Pulse or digital communications – Equalizers – Automatic
Reexamination Certificate
2000-03-07
2002-08-13
Pham, Chi (Department: 2631)
Pulse or digital communications
Equalizers
Automatic
C375S229000, 37
Reexamination Certificate
active
06434193
ABSTRACT:
BACKGROUND OF THE INVENTION
This invention generally relates to apparatus and methods for waveform equalization coefficient generation for use in multivalued digital microwave communication.
In recent years, there has been a tendency towards the multivaluing of modulation/demodulation of the digital microwave communication type for the efficient use of frequency. In addition to modulation techniques such as QPSK and 16QAM, the use of 64QAM and 256QAM has just started.
As the multivaluing of modulation/demodulation advances, effects due to signal distortion or the like occurring in communication paths become relatively serious. Accordingly, technology, having the ability to guarantee that correct signals are received at the receiving side, plays an important part, and automatic adaptive equalizers to achieve transmission path equalization on the receiving side have been proposed.
Transmission path equalization is first described below.
FIG. 16
shows a transmission path and an equalization model thereof. As can be seen from
FIG. 16
, signals from the transmitter, which vary according to the characteristics of a transmission path, are received together with noise. On the receiving side, an equalizer, serially arranged before the receiver, equalizes a received signal X
0
to a desirable signal Z
0
for the receiver. When noise is negligible, it is sufficient to employ an equalizer opposite in characteristic to the transmission factor of the transmission path. On the other hand, when noise is great to a certain extent, it is necessary to perform design of an equalizer in consideration of noise. A practically-used equalizer is formed by a digital filter, which is called a digital equalizer.
FIG. 17
is a block diagram of a digital filter. In
FIG. 17
, X
0
is an input received signal applied from through a transmission path. X
1
to X
m
are received signals having a delay, produced by each delay element, with respect to X
0
. C
0
to C
m
are equalization coefficients. X
0
is multiplied by C
0
by multiplier. Likewise, X
1
-X
m
are multiplied by C
1
-C
m
, respectively. The multiplying results are summed together by adder and the sum is provided as an equalization signal, Z
0
.
A mechanism of multiplying together a delay signal and an equalization coefficient, employed in a digital filter, is known in the art as a tap. By summing together products produced by respective taps, Z
0
is obtained. The equalization coefficients C
0
-C
m
best suited for signal restoration are then calculated by a waveform equalization coefficient generator.
An algorithm of generating equalization coefficients is now described below.
As previously described, signals from a transmitter, which vary according to the transmission path characteristic, arrive at a receiver with noise. If the characteristic of a transmission path is constant, then it is sufficient to calculate the opposite transmission path characteristic and use a fixed equalization coefficient that implements the calculated opposite transmission path characteristic. However, in a system in which the effects of noise and characteristics change with time, it is necessary to carry out sequential equalization coefficient updating according to the state of received signals. An automatic adaptive type algorithm is used in equalization coefficient updating. Practically, based on an equalization coefficient in the preceding state, the subsequent equalization coefficient is computed. In this case, a specific evaluation index is set, and equalization coefficient updating processing is carried out in order that the set value is minimized. A typical algorithm of such a type is the LMS (least means square) algorithm.
In the LMS algorithm, a means square error is used as an evaluation index for equalization coefficient. More specifically, the equalization coefficient is given by
C
n+1,m
=C
n,m
−&agr;×X
m
×e
0
(Expression 1)
where n is the number of times the equalization coefficient is updated, m is an equalization coefficient's tap number, e
0
is Z
0
−x
0
(x
0
is a pre-transmission signal), and &agr; is the step size.
If the signal X
m
and the error data e
0
are complex-expressed by
X
m
=X
m(r)
−jX
m(i)
e
0
=e
0(r)
+je
0(r)
where (r) represents the real part data and (i) represents the imaginary part data, then the following is obtained.
X
m
×e
0
=(
X
m(r)
×e
0(r)
+X
m(i)
×e
0(i)
)+
j
(
X
m(r)
×e
0(i)
−X
m(i)
×e
0(r)
)
Accordingly, Expression (1) becomes the following.
C
n+1,m(r)
=C
n,m(r)
−&agr;×(
X
m(r)
×e
0(r)
+X
m(i)
×e
0(i)
) (Expression 2)
C
n+1,m(i)
=C
n,m(i)
−&agr;×(
X
m(r)
×e
0(i)
−X
m(i)
×e
0(r)
) (Expression 3)
However, in actual transmission systems, the pre-transmission signal, x
0
, is unknown at the receiving side and therefore cannot be used to calculate the error data e
0
. For this reason, it is designed such that estimation for pre-transmission signals is performed on the receiving side and waveform equalization processing is carried out using the estimated value as a reference signal. This is called a blind algorithm.
Practically, it very hard to understand the fact that updating by a blind algorithm, when it is repeated several thousand times under specific conditions, results in equalization coefficient convergence and signal waveform equalization is accomplished. A commonly-used waveform equalization coefficient generator performs arithmetic operations as shown in Expressions (2) and (3) for equalization coefficient updating.
However, there are the following problems with conventional waveform equalization coefficient generators.
When performing equalization coefficient updating according to Expressions (2) and (3), it is necessary to prepare error data for respective signal data. This enormously increases the storage capacity of memory necessary for storing the error data and thereby increases the size of circuitry.
In addition to the above-described problem, there is another problem that many arithmetic units are required for performing equalization coefficient updating. For instance, six multipliers, and four adders or subtracters are necessary. A conventional waveform equalization coefficient generator becomes large in circuit size and consumes more electric power.
SUMMARY OF THE INVENTION
Bearing in mind the above-described problems with the prior art techniques, the present invention was made. It is therefore a general object of this invention to provide an improved waveform equalization coefficient generator which is smaller in circuit size and which consumes less electric power in comparison with conventional ones.
The present invention provides the following waveform equalization coefficient generators.
In a digital equalizer for waveform equalizing a signal modulated by a multivalued QAM (quadrature amplitude modulation) technique and transmitted and a pre-transmission signal, the present invention provides a waveform equalization coefficient generator for generating equalization coefficients for respective taps of digital filters which perform signal waveform equalization wherein said waveform equalization coefficient generator carries out updating of an equalization coefficient by means of separate updating of real part data and imaginary part data of said equalization coefficient and wherein a common arithmetic unit is used to perform arithmetic operations for updating said real part data and said imaginary part data by adaptively selecting data required in said arithmetic operations.
Such arrangement achieves a considerable simplification in apparatus configuration and thereby reduces not only the size of circuit but also the consumption of electric power.
The above-described waveform equalization coefficient generator comprises:
(a) an error data generation unit for generating error data necessary to update an equalization coefficient to a received signal; and
(b) a complex
McDermott & Will & Emery
Nguyen Dung X
Pham Chi
LandOfFree
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