eTDR Fault Localization Accuracy - The effect of Multiple Impedance mismatches

21
All contents are Copyright © 2015 Intraway Corporation. All rights reserved. Intraway and the Intraway logo are registered trademarks of Intraway Corporation. and/or its affiliates in the U.S. and certain other countries. All other trademarks mentioned in this document or Website are the property of the irrespective owners. The use of the word partner does not imply a partnership relationship between Intraway and any other company. eTDR Fault Localization Accuracy The effect of multiple Impendence mismatch By: Francisco J. Gastiazoro Product Manager Broadband Business Unit Intraway Corporation Campillo 2541 Buenos Aires Argentina +54 (911) 2184-6020 [email protected]

Transcript of eTDR Fault Localization Accuracy - The effect of Multiple Impedance mismatches

All contents are Copyright © 2015 Intraway Corporation. All rights reserved. Intraway and the Intraway logo are registered trademarks of Intraway Corporation. and/or its affiliates in the U.S. and certain other countries. All other trademarks mentioned in this document or Website are the property of the irrespective owners. The use of the word partner does not imply a partnership relationship between Intraway and any

other company.

eTDR Fault Localization Accuracy The effect of multiple Impendence mismatch

By:

Francisco J. Gastiazoro

Product Manager – Broadband Business Unit

Intraway Corporation

Campillo 2541 – Buenos Aires – Argentina

+54 (911) 2184-6020

[email protected]

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Contents _____________________________________________________________________________ 2

Introduction (Executive Summary) ________________________________________________________ 3

Micro-reflections in Transmission Lines ____________________________________________________ 3 Standing Waves _____________________________________________________________________________ 3 Impedance Mismatch ________________________________________________________________________ 4 Return Loss ________________________________________________________________________________ 5 Reflectometers and Micro-reflections ___________________________________________________________ 6

DOCSIS Adaptive Equalization and Pre-equalization __________________________________________ 9

Fault Localization _____________________________________________________________________ 13 Using Time Domain Reflectometer (TDR) _______________________________________________________ 13 Parabolic Interpolation Algorithm _____________________________________________________________ 14 Multiple Impedance mismatches. _____________________________________________________________ 16 Using Micro-reflection Signatures and Geo-reference _____________________________________________ 18

Conclusions _________________________________________________________________________ 21

Bibliography _________________________________________________________________________ 21

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Impedance mismatches are present in many transmission lines, including coaxial cables in HFC outside plants that

create echo, known as micro-reflection. From DOCSIS 1.1, the standard provides means to undermine this effect

by applying equalization techniques in the transmitter and the receptor.

Adaptive equalization filters located at the Cable Modem and the CMTS are the response to most linear

impairments such as micro-reflections. This solution improves typical monitoring indicators such as the RxMER.

Monitoring tools that only focus on degradation of such data loses an important source of proactive maintenance.

This paper introduces detailed information about this effect in order to provide a theoretical and technical

background which helps understand how to interpret pre-equalization data that helps in fault localization.

The obtained conclusions will allow cable operators to effectively use TDR and micro-reflection signatures along

with Cable Modem geo-reference to narrow down the possible locations of the impairment and respond swiftly to

proactive indicators before it affects the customer’s satisfaction.

Standing Waves

When a wave that travels through a medium faces another one with the same frequency and amplitude doing the

same in the opposite direction, we are in the presence of a standing wave. This phenomenon is encountered in

many scenarios in real life such as in sound propagation in guitar’s strings and, of course, in what is the subject of

this paper, electric signals.

What you can see in the line is a series of nodes (zero displacement) and anti-nodes (maximum displacement) at

fixed points. Figure 1 depicts this effect throughout a transmission line at two different moments.

Figure 1 – Standing Waves

When the amplitude of the second wave, the one travelling in the opposite direction, is not equal to the original one,

we are in the presence of a partial standing wave. Due to losses in the transmission lines and other effects later

studied, this is the scenario we are finding in real life applications. This real life standing wave is presented in the

next figure and shows a scalloped sinusoidal form that varies in function of the Reflection Coefficient.

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Γ = 1 Γ = 0.5 Γ = 0.1

The degree to which the resulting wave is a pure standing wave or just a travelling wave is measured by the

Standing Wave Ratio (SWR) also called Voltage Standing Wave Ratio (VSWR) when referring to electric signals.

VSWR is defined as the ratio of the partial standing wave’s amplitude at an antinode (maximum) to the amplitude at

a node (minimum) along the line. As the purpose of the paper is to analyze the effects on transmission signals, we

are going to use VSWR. This indicator is of much importance for further analysis and it is defined as:

(1)

Impedance Mismatch

The most basic model of a transmission system is comprised of a Source, a lossless Transmission Line and the

Load (the receiver). Each element has its own impedance, known as the characteristic impedance Z. The condition

that is assumed when analyzing the system’s behavior is that all impedances are the same. In other words Zs = ZT

= ZL. This implies that all the signal energy is absorbed by the load.

Figure 2 – Transmission Line Model

That model is especially useful to understand how the system will behave under ideal/theoretical conditions (where

there is no loss in any form).

When the impedances of the transmission line and the load are not the same we are in front of impedance

mismatch. Impedance mismatches behave like mirrors, all or some of the energy delivered to the load is reflected

back to the line, causing standing waves. A reflectometer is any element in the line that creates reflected waves,

therefore, impedance mismatches act as reflectometers.

In real life, there is no perfect match between any two elements in the transmission line; every connector, amplifier,

node, splitter, coupler, power inserter, feeder tap, terminator, and even the cable itself represent an impedance

mismatch of some sort. For instance, we have the manufacturing errors (there is always an error margin),

components damaged by the weather/environment conditions, no perfect fit between a coax connector and the

cable itself, etc.

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Figure 3 - Incident, Transmitted and Reflected Signals in a Transmission Line

How severe are those impedances mismatches? To respond to this we use VSWR.

The ratio of reflected to incident wave (or Voltage) is known as the reflection coefficient, Γ, which is mathematically

defined as Γ = E–/E+ where E– is the reflected wave’s voltage and E

+ is the incident wave’s voltage. The same

expression can be re-written as:

(2)

ZL and ZT are not usually purely resistive impedances, so Γ has to be considered a complex number. Using phasor

notation we will refer the reflection coefficient as:

(3)

The magnitude of Γ vary from 0 to 1, where 0 indicates all power is absorbed by the load (no reflection), and 1

indicates 100% reflection (short circuit, open circuit or pure reactance).

VSWR relates to the reflection coefficient through the following mathematical expression:

(4)

The VSWR ranges from 1 (No standing wave) to ∞ (a perfect standing wave).

Return Loss

Cable industry generally uses return loss rather than VSWR to characterize impedance mismatches. In its simplest

form, return loss is defined as the difference, in decibels, between the amplitude of the incident wave and the

reflected wave.

R(dB) = 10 𝑙𝑜𝑔𝐼𝑛𝑐𝑖𝑑𝑒𝑛𝑡 𝑃𝑜𝑤𝑒𝑟

𝑅𝑒𝑓𝑙𝑒𝑐𝑡𝑒𝑑 𝑃𝑜𝑤𝑒𝑟

So Return loss can also be seen as.

R = 10 𝑙𝑜𝑔 (𝑉+2

𝑉−2)

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R = 20 𝑙𝑜𝑔 (𝑉+

𝑉−)

R = 20 𝑙𝑜𝑔 (1

|Γ|)

The Reflection coefficient Γ is:

|Γ| =𝑉𝑆𝑊𝑅 − 1

𝑉𝑆𝑊𝑅 + 1

So

R = 20 𝑙𝑜𝑔 (𝑉𝑆𝑊𝑅 + 1

𝑉𝑆𝑊𝑅 − 1)

For example, assume that an incident wave’s amplitude is +30 dBmV, and an impedance mismatch causes a

reflection whose amplitude is +14 dBmV. Here the return loss is 30 dBmV – 14 dBmV = 16 dB, a fairly typical value

for passive devices such as taps and splitters The incident and reflected voltages derived from the +30 dBmV (31.62 mV) incident signal and +14 dBmV (5.01

mV) reflected signal. From these, the reflection coefficient is

Γ =𝑉−

𝑉+

Γ =5.01 𝑚𝑉

31.62 𝑚𝑉

Γ = 0.1584

Next, let’s calculate the voltage standing wave ratio

𝑉𝑆𝑊𝑅 =1 + |Γ|

1 − |Γ|

𝑉𝑆𝑊𝑅 =1 + 0.1584

1 − 0.1584

𝑉𝑆𝑊𝑅 = 1.38

Reflectometers and Micro-reflections

An echo, like the sound, is a variation of the original signal that arrives at the receptor or transmitter a time after the

original signal has, due to the effect of reflections. For an echo to reach the receptor, at least two reflectometers

have to be present in the transmission line. In other words when multiple impedance mismatches exist, there will be

multiple reflections, ending up, therefore, in a situation where the echo is encountered in the receptor side.

If only one reflection is present, we still encounter a standing wave, however that wave has no effect on the signal

in the receptor side. The only effects visible are the ones related to the changes introduced solely by the

malfunctional element in the line.

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Even though this may look trivial, it is not. This assumption is based on the fact that if it happens in real life, we are

not in the presence of an impedance mismatch between the cable modem and the coax cable, or the mismatch is

so little that the second reflection is below the noise level already present in the line. It is important to take this

conclusion into account in fault localization as we will see later.

In a high-speed data scenario a micro-reflection is reflection with a short time delay. That is, a close-in reflection

whose time delay relative to the incident signals ranges from less than a symbol period to perhaps several symbol

periods. From now on, we will be focusing on micro-reflections.

Let us see the effect of two reflectometers on a lossless line to see the effect of an echo in the receptor’s side on

the received signal.

Figure 4 – Echo Generated by Two Reflectometers

The incident wave at the second reflectometer is represented as:

The first reflector is represented as the phasor . Conversely, the second reflector is represented as

.

The reflected wave will take a Δt delay to reach the second reflector, this Δt is the round trip delay that takes from

bouncing at the second reflector, travels towards the first reflector, bounces again and finally, travels back to the

second reflector to be summed with the incident signal. That time delay has an effect in the signal’s phase and it’s

represented mathematically as the phasor .

Adding up all the effect to the incident signal, the reflected signal is represented as:

(5)

So, the resultant signal that continues through the line until it reaches the receptor is the sum of both the incident

and the reflected signals.

The time delay introduces an interesting effect now, depending on which frequency it is transmitted, the resulting

wave has different effects over the amplitude and the phase. This effect is known as a linear distortion.

The next step is to look further on the frequency response of this system. To do so we are going to use phasor

analysis. Figure 5 shows the possible value the resulting signal can have when summing both phasors at different

frequencies.

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Figure 5 – Phasor Representation of the Sum of Reflected and Incident Wave

The amplitude of the signal changes with the frequency reaching its maximum when both, the incident and the

reflected signals, are in phase, and reaching the minimum when both are out of phase. Mathematically this is:

and (6)

As any other periodic signal, each value is repeated each 2π radians.

So the shape will repeat periodically every as shown in Figure 6.

Figure 6 – Amplitude Ripple in the Frequency Response

The first conclusion is that micro-reflection creates a linear distortion that affects the frequency response of the

system as a whole. This effect is known as amplitude ripple. The amplitude ripple is characterized by its amplitude

swing.

(7)

If we replace the amplitude ripple can be calculated in the same way as the VSWR in (4)

using this equivalent reflection coefficient. VSWR ≃ Amplitude Ripple.

This leads to a second conclusion: we can know the magnitude of the reflected signal by measuring the amplitude

ripple in the frequency domain.

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It is worth noticing that the reflections do not stop after the second reflection, they continue to do so until they reach

the noise floor. All the conclusions reached in this section are still valid when we extend the analysis to more than

one echo at the receptor.

If we replace a lossless line with a real one, the amplitude of the ripple will be lower because the reflected wave

loses energy when travelling between the reflectors, but the effect remains the same. This loss is included in the

equivalent reflection coefficient.

An adaptive filter is one whose coefficients (parameters that define its behaviour) change over time “adapting” itself

to the input signal or the context where the signal lives. DOCSIS 1.1, 2.0 and later are capable of equalizing using

adaptive filters in the transmitter, a process which is called pre-equalization, and in the receiver, just called plain

equalization.

Those filters are designed to cancel, or at least to mitigate, the effect of the channel impairments. This is been done

in two ways:

1. Cancelling the impairment effects once the signal has traveled the channel (transmission line), that is, at

the receiver.

2. Pre-distorting the signal before it leaves the source so that when it has finished traveling the transmission

line, the impairment effects are compensated.

Mathematically, in terms of the frequency response, both scenarios can be represented as

and respectively. Where X(z) is the

transmitted signal and H(z) is the transfer function of both the channel and the filter. It is easy to see that if the

system is able to reach the condition where , the received signal is equal to the

transmitted signal.

It is beyond the scope of this paper, but it can be demonstrated that, to successfully cancel the linear impairments,

such as micro-reflections at the receiver, an Infinite Impulse Response Filter (IIR) is needed. However, to

implement this in the transmitter, the same effect can be achieved with a Finite Impulse Response Filter (FIR).

In practice, a FIR filter are also implemented at the receiver, which do not compensate entirely the channel

impairments, but it attenuates the effects greatly, reaching even to a steep drop below the noise floor already

present in the signal. FIR filters require more computational capacity to do the same task than the IIR, but, in the

case of the latter, implemented with adaptive coefficients, it is difficult to assure its stability as they are more prone

to have their poles outside the region of convergence due to a series of effects not relevant to this paper.

Mathematically, the transfer function of a FIR filter can be described as: (8)

Most FIR filters are implemented using a Lattice scheme and their coefficients are calculated based on a Minimum

Square Error strategy. The following diagram of a four tap filter exemplifies this:

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Figure 7 - Four Tap FIR Filter with Equalization

Now, let us see how to mitigate the micro-reflection effect with equalization at the receiver and then with pre-

equalization at the transmitter.

To keep it simple, the transmission line (the channel) will introduce a single micro-reflection, of half the value of

transmitted signal, inverted and with separation between reflectors of one tap symbol. Graphically this can be seen

as:

Figure 8 - Micro-Reflection Representation

When the equalizer is implemented at the receiver (CMTS), with a 3 stage tap FIR Filter, the transfer function that

best compensate the channel effect is represented with the followings coefficients:

(9).

Figure 9 depicts what happens to the signal with a micro-reflection at different stages to finally show the output

signal.

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Figure 9 - A Signal with Echo through an Equalizer at the Receptor.

The micro-reflection was not completely cancelled by the filter, but it is reduced eightfold and delayed 4 symbols

resulting in a lower amplitude ripple.

On the other hand, when the filter is implemented in the transmitter and the signal is pre-distorted, the transfer

function is the following:

(10)

Figure 10 depicts what happens to the signal at different stages to finally show what happens when the output

signal encounters the micro-reflection.

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Figure 10 - A Signal with Echo through an Equalizer at the Transmitter

As seen in the picture, the micro-reflection is summed to the pre-distortion added by the filter resulting in elimination

of the former.

Looking at pre-equalization tabs coefficients we can see how separate the micro-reflections from the original source

are. This is the base for what comes next, fault localization.

In DOCSIS 1.1 cable modem support 8-tap upstream pre-equalization and DOCSIS 2.0 and later versions support

24-tap upstream pre-equalization. CMTS also implements equalization filter at the end of the upstream path.

A Cable Modem has no way of knowing what the upstream channel response is. Due to this, ranging and station

maintenance bursts transmitted by the modem are evaluated by the CMTS. The CMTS upstream receiver has its

own adaptive equalizer, from which equalizer coefficients that are transmitted to each modem derive. The modems,

in turn, use those equalizer coefficients to configure their internal adaptive pre-equalizers.

Currently available CMTS burst receivers, which incorporate DOCSIS 2.0 and later 24-tap adaptive equalization,

support main tap positions of 2 through 10. Adaptive equalizer tap position 8 is generally the default setting.

How does that affect the maximum time delay the filter can correct when dealing with micro-reflections?

Assuming that adaptive equalizer tap #8 is the main tap, that results in a usable span is: (24 – 8) x

0.1953125 μs = 3.13 μs.

If the adaptive equalizer main tap is changed to #10, the usable span becomes (24-10) x 0.1953125 =

2.73 μs, and

if the adaptive equalizer main tap is changed to #2 the usable span becomes (24-2) x 0.1953125 = 4.3 μs.

Another way of seeing the value of coefficients is to think of them in terms of energy. Figure 11 shows a real Cable

Modem pre-equalizer filter expressed as tap energy.

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Figure 11 – Cable Modem Pre-equalization Energy Tap Representation

Using Time Domain Reflectometer (TDR)

A time Domain Reflectometer (TDR) is an instrument which locates fault in cables by transmitting an incident signal

and measuring the time until the reflection is received. Knowing that, time interval allows the instrument to detect

the distance to the impairment by following this simple mathematical formula.

(11)

Where the Vp is the velocity of propagation in the cable, which depends on the dielectric characteristic of the line

(e.g. the coaxial cable has a velocity of propagation around 87% of the speed of light in a vacuum) and T is the

round-trip delay (the sum of the time that takes the incident signal to reach the impairment and the time it takes the

reflection to reach the source again).

Knowing which kind of cable was used in the transmission line, the only thing remaining to know is the time that it

takes a reflected signal to arrive to the source.

As presented previously in this paper, DOCSIS pre-equalization coefficients hold information about the symbol

delay and energy of the micro-reflection and other linear impairments. However, there is a trick; the time delay

information present in the equalizer measured the micro-reflections from the receiver point of view as was

expressed in the Reflectometers and Micro-reflections

.

One of the sources of micro-reflection is given by a broken feeder acting as the first reflectometer and the Cable

Modem itself (or a splitter inside the house) acting as the second one. Figure 12 describes this scenario.

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Figure 12 – Cable Modem/Broken Feeder Impedance Mismatch Representation

To keep it simple, we will assume that the round-trip delay is exactly 3 symbols. So if we see the pre-equalizer filter

at the Cable Modem we will see something like this (assuming main tap location is at 8th position) in terms of

energy.

Figure 13 - Energy Tap - Cable Modem/Feeder Micro-reflection example

That is, 3 symbols away from the main tap, needs to be translated to seconds, or more accurately microseconds. If

the symbol rate is about 5.12 Msym/s when the upstream channel is set to 6.4 Mhz with a roll-off of 0.8, this gives

a time symbol period of 0.1953 µsec. The velocity of propagation for coaxial cable is around 260,819,438 meters

per second (855,706,819 feet per second). The TDR calculation with this numbers gives: 76.41 meters (250 feets).

So in this scenario, the TDR is telling us that the broken feeder is about 250 feets from the Cable Modem and that

is excellent news.

In real life it is very unlikely that the reflectors are located at distances that are multiple of the symbol period. When

this happens, we will see that there is a main echo tap (the one with the greater energy) and surrounding taps with

lower energy. This is because the pre-equalizer uses more than one tap to compensate for the micro-reflection.

In order to improve the accuracy and not to rely just on the main echo considering the energy in the surrounding

taps, an interpolation algorithm can be used to improve the TDR determination.

A good example of this kind of algorithm is the Parabolic Interpolator which is shown below.

Parabolic Interpolation Algorithm.

The figure below shows an example test case. Pre-equalizer taps 9, 10, and 11 have magnitudes 35 dB, 40 dB

and 29 dB, respectively. We are not concerned about other taps since the algorithm uses only a 3-point

interpolator, so the surrounding taps are plotted as zeros.

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The algorithm inputs are the 3 taps around the (local) peak: (x0,y0), (x1,y1), (x2,y2), where the middle sample

(x1,y1) is the local peak of interest. The x value is the pre-equalizer tap number (typically in the range from 1-24)

and the y value is the tap magnitude in dB. It has been found empirically that using the dB values gives good

results; it is not necessary to convert from dB values to power ratios. Hence for our example we have the following

inputs to the algorithm:

x0 = 9

y0 = 35

x1 = 10

y1 = 40

x2 = 11

y2 = 29

The algorithm fits a parabola, shown in the figure as a dotted blue line, to the 3 taps. We assume the equation for

the parabola is y = a*x^2 + b*x + c.

The following code solves for the location of the peak of this parabola:

a = (y0 - 2*y1 + y2)/2; % Coefficient a in y = a*x^2 + b*x + c; note: a should be negative, otherwise no peak

exists

b = (y2 - y0)/2; % Coefficient b in y = a*x^2 + b*x + c

c = y1; % Coefficient c in y = a*x^2 + b*x + c

xm = (y0 - y2)/(4*a); % x-axis offset from max sample (samples)

ym = -(y0 - y2)^2/(16*a); % Magnitude (y-axis) offset from max sample

-4 -3 -2 -1 0 1 2 3 40

5

10

15

20

25

30

35

40

45Parabolic Interpolator: y Magnitude vs x, Zoom View

Time (samples, 0=center sample #10 used by interpolator)

Magnitude o

f y

Peak offset = -0.1875 samples

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x_out = x1 + xm; % Interpolated x index (tap number)

y_out = y1 + ym; % Interpolated tap magnitude

The output is (x_out,y_out). The x_out value generally lies between integer tap numbers, giving fine time location

information. The y_out value may also be used if fine magnitude accuracy is desired. In our example we have the

following outputs:

x_out = 9.8125 (a little to the left of tap 10)

y_out = 40.2813 dB (a little higher than tap 10 magnitude).

This parabolic interpolation algorithm is courtesy of Bruce Currivan from Broadcom Corporation.

Monitoring tools, use this to elaborate an algorithm that calculates the TDR based on energies of the main echo tap

(the one which holds the greater amount of energy) and its surroundings. Figure 14 shows real time calculations of

the TDR for a series of cable modems.

Figure 14 – TDR calculations examples

Multiple Impedance mismatches.

Now we are going to analyze what happens in a different scenario. This new scenario involves an almost perfect

impedance match in the Cable Modem (the reflection caused by this mismatch is near to the noise floor), but there

are a broken feeder and a mismatched line tap both acting as reflectometers along the upstream. Figure 15 depicts

the scenario.

Figure 15 – Line Tap/Broken Feeder Impedance Mismatch Representation

Now, if the round-trip delay from the feeder to the line tap and back is exactly 3 symbols, the equalizer energy tap

will be exactly the same as Figure 13 - Energy Tap - Cable Modem/Feeder Micro-reflection example

.If we calculate the TDR in this scenario under the same conditions that the first example (same cable type and

upstream channel), it will throw the exact same distance: 76.41 meters (250 feet). But this time, the 250 feet are not

centered in the Cable Modem.

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This elemental analysis can be extended to more than 2 impedance mismatches.

To add a little complexity to the analysis, we are going to show a last scenario. This involves a mismatched line tap,

a broken feeder and a Cable Modem. The round-trip delay between the line tap and the feeder is 3 symbols and the

round-trip delay between the line tap and the cable modem is 4 symbols. Figure 16 depicts this scenario.

Figure 16 – Cable Modem/Broken Feeder/Line Tap Impedance Mismatch Representation

The relationship between the reflection coefficient is: . Figure 17 shows the three

micro-reflections generated in this scenario and timing in which they arrive.

Figure 17 – Multiple Micro-Reflections Representation

The first micro-reflection to arrive is the one between the Feeder and The line tap, which does 3 symbols time later

than the original signal. The second micro-reflection to arrive is the one between the line tap and the Cable Modem,

and it arrives 4 symbols time later than the original signal. The last micro-reflection to arrive is the one between the

feeder and the Cable Modem, which arrives 7 symbols time after the original signal. It can be proven that the

relationship between amplitudes is Micro-Reflection 1 > Micro-Reflection 3 > Micro-Reflection 2. Figure 18 shows a

possible pre-equalizer energy tap for this scenario.

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Figure 18 – Pre-Equalizer Energy Tap Representation in Cable Modem/Broken Feeder/Line

Tap Impedance Mismatch Representation

The main echo tap here is again the 3rd tap, and applying the TDR calculation to this information gives the exact

same distance: 76.41 meters (250 feet). And, as in the prior example, the 250 feet are not centered in the Cable

Modem.

All this leads to one simple question: how sure can we be that the main echo (the most significant one) involves the

Cable Modem and that the distance based on TDR can be centered in the Cable Modem? The answer is simple:

TDR calculation alone may not tell us the exact location because the first reflectometer is not known and it will only

be useful when the cable modem is proven to be one. Due to this we cannot based our decision by solely looking at

this parameter.

Using Micro-reflection Signatures and Geo-reference

As seen in the previous section, TDR alone do not tell us exactly where the impedance mismatches are, it only

informs the distance between the main two.

To analyze this further we need to consider the entire dataset from the same fiber node. Most of the upstream path

is shared by many cable modems, due to this, when impedance mismatches are located in common paths, all cable

modems that share that path should experience the same or almost the same pre-equalizer settings. The following

figure shows the frequency response of several Cable Modem sampled from a fiber node (for clarity only a few

were included) where there are two Cable Modem with clearly common micro-reflections.

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Figure 19 – Common Impairments in The Frequency Response

The way of helping to determine if two or more Cable Modems have common micro-reflections, is to include in the

analysis the micro-reflection level.

The micro-reflection level can be estimated using the VSWR defined in (1) and the relationship with the ΓTotal

defined in (7).

Given the size of typical fiber nodes, the combination of echo delay and amplitude ripple of the frequency response,

known as the micro-reflection signature, is enough to determine the uniqueness of a micro-reflection. Due to this, all

Cable Modems that share the same micro-reflection signature are considered to have a common impairment.

Monitoring tools use this information combined with the TDR calculation and the Cable Modem’s geo-reference to

help isolate the location of the fault. Using the TDR we can draw a circle centered in the Cable Modem to form a

probability area. All these give us three possible scenarios:

The first scenario is given when the micro-reflection signature is not shared with other Cable Modems, such as the

one that figure 20 shows. This indicates that we can consider that there is a very high probability that the two

reflectometers are in the portion of the path which only belongs to the Cable Modem with the impairment

Figure 20 – No Common Impairment Scenario

Even more, if the TDR gives a distance that is greater than the unshared path, the impairment location is almost

certain to be within the Cable Modem premises. If it were not the case, other Cable Modems should experience the

same micro-reflections.

The second scenario is given when there is a shared micro-reflection signature, but at least one of the probability

areas do not overlap, such as the one the Figure 21 shows. In this case, only the portion of the path shared solely

by the Cable Modems with the same signature has to be taken into account as there is a high probability of a

common impairment, and the Cable Modems themselves are not acting as reflectometers.

Figure 21 – Common Impairment and not Overlapping Area

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The last scenario is an extension of the last one, which is given when not only there is a shared micro-reflection

signature but all the probability areas overlap. In this case either both reflectors are in the common path or only one

is and the others are the Cable Modems. If the latter is the case, the first reflectometers should be located at the

intersection of all the areas.

Figure 22 – Common Impairment with Overlapping Area

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This paper analyses the effect of an impedance mismatch on the transmission line, showing that when there are at

least two of them, a micro-reflection is received in the receptor side. This effect provokes an amplitude ripple in the

frequency response that is perceived as noise.

This theoretical background was provided to understand the need of equalization filters. A theoretical impedance

mismatch example is used to exemplify how to use pre-equalization information present in those filters to retrieve

relevant information about the micro-reflections.

It was also illustrated how time domain reflectometry uses the information provided by the main echo tap to

determine the fault’s location. By presenting simple impedance mismatched examples, the first conclusion was

presented to the audience. TDR calculation is not a reliable indicator by itself as it only provides the distance

between the two main reflectors and those two can be anywhere along the line.

Lastly and as a final conclusion, this paper makes clearly evident that with the aid of micro-reflection signatures and

geo-reference, the impairment location path can be narrowed down significantly, and that tools that take into

account that information are providing significant data that can help technicians to pinpoint the impairments faster

before the degradation affects the customer’s satisfaction.

[1] Wave Transmission (Connor, F.R), Edward Arnold Ltd., 1972 ISBN 0-7131-3278-7.

[2] Introduction to Signal Processing (Orfanidis, S.J), Prentice Hall, ISBN 0-1320-9172-0

[3] Proactive Network Maintenance Using Pre-equalization, CM-GL-PNMP-V02-110623, Cablelabs

[4] Carrier-Frequency Estimation of BPSK and QPSK Signals Using Spectral-Line Techniques, B. Currivan,

Proceedings of the National Science Foundation Workshop on Cyclostationary Signals, August, 1992, Yountville,

CA, USA.