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One of the biggest challenges in Planning, Designing and even
Optimization of Mobile
Networks is to identify where the users are, or how they are
distributed.
lthough this information is essential, it is not so easy to be
obtained. !ut if we have and
know how to use some counters related to this kind of analysis,
everything is easier.
"or #$M, we have seen that we can have a good idea of the
location %distribution& of users
through the measures of ' %'iming dvance&, as we detailed in
a tutorial about it.
'oday we are going a little further, and know the e(uivalent
parameters in other
technologies, such as )*DM %and +'&.
Goal
+earn the Performance -ndicators related to the users
distribution in a multitechnologymobile network, and also learn how
to use these indicators together in analysis.
TA in 2G (GSM)
)e/ve aready talked about ' in #$M in another tutorial, so let/s
0ust remember the most
important concept.
' %'iming dvance& allows us to identify the distribution of
1# %#$M& users regarding itsserving cell, based on signal
propagation delay between the the 2/s and the !'$. 'he #$M
mobile %from now on, we will call here 2 too as in 3#&
receives data from !'$, and 3
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time slots later sends its data. -t is sufficient if the mobile
is close to the !'$, however,when the 2 is far away, it must take
into account the delay that the signal will have to go
through the radio path.
$o4 the 2 sends the ' data together with other measures for the
necessary timead0ustments to be made.
-n this way, we indirectly get a map with the distribution of
users, or their probable location
area, corresponding to the coverage area of the cell, with a
minimum and ma5imum radius.'he following figure shows this more
clearly, for an antenna with 67 8!), and ma5imum %9&
and minimum %1& radius.
And in 3G and 4G (WCDMA, LTE), does we also have
TA?'he e5pected (uestion here is4 does we have ' in 3#:;#<
'he answer is =es, but in
)*DM the name is another, it is called Propagation Delay. %-n
+', we have bothparameters ' and PD&.
$o, let/s learn a little more about it.
Proa!a"ion Dela# in 3G (WCDMA)
s we/ve told, in 3# the corresponding parameter to ' in 1#
%#$M& is the Propagation
Delay. )ith this parameter, we can estimate the distance between
the 2 and the serving
cell, in the same way as we do in #$M.
!ut in 3# it has some different characteristics. 'o begin with,
3# measurements are made
by the >N*, and not by the 2.
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-n one recent />>* and >!/ tutorial we have seen how an
>>* connection is established,where the 2 sends a />>*
*ONN*'-ON M$$#/ message. )hen the >N* receives this
message, it sends another message back to Node!, to set up a
>adio +ink %/>D-O +-N?$'2P >@2$'/& %9&. 'his
message contains the -nformation lement with the Propagation
Delay data, that is, the delay that has already been checked and
ad0usted to allowtransmissions and reception synchronization.
s already mentioned, the information does not come from the 2 as
in #$M, but is theinformation that the >N* already has to make
the communication possible4 the information
of this delay, the Propagation Delay -nformation lement %-&
is sent every 3 chips.
$o let/s do some math.
• )e know that the )*DM has a constant rate e(ual to 3.A; Mcp
chip:s.
• )e also know %we consider& that the speed of light is
3BB,BBB km:s.
-n 9 second - have 3.A; M chips, in how many seconds - have 3
chips< nswer4 B.16 ps%pico seconds&.
s we have seen that the information is sent every 3 chips, the
total is 3 5 B.16 C B.A psps, which is the Propagation Delay time
granularity.
nd now let/s translate this minimum value into Distance4 -f -
run 3BB,BBB miles in 9second, what distance - run in B.A ps<
nswer4 13; meters.
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-n other words, have the Propagation Delay with granularity of
13; metersE
Note4 it is important to know that this distance information is
available to the system not
only in the establishment of the call, but also during the
entire e5istence of it.
$o%nd Tri Dela# & $o%nd Tri Ti'e ($TT)
)hen we talk about Propagation Delay, there/s another very
important concept, related to
the sub0ect and used in several other areas that involve
communication between two points4the >ound 'rip Delay F
'ime.
+et/s understand what it is with an e5ample. -magine a simple
communication between two
people, where the first say /8i/, and the second one also
answers /8i/.
-n an ideal world, first person speech travels up to the second
one, taking a certain amountof time %t9&, and the speech of the
second person returns with a time %t1&. $o, we have a
total time elapsed from when the first person said /hi/ till he
received the other guy/s
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answer. 'his time is the >ound 'rip 'ime, or the time at
which a signal travels a route untilthe response is received back
at the source.
!ringing this analogy to an 2 and a Node!, we have the image
below.
44 >'' C %t9 G t1&
-n fact, the approach above is very close to real. !ut we have
to consider also the time in
which the receiver takes to /process/ the information, or the
time it takes to respond afterreceiving the information.
*onsidering then this /latency/ time %'+&, the >'' is so
as4
44 >'' C %t9 G t1& G '+
$o, we understand then what is >''. !ut how do - use
it<
'his information is very important to the system, and can be
used for several purposes. Oneof them for e5ample, can be also to
find 2/s locations. Our goal today is to know all means
to find the location information of the 2/s, remember
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)ell, this is another method %in addition to the counters, as we
shall see soon&. )hen theNode! sends a message to the 2 it
knows e5actly what time is. nd then, when it receive
a response from the 2, it also knows e5actly that other
timeE
$o, it 0ust do the subtraction of the times to find the >'',
and calculate the distanceE Note4the time used for the calculation
is half of the >'' as the >'' is the roundtrip path. -n
this
case, the latency time on the receiver is /disregarded/.
)ith this distance information we can draw a circle with the
likely area where the 2 is. ndif it is being served by various
cells, the intersection of the circles of each one of them
gives
us a more accurate positioning %it is what we call
/'riangulation/&. nd these calculations areeven more accurate
when other information is used togheter, such as /*ell-D/, M**,
>N*,
+* and *all +ogs %*8>&, with much more detailed
information.
!ut let/s go back to the case where we only use the information
of Propagation Delay that
is our focus today and that already gives us sufficient
allowance for several veryinteresting analysis.
TA and PD (Proa!a"ion Dela#) o%n"ers
'he Propagation Delay information are %also& available in
simple form of Performance
counters.
'hese types of counters are available in preset ranges according
to each vendor. 'he
ranges vary from 9 Propagation Delay to several /grouped/
Propagation Delay.
"or e5ample in 8uawei have some ' ranges in #$M, and other PD
ranges in )*DM %Note4
8uawei calls these propagation delay counter s as 'P instead of
PD&. "or an /ideal/ scenario,we would have counters for /each/
Propagation Delay.
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ctually, that/s not what happens, because as we told before,
they may be grouped into
ranges. Note4 the reason for this is not the case, but really
too many ranges may even
disrupt analysis.
'P %Propagation Delay )*DM in 8uawei& has 91 ranges.
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-n the above figure we have PD' from B to 99.
• "or 'PHB the 2 is between B and 13; meters from Node!I
• "or 'PH9 the 2 is between 13; and ;6A meters from Node!I
• ...
• "or 'PH36H77 the 2 is between A.; and 93.9 km from Node!I
• nd for 'PH76HMO> the 2 is more than 93.9 km from Node!.
-n the #$M %8uawei& have the same concept.
Note4 $ee however that the amount of ranges here %#$M& is
much bigger, and only begin tobe grouped from 3B %from almost 9
kmE&.
)ith the counters organized in so different ways, be grouped by
different rangesgranularities, different distance %77B m for #$M
and 13; m for )*DM& it is very difficult to
analyze the propagations, or rather, it is almost impossible to
compare them...
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nd so what does we do, since we need to analyze the distribution
of the 2/s in a genericway, doesn/t matter if it is using 1# or
3#<
'he solution that we found in telecom8all was to make an
/approach/, that is, a way to be
able to see where we have more concentrated 2/s, no matter if at
the time they are using1# or 3#. ven because, this /distribution/
among 'echnologies and *arriers depends on
several factors, such as selection and handover parameters, and
also physical ad0ustmentsof radiant system. !ut the /concentration/
of users does not depend on these factors4 thetotal amount of users
in a particular area is always the sameE
'o this, the module /8unter Propagation nalyzer/ uses a
methodology and /particular/
counters, allowing to do this approach4 we have created a range,
and called it PD'. s the3# %8uawei, which we are using as an
e5ample& has less ranges only 91, we made the
initial PD' definition based on it. 'he result can be seen in
the table below.
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Of course this approach or /methodology/ is not perfect, but in
practice the outcome is veryefficient. -n addition, if you need a
more detailed analysis %for e5ample if you need to know
with more accuracy than the approach presented here& 0ust
look to the original table, whichcontains each counter in its
standard range in original granularity.
"or other vendors, the ranges may be different, but the
methodology is always the same.
-n ricsson for e5ample, the Propagation Delay )*DM counter is
/pmPropagationDelay/,and it is collected by the >N* 0ust like in
8uawei.
-t has ;9 bins, being the first to indicate the ma5imum delay in
chips %*ell >ange&, andother %9 to ;B& to inform the
number of samples in the period, referring to the percentage
of the ma5imum *ell >ange.
)hen the 2 try to connect at one point greater than the *ell
>ange it will fail.
>egarding to bins, the distribution goes from B to 9BBJ, as
the rule below4
• bin94 samples between B and 9J of *ell >ange %for e5ample,
if the *ell >ange is 3B km, bin9 has
the samples between B and 3BB m from Node!&I
• bin14 samples between 9J and 1J of *ell >angeI
• K
• bin;B4 samples between L6J and 9BBJ of *ell >ange.
nd the /ad0ust/ of PD' can be done the same way, depending on
your need.
*onclusion4 Different vendors have different propagation
counters, and in different formats but the information is always
the sameE -n all cases we can do the calculations that bring
the analysis to the same comparison universe, with the benefits
that we/ve illustratedabove.
Dis"ri%"ion o* $adio Lin+ ail%re (GSM) and E-o(WCDMA)
Okay, we/ve seen today how to check the distribution of 2/s on
1# and:or 3# networks
based on its counters. !ut in addition, we have also other
e(ually interesting informationE
-n #$M, in addition to PD', we were able to count >adio +ink
"ailures. nd this gives us a
great opportunity of crossing this information with the amount
of *all DropsE 'he rule issimple4 the point we have a lot of
>adio +ink "ailures, /much/ probably we also have a lot
of
Dropped *allsE 'he relation is straightforward.
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nd in )*DM, in addition to PD', we also have the average value
of cNo, that indicatesthe average (uality of a given
cell:regionE
Note4 -n 8uawei, for the average value of c:No for each 'P, take
the counter value and use
the formula4 cNo C %value ;L& : 1.
TA in 4G (LTE)
s well as in 1# and 3#, we were also able to get the 2/s
distribution information in +'.
'he concepts applied are the same as already seen before, we can
only point out that in +'we have both ' and PD.
s today/s tutorial is already (uite e5tensive, we will finish
this part here, but with thecertainty that if you assimilated what
was presented, without any ma0or problems you will
be able to e5tend this information to your specific
scenario.
Pra"ial Anal#sis
fter having seen even with a little more detail the concepts of
propagation %including"ailures in #$M and cNo in )*DM&, we will
see some possible analysis that we can do in
practice.
)e have already said that the professional who has e5perience on
this kind of analysis can
improve enough to network -ndicators as >etainability and
ccessibility. !ut how hemanages to do this<
$imple4 with the propagation analysis, it is possible to
identify cells that are with their muchgreater coverage than
planned:e5pected /overshooting/ cells, especially if they are
reaching places where we have other cells with better signal
levelE
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-n this case, we have pilot pollution, interference and high
transmit power. s a result,
increase of stablishment "ailures and *all Drops, both in
overshooting cell, as in the otherwhere it is interfering.
-n addition, we can discover cells that have their coverage area
in the same direction%sector&, but that have very different
concentration %for e5ample in the case of 3 )*DM
carrier, where one *arrier can be with the highest concentration
of users closer to the cell,and another with this concentration
away don/t worry, we will see e5amples below and will
be easier to understand&.
'his difference of distribution:concentration can be seen
between the multitechnologies of
the sector, for e5ample, if the #$M coverage is much smaller
than the )*DM and viceversa. -n this case, it serves as a great
call for ad0ustments of tilts and azimuth between the
antennas in this sector.
Pra"ial anal#sis . Wor+shee"s and Char"s
2sing data from simple counters, we already have e5cellent ways
of analysis like charts andgraphs. "or e5ample, the following is a
complete view of a particular sector of our network
%all cells of all technologies and all carriers&. Note that
the simple thematic distribution
obtained with 5cel *onditional "ormatting already gives us a
clear vision of this sector.
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"iltering only for the contribution %/PD'HP/& of each cell,
we can see clearly that a sector%855519& is with its coverage
beyond the e5pected %9&.
-n addition, we were able to match %9& failures %now
filtering by /*NO>+"-+HP/&, showingthe immediate need for
actions in this sector.
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Pra"ial Anal#sis & Mas
-n addition to the simple analyses on charts and tables, we can
georeference it, with a
direct relationship with the coverage area. "or demonstration,
we create some dummy PD'data of our network. Note4 real network has
much more cells, but with these few sample
data we can show the main points of analysis.
*ontinuing, we will then see the PD' data of ; e5amples sites
plotted.
'o analyze the PD' distribution in #oogle arth, we use a report
generated by the /8unter
# Propagation nalyzer/ module, and so we need to know the
criteria that we are using4in this report, the heights %9& from
each region %PD' of B to 99& represent the percentage
of samples in that region. nd the colors %1& represent the
@uality4 cNo to 2M'$, and>adio +ink "ailure J for #$M. Note4 you
can build your reports in #oogle arth and:or
Mapinfo, 0ust follow and apply the concepts presented here to
your own tools:macros.
'he data are grouped in /"olders/, with the first level being
the sector %9& %a specific
direction for all cells of all technologies and carriers&. t
the second level, we have theranges %1& of PD' percentage %how
many samples from total cell samples we have in each
region&. nd in the third level we have cells:PD'
%3&.
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lso e(ually important is the definition of the range used in the
generation of the data, andconse(uently in the legend. Note that we
use the same coloring scale for cNo and >adio
+ink "ailure. $o, no matter if the coverage is #$M or 2M'$ for
e5ample if the region is
>ed, we know it/s badE %Or )*DM cNo worse than 96 d!, or #$M
>adio +ink "ailuremore than 7BJE&.
?nowing these details, we can do some demonstrations. #iving a
zoom in a more e5tensivearea, we see that we have multiple cells
with coverage in places where they should not be
covering. Of course, these points have a few samples, but with
vary bad (uality, as we seein the region shown below %9& ranges
mostly Pink, >ed and Orange.
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nalyzing specific cells, for e5ample /N/, we see that the same
coverage area is much
larger than it should %overshooting cell&, both the #$M
%9& and 2M'$ %1& are more than ;km of the serving cell.
-n this case, we have another interesting point, also seen
below4 most of the users in the
region %9& are served almost e5clusively by #$M. Now in
region %1& almost all users use)*DM. 'his is another point of
optimization4 these coverages should be, as far as possible,
/proportional/.
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nother e5ample4 the /!2/ site is a typical case of need of
urgent action, for e5ample by
increasing the tilt/s of overshooting cells. 'oo many samples at
more than ; km, and withpoor (uality. s these are cells of an urban
area, and in addition we have other cells serving
that distant locations, it is recommended to increase tilt, and
later run a new analysis.
'he opposite of what we saw above is also possible4 we can
identify cells that have a verygood coverage area %in this case, a
more contained area&, and with e5cellent (uality levels
%#reen and !lue&.
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)e could go on demonstrating several other analyses that are
possible using the datapresented here today. 8owever, the best way
is that you use these incredible resource in
your analysis, because with no doubt it represents a big
help.
Many people try to optimize the network based on parameter
changes only. !ut we saw thatin many cases like above, there may be
situations where the most recommended is physical
intervention %ad0usting of ntenna, 8eight, zimuth, 'ilt,
etc...&.
No doubt the analysis presented in this tutorial are essential
to the improvement of any
mobile network, and if you so far haven/t used, it/s a good time
to start.
Conl%sion
)e learned today an important concept used in many areas of
mobile 1#:3#:;# networks4the propagation delay, used as a tool for
assessment of the geographical distribution of
users.
'he measures are the 'iming dvance, that in #$M is measured by
the 2, and Propagation
Delay, that in 2M'$ is is calculated by the >N*. !oth allow
us to estimate the distance of the 2 until the serving cell,
conse(uently allowing several analysis, e5emplified above.
'he ' in #$M has a granularity of 77B meters, and the
Propagation Delay in )*DM hasgranularity of 13; meters. 2sing these
measures, we can /see/ e5actly where network users
are distributed at a level of cell:carrier:technology in each
region.
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-n addition, we have other measures, also mapped by region4 cNo
for )*DM and >adio+ink "ailure for #$M.
ll these measures together with other network information
%>adiant $ystems, zimuths,
'ilts, etc ...& give a huge help to the telecom professional
for analysis and optimizing taskswith significant results for the
improvement of the (uality of the entire network.
)e hope you en0oyed. 2ntil our ne5t meetingE
