Pulse or digital communications – Equalizers – Automatic
Reexamination Certificate
2000-04-04
2004-01-06
Vo, Don N. (Department: 2631)
Pulse or digital communications
Equalizers
Automatic
C375S229000, C375S232000, C375S233000, C375S236000, C708S323000
Reexamination Certificate
active
06674795
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to communication systems, and more particularly to time-domain equalization of a communication channel.
BACKGROUND OF THE INVENTION
FIG. 1
shows a typical communication system
100
having a local/central unit
102
in communication with a remote unit
106
over a communication medium
104
. Generally speaking, the communication medium
104
supports bi-directional communications between the local/central unit
102
and the remote unit
106
. For convenience, communications from the local/central unit
102
to the remote unit
106
are said to be “downstream” communications, while communications from the remote unit
106
to the local/central unit
102
are said to be “upstream” communications. Thus, the communication medium
104
typically supports a downstream channel over which the local/central unit
102
communicates to the remote unit
106
and an upstream channel over which the remote unit
106
communicates to the local/central unit
102
. The upstream channel and the downstream channel may share the same physical communication link or occupy different physical communication links. When the upstream channel and the downstream channel share the same physical communication link, the upstream channel and the downstream channel may occupy the same frequency band (e.g., analog modem channels) or different, typically non-overlapping, frequency bands (e.g., ADSL or cable modem channels). The upstream and downstream channels may be symmetric or asymmetric.
Within the communication system
100
, it is common for the upstream and downstream communication channels to have dispersive characteristics. Specifically, each channel has a particular impulse response that disperses signals carried over the channel by extending the effects of each signal over a period of time. In many cases, the dispersive nature of the channel causes various distortions of the signals carried over the channel, such as Inter-Symbol Interference (ISI), Inter-Carrier Interference (ICI), and other distortions.
FIG. 2A
shows a representation of an exemplary transmit signal
210
that is transmitted over a dispersive channel, for example, by the local/central unit
102
. The exemplary transmit signal
210
includes two symbols, S
1
(
211
) and S
2
(
212
), that are transmitted over the dispersive channel with no inter-symbol delay.
FIG. 2B
shows a representation of an exemplary receive signal
220
that is received over the dispersive channel, for example, by the remote unit
106
, when the symbols S
1
(
211
) and S
2
(
212
) are transmitted over the dispersive channel with no inter-symbol delay. As shown in
FIG. 2B
, the transmitted symbol S
1
(
211
) is dispersed by the dispersive channel such that the received symbol R
1
(
221
) overlaps the beginning of the symbol S
2
(
212
). This causes ISI between the symbols S
1
(
211
) and S
2
(
212
) and therefore corruption of the symbol S
2
(
212
).
One way to avoid or reduce ISI is to add a sufficient amount of inter-symbol delay to the transmitted symbols so that the received symbols do not overlap.
FIG. 3A
shows a representation of an exemplary transmit signal
310
that is transmitted over a dispersive channel, for example, by the local/central unit
102
. The exemplary transmit signal
310
includes two symbols, S
1
(
311
) and S
2
(
312
), that are transmitted over the dispersive channel with inter-symbol delay.
FIG. 3B
shows a representation of an exemplary receive signal
320
that is received over the dispersive channel, for example, by the remote unit
106
, when the symbols S
1
(
311
) and S
2
(
312
) are transmitted over the dispersive channel with inter-symbol delay. As shown in
FIG. 3B
, the transmitted symbols S
1
(
311
) and S
2
(
312
) are dispersed by the dispersive channel. However, because of the inter-symbol delay in the transmitted signal, the received symbols R
1
(
321
) and R
2
(
322
) do not overlap. As a result, there is no ISI between the symbols S
1
(
311
) and S
2
(
312
).
While the inter-symbol delay added to the transmitted signal eliminates (or at least reduces) ISI, there are detriments to employing such inter-symbol delay. For one, the inter-symbol delay reduces the efficiency of the transmitted signal in that fewer symbols (and therefore less data) are transmitted over a particular period of time. Also, the inter-symbol delay can cause cross-talk between channels carried over a common physical communication link. Thus, inter-symbol delay may be impractical for certain applications.
Another way to avoid or reduce ISI is to “shorten” the impulse response of the channel. This is typically done using a time-domain equalizer (TEQ) at the receiving end of the communication channel. The TEQ is a short Finite Impulse Response (FIR) filter that is used to time-compress (shorten) the impulse response of the communication channel. In addition to shortening the impulse response of the channel, the TEQ also tends to “flatten” the channel and amplify noise. The effectiveness of the TEQ has a direct impact on overall performance, and therefore the TEQ design and the TEQ coefficients must be carefully determined. There are typically different design considerations for time-domain equalization of the upstream and downstream channels. Also, whether the implementation platform is memory or processing power limited (or both) plays an important role in the TEQ design.
The following references are hereby incorporated herein by reference in their entireties, and may be referenced throughout the specification using the corresponding reference number. It should be noted that the reference numbers are not consecutive.
[1] John A. C. Bingham,
ADSL, VDSL and Multicarrier Modulation
, John Wiley & Sons, 2000.
[2] J. S. Chow, J. M. Cioffi, and J. A. C. Bingham “Equalizer Training Algorithms for Multicarrier Modulation Systems,”
ICC
1993, May 1993, pp. 761-765.
[3] D. D. Falconer and F. R. Magee, Jr., “Adaptive Channel Memory Truncation for maximum Likelihood Sequence Estimator,”
B.S.T.J
. November 1973, pp. 1541-1562.
[5] D. T. Lee, B. Friedlander, and M. Morf, “Recursive Ladder Algorithms for ARMA Modeling,”
IEEE Trans. Automat. Contr
., vol. AC-27, No. 4, August 1982.
[6] P. J. W. Melsa, R. C. Younce, and C. E. Rohrs , “Impulse Response Shortening for Discrete Multitone Transceivers,”
IEEE Trans. Commun
, vol. 44, No. 12, pp. 1662-1672, December 1996.
[7] N. Al-Dhahir, A. H. Sayed, and J. M. Cioffi, “Stable pole-zero modeling of long FIR filters with application to the MMSE-DFE,”
IEEE Trans. Commun
., vol. 45, No. 5, pp. 508-513, 1997.
[8] N. Al-Dhahir, A. H. Sayed, and J. M. Cioffi, “A high-performance cost-effective pole-zero MMSE-DFE,”
Proc. Allerton Conf. Commun., Contr., Computing
, September 1993, pp. 1166-1175.
[10] Steven M. Kay,
Modern Spectral Estimation: Theory and Application
, Prentice Hall, 1988.
[11] Peter E. Caines,
Linear Stochastic Systems
, John Wiley & Sons, 1988.
[13] N. Al-Dhahir and J. M. Cioffi, “A low complexity pole-zero MMSE Equalizer for ML Receivers,”
Proc. Allerton Conf. Commun., Control, Comput
., pp. 623-632, 1994.
SUMMARY OF THE INVENTION
In accordance with an aspect of the invention, a technique for time-domain equalizer (TEQ) training determines the TEQ order and TEQ coefficients by applying the multichannel Levinson algorithm for auto-regressive moving average (ARMA) modeling of the channel impulse response. Specifically, the TEQ is trained based upon a received training signal. The received training signal and knowledge of the transmitted training signal are used to derive an autocorrelation matrix that is used in formulating the multichannel ARMA model. The parameters of the multichannel ARMA model are estimated via a recursive procedure using the multichannel Levinson algorithm. Starting from a sufficiently high-order model with a fixed pole-zero difference, the TEQ coefficients corresponding to a low-order model are deri
Liu Qingli
Purkovic Aleksandar
Ghulamali Qutub
Nortel Networks Limited
Steubing McGuinness & Manaras LLP
Vo Don N.
LandOfFree
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