Telephonic communications – Diagnostic testing – malfunction indication – or electrical... – Of trunk or long line
Reexamination Certificate
2002-01-09
2004-06-01
Tran, Quoc D. (Department: 2643)
Telephonic communications
Diagnostic testing, malfunction indication, or electrical...
Of trunk or long line
C379S022000, C379S022020, C379S024000, C379S002000, C379S027030, C379S001010
Reexamination Certificate
active
06744854
ABSTRACT:
FIELD OF THE INVENTION
The present invention is directed in general to wireline telecommunication systems, and more particularly to an enhancement of a frequency domain reflectometry (FDR)-based, energy reflection anomaly-locating mechanism of the type disclosed in the '681 application, including the use of a precursor signal conditioning circuit for improving the performance of the FDR signal processing subsystem.
BACKGROUND OF THE INVENTION
As described in the above-referenced '681 application, telecommunication service providers are continually seeking ways to optimize the bandwidth and digital signal transport distance of their very substantial existing copper plant, which was originally installed for the purpose of carrying nothing more than conventional analog (plain old telephone service or POTS) signals. In addition to the inherent bandwidth limitations of the (twisted pair) copper wire medium, service providers must deal with the fact that in-place metallic cable plants, such as that shown at
10
in the reduced complexity network diagram of
FIG. 1
, linking a central office
12
with a subscriber site
14
, typically contain one or more anomalies, such as but not limited to load coils (used to enhance the wireline's three to four kilohertz voice response), and bridged taps
16
, to which unterminated (and therefore reflective) lateral twisted pairs
18
of varying lengths may be connected.
Because these discontinuities cause a portion of the energy propagating along the wireline link to be reflected back in the direction of the source, at the high frequencies used for digital data communications (e.g., on the order of one MHz), such reflections can cause a significant reduction in signal amplitude, when (counter-phase) combined with the original signal, disrupting digital data service. To locate these reflection points, it has been conventional practice to employ interactive, time domain reflectometry (TDR), which relies upon the ability of a skilled technician to make a visual interpretation of a displayed TDR waveform, and thereby hopefully identify the bridged taps, and the lengths of any laterals that may extend therefrom. Because this process is subjective, it is imprecise and very difficult to automate.
In accordance with the invention disclosed in the '681 application, shortcomings of a conventional TDR-based scheme for locating energy reflecting anomalies are obviated by stimulating the line with a linearly stepped frequency sinusoidal waveform, and analyzing the composite waveform response by means of frequency domain reflectometry, whose frequency bins represent distances that are integral multiples of delay, so that there is a one-for-one correspondence between the bins of a Discrete Fourier Transform (DFT) and distances to the reflection points along the wireline.
The frequency domain reflectometry system of the '681 application is diagrammatically illustrated in
FIG. 2
as comprising a processor-controlled test head
20
(such as may be installed in a central office, or included as part of test signal generation and processing circuitry of a portable craftsperson's test set), coupled to an access location
21
of a line under test (LUT)
22
by means of a line-driver amplifier
24
and an input receiver amplifier
26
. Line-driver amplifier
24
is coupled to the LUT
22
through source resistors
27
,
28
, each having an impedance equal to one-half the impedance (Zo) of the metallic line pair.
Coupled to the test head
20
is a control processor
30
, that is programmed with an FDR test routine shown in the functional block diagram of FIG.
3
. As shown therein, an initial tone generation function
31
generates a series of digitally created test signals, in particular a sequence of discrete frequency sinusoidal tones, to produce what is in effect a frequency-swept sinusoidal waveform. The swept frequency waveform may be varied in a linear, stepwise manner, for example beginning at minimum frequency such as 0 Hz and stepped in incremental frequency steps up to a maximum frequency. (Conversely, the frequency variation may begin at an upper frequency and proceed to a minimum frequency, without a loss in generality.) These tones are applied (via the line-driver amplifier
24
of
FIG. 2
) to the line under test
22
.
As the frequency of the sinusoidal waveform is swept, the wireline's response signal level at the test access point
21
is monitored (via the input amplifier
26
), digitized by way of an analog-to-digital converter (ADC)
32
, and stored in a signal measurement buffer (not shown). The amplitude of the measured signal response will exhibit a variation with frequency that is a composite of the fluctuations in impedance due to any reflection points along the LUT. In order to optimize the accuracy of the analysis, the response data may be selectively modified by a bandpass filter BPF
33
, the center frequency of which is varied, or ‘slides’, along the variation of frequency of the swept sinusoid being applied to the LUT. This filtering operation serves to remove any DC level and discontinuities that might cause spurious results, between start and end sample values of the data. The filtered data is then stored with each frequency step iteration, to produce a sampled amplitude array
34
. A loss compensation function (LCF) may also be applied to the data set, to compensate the frequency response characteristic of the LUT for loss over distance and frequency.
The line under test can be characterized in terms of its resistance (R), inductance (L), capacitance (C), and conductance (G) parameters per unit length, which are available from tabulated industry-available sources for the type of wire. From these parameters, a frequency-dependent propagation constant &tgr; can be derived as:
&tgr;=&agr;+
j
&bgr;=((
R+jwL
)(
G+jwC
))
1/2
, where
w
=2
Πf.
The real part of the propagation constant, &agr;(f), is the attenuation along the line per unit length. Since the envelope of a signal propagating along the line as a function of distance is attenuated by e
−&agr;(f)t
, &agr;(f) can be determined.
The effect on the frequency response waveform is that amplitude decay is less pronounced for reflected signals propagating on shorter loops, since the shorter distance offsets the effects of the loss at high frequencies, due to the effects of &agr;(f). Since the actual length of the line under test is unknown, a compromise between the two extremes may be employed, to provide compensation for the overall frequency response waveform for all distances of interest.
In order to determine the coefficient of the exponential attenuation function in terms of frequency, it is necessary to reduce the number of degrees of freedom of the total loss function. Since the maximum frequency of the swept sinusoidal waveform is known, a priori, a loss compensation function based upon the mid frequency point of the sweep f
mid
=f
max
/2 may be employed. As will be described in detail below with reference to the amplitude vs. frequency response diagram of
FIG. 4
, from this mid frequency, f
mid
, a corresponding resolution distance d
mid
is defined as:
d
mid
=V
p
/4
f
mid
An ‘average loss’ value &eegr; can be derived as:
&eegr;=e
−&agr;(fmid)dmid
The loss compensation function LCF can therefore be defined as:
LCF
=exp((−21
n
(&eegr;)/
f
max
)
f
).
This loss-compensated data is processed in accordance with a frequency analysis operator, such as Discrete Fourier Transform (DFT)
35
, which decomposes the composite line signal response into frequency bins associated with the individual reflectors' frequency fluctuations.
Next, the Fourier transform-processed data is coupled to a tap decision operator
36
, the output of which is coupled to a remote terminal unit
37
. The tap decision operator employs a threshold established for the contents of the frequency bin data produced by the DFT, in order to distinguish between significant (useful) and spurious energy.
Berrier Travis Lee
Soto Roy Lujan
Wong Wayne Kwok-Wai
Allen Dyer Doppelt Milbrath & Gilchrist, P.A.
Harris Corporation
Tran Quoc D.
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