wmax is the maximum frequency component of the signal x(t).
15. A frequency domain equalizer for automatically equalizing the discrete Fourier transform components Xn of a received electrical signal x(t) transmitted through a transmission channel comprising:
a) means for storing distortion equalization correction factors, Cn, associated with said signal x(t), b) means for sampling said signal x(t) to pro-vide a plurality of sets, i, of sample values Xk, K = 0, 1...N-1, said values xk corresponding to samples of the signal x(t) time displaced by an amount ? from one another where T
is a sample time frame and N is an integer, c) said sampling means providing the ith sample set time delayed from the i-1th sample set by an amount to where, o<t0??, thereby providing an overlapping sliding window sampling of said signal x(t), d) means for generating the DFT components corresponding to each sample set of values xk of said plurality of sample sets, e) means for multiplying said generated components Xn by said factors Cn for each of said sets i, such that Yn = Xn?Cn and f) means for generating the inverse DFT of the set of components Yn to provide an output signal corresponding to one value of k for each set, i, of values xk, said value of k being the same value for each set i.
16. A frequency domain equalizer as recited in Claim 15, wherein said correction factors Cn are thediscrete fourier transform components of the impulse response function of the equalizer
17. A frequency domain equalizer as recited in Claim 16, wherein said means for generating the inverse discrete fourier transform comprises means for providing only real parts of said components Yn as inputs thereto.
18. A frequency domain equalizer as recited in Claim 16, wherein the sampling rate of said sampling means is given by N/T, and said sampling rate is at least equal to the Nyquist sampling rate for said received signal x(t).
19. A method of equalizing the discrete Fourier transform components Xn of a received electrical signal x(t) comprising the steps of:
a) storing equalizer transfer components Cn, b) sampling the received electrical signal x(t) to provide a set of signal sample values xk, k being a sample time index having values 0, 1...N-1, N being an integer, c) calculating the discrete Fourier transform of said sample values xk, k = 0,...N-1 to provide the discrete Fourier components Xn, n = 0,...N-1, d) multiplying each component Xn by the corresponding component Cn thereby producing equalized components Yn = Cn.Xn n = 0,...N-1, e) calculating the inverse discrete Fourier transform of the set of components Yn to provide an output signal corresponding to one sample time index of the received electrical signal.
20. A method as recited in Claim 19 further com-prising the steps of:
a) replacing the sample set xk, k = 0,...N-1 by a sample set shifted in time an amount tO, O<tO??, where T is the sample set time frame, b) calculating the discrete Fourier transform components Xn of the shifted sample set, c) providing equalized components Yn for the shifted sample set, d) calculating the inverse discrete Fourier transform of the set of components Yn for said shifted sample set to provide an output signal corresponding to said one sample time index of said received electrical signal.
21. A method as recited in Claim 20, wherein said sample values have only real values, N id an even integer and said discrete Fourier transform, said inverse discrete Fourier transform and said equalized components are calculated for n ranging in one of the groups, n = 0, 1...N/2 and n = 0, N/2, ? + 1, ? + 2,...N-1.
22. A method as recited in Claim 21, wherein said one time sample index of said inverse discrete Fourier trans-form is either the Oth or the N/2th time sample index.
23. A method of equalizing the discrete Fourier transform components X of a received electrical signal x(t) comprising the steps of:
a) storing distortion equalization correction factors, Cn, associated with said signal x(t), b) sampling said signal x(t) to provide a plurality of sets, i, of real sample values xk, k = 0, 1...N-1, said values xk corresponding to samples of x(t) time displaced by an amount ? from one another where T is a sample time frame and N is an integer, c) delaying the ith sample set with respect to the i-1th sample set by an amount t0 where 0 <t0??, thereby providing overlapping sliding window sampling of said signal x(t), d) generating the discrete Fourier transform of said sample values xk, k - 0,...N-1 to provide the discrete Fourier components Xn, n = 0,...N-1, e) multiplying said generated components Xn by said factors Cn for each of said sets i, such that Yn = Xn?Cn and f) generating the inverse discrete Fourier transform components Yn to provide an output signal corresponding to one value k for each set of values xk, said value of k being the same value for each set i.
24. A method as recited in Claim 23, wherein correction factors Cn are the discrete Fourier transform components of the impulse response function of the equalizer.
25. A method as recited in Claim 24, further comprising the step of generating the inverse discrete Fourier transform by providing only real parts of said components Yn as inputs thereto.
26. A method as recited in Claim 24, wherein said step of sampling comprises sampling at a rate given by N/T
wherein said sampling rate is at least equal to the Nyquist sampling rate for the signal x(t).
CA275,215A 1976-07-19 1977-03-31 Frequency domain automatic equalizer utilizing the discrete fourier transform Expired CA1087693A (en)

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US706,703 1976-07-19
US05/706,703 US4100604A (en) 1976-07-19 1976-07-19 Frequency domain automatic equalizer utilizing the discrete Fourier transform
US05/706,702 US4106103A (en) 1976-07-19 1976-07-19 Derivation of discrete Fourier transform components of a time dependent signal

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JPS5888914A (en) * 1981-11-20 1983-05-27 Hiroshi Miyagawa Automatic equalizer
JPS5888915A (en) * 1981-11-20 1983-05-27 Hiroshi Miyagawa Frequency sampling type automatic equalizer
US4813001A (en) * 1987-05-29 1989-03-14 Schlumberger Systems, Inc. AC calibration method and device by determining transfer characteristics

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US3292110A (en) * 1964-09-16 1966-12-13 Bell Telephone Labor Inc Transversal equalizer for digital transmission systems wherein polarity of time-spaced portions of output signal controls corresponding multiplier setting
US3375473A (en) * 1965-07-15 1968-03-26 Bell Telephone Labor Inc Automatic equalizer for analog channels having means for comparing two test pulses, one pulse traversing the transmission channel and equalizer
US3582879A (en) * 1969-04-25 1971-06-01 Computer Mode Corp Communication channel equalization system and equalizer
US3614673A (en) * 1970-05-28 1971-10-19 Bunker Ramo Technique for utilizing a single pulse to set the gains of a transversal filter
US3851162A (en) * 1973-04-18 1974-11-26 Nasa Continuous fourier transform method and apparatus
US4027257A (en) * 1976-06-01 1977-05-31 Xerox Corporation Frequency domain automatic equalizer having logic circuitry

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GB1585836A (en) 1981-03-11
DE2729336C2 (en) 1988-08-11
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IT1086161B (en) 1985-05-28

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