2009114 Clarify in Gsm Network Pmo Cl092009

8/3/2019 2009114 Clarify in Gsm Network Pmo Cl092009

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Adapted For Distribution - CL092009

Abstract

Propagation model tuning is a fundamental part

of everyday GSM cellular engineering practice.

The model tuning is usually accomplishedthrough elaborate and costly tests based on

CW measurements. This paper evaluates

alternatives to CW testing where measurements

are collected using traditional GSM scanners

and PCTELs CLARIFY Interference Management

System.

Use of CLARIFY for

RF Coverage Analysis

and Propagation Model

Optimization in GSM

Networks

The results of the analysis reveal that

CLARIFY receiver provides a viable alternative

for CW tests in many practical situations.,Traditional GSM scanners are affected by the

co-channel and adjacent channel interference

and therefore their use should be limited to

cases of relatively low frequency reuse.


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PCTEL Technical Paper CL092009 Page 1 of 7

1. Introduction

In the operation and maintenance of GSM networks, radio

signal RF propagation modeling tools are widely used to

accomplish many significant RF engineering tasks. Network

planning, optimization, frequency planning, capital investment

planning or automated cell planning processes depend heavily

on the outputs of the RF propagation modeling tools. For that

reason, it is of utmost importance that engineers have access to

an accurate set of RF models.

In common engineering practice, the accuracy of the RF

propagation models is achieved through careful integration of

path loss measurements. The path loss measurements are

collected using a process called model tuning. In this process,

a group of test sites is selected to represent the morphology

within a given cellular market. The cellular market can

comprise much such morphology, each comprised of a distinct

subset of test sites. For each of the selected sites a Continuous

Wave (CW) transmitter is mounted and detailed path loss

measurements are performed. The measured data is then used

to determine the parameters for an optimizedRF propagation

model for a given morphological classification. In the end, theparameters of the optimized models are applied across the

board to all the cells in accordance with their morphology

classification. To achieve a high quality result for the modle

tuning effort, it is critical that empirical path loss

measurements are performance with high precision, high

sensitivity field equipment. Typically dedicated radios,

referred to in the industry as scanning receivers, are needed for

optimal results.

It is easy to see that the process of model tuning that is

based on extensive CW testing is cumbersome and costly.

Each site under the test needs to be set up separately and the

frequency plan needs to be modified to accommodate the CW

test frequency. That usually leads to drive testing of one testsite at the time and model tuning for even the smallest cellular

market may take days to accomplish. Additionally, despite all

of the efforts, one realizes that the RF propagation for the

majority of the cells in the market is not tested in the process.

Instead, most RF propagation models are determined on the

basis of qualitative assessment of cells RF propagation

morphology. As a result, even though the accuracy of the

models is generally improved, the level of improvement for the

entire market is difficult to assess. Strictly speaking, one can

only guarantee that the accuracy is achieved for the sites that

are in the selected test site group. For the rest of the sites, the

accuracy depends on the similarity of the sites RF propagation

environment to one of the representative morphologiesselected for the study.

Over the past few years several alternatives to CW testing

became possible. One may consider use of phone based

measurement devices, use of traditional GSM scanners or use

of CLARIFY high dynamic range receivers [1]. In theory, all

alternative systems allow data collection on a live network

without any special equipment set-up requirements.

Furthermore, they allow simultaneous measurements of all

cells without any disruption in the systems normal operation.

A rigorous analysis reported in [2] shows that the RSL

measurements obtained by the phone based devices are not

sufficiently accurate and repeatable. Therefore, for RF

propagation modeling purposes, phone based systems do not

offer a viable and cost effective alternative to CW testing. The

goal of this paper is to evaluate if CW based measurements

can be replaced by measurements obtained using traditional

GSM scanners or CLARIFY receivers.The outline of the paper is provided as follows. Section 2

describes the experimental procedure used for data collection,

including drive-test methodology, GSM base station and

equipment setup. Section 3 presents the analysis of the

obtained measured data, while observations and conclusions

are then outlined in Section 4.

2. Measurement procedure

The data presented in this paper were collected using

commercial measurement equipment and using processes

generally embraced in the standard engineering practice. Also,

the measurements are collected using existing commercialcellular network operating in the 850 MHz frequency band.

The details of the measurement procedure are provided as

follows.

2.1. Drive test methodology

The RSL measurements are taken in two typical GSM

network environments: suburban environment and dense urban

environment. Both environments are characterized with a

relatively flat terrain. The drive test routes are chosen in a

manner with good engineering practices associated with RF

propagation model tuning recommendations. The routes are

selected to capture the full dynamic range of signal strength of

the transmitter. The signals are sampled in radial and crossing

routes within the beam-width of the transmitting antenna.

During the drive test, the measurements are recorded

simultaneously by each measurement device. In order to meet

Lee sampling criteria [3], the maximum vehicle speed is

maintained to accommodate the slowest RSL collecting device.

In each environment, one serving sector is selected for the

study. To allow comparisons between the instruments a CW

transmitter is set up on the selected sector. The frequency

selected for the CW transmitter is within the network guard

band and therefore, it is unused throughout the network. As

such, the CW channel is transmitted without any co-channel or

adjacent channel interference. Unlike the CW receiver, both

the GSM scanner and the CLARIFY receiver measure

Broadcast Control Channel (BCCH) of the selected sectorunder the live network conditions. The network in the

suburban area uses frequency plan with the reuse of N=15 on

the BCCH layer. The reuse in the urban area network is N=30.

Both networks deploy ad-hoc frequency plan and therefore,

a regular reuse of the BCCH channels is not maintained.

The drive test routes for the suburban and urban areas are

illustrated as red traces in Figs. 1-2. The selected sectors are

presented in light blue color. From the figures, one may get


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better idea on the cell density within the two environments.

Typical separations between sites in suburban area are about 3-

5 miles, while in urban area the distances are reduced below

one mile.

TABLE I. BASE STATIONS SET UP

Parameter Suburban sector Urban sector

Tx centerline (ft) 278 120

BCCH CW BCCH CW

ARFCN 145 180(*) 144 170(*)

EiRP (dB) 42.36 40.36 42.96 40.96

(*) Channels 170 and 180 are in the guard bands of the two systems

2.2. Selected sector setup

At the selected sectors, the CW transmission shares the

same antenna system used for the GSM cell. The suburban

sector is on a self standing cell tower, while the urban sector is

mounted on a side of a tall building in a city core area. Further

details of the setup are given in TABLE I. One may notice

that there is a difference in the EiRP values between CW and

BCCH signals of about 2dB in favor of the last one. This

difference is taken into consideration in the post-processing of

the data and in the path loss calculations.

2.3. Equipment setup

The equipment setup used for data collection is presented

in Fig. 3. As seen, the drive test system contains a CW

receiver, a GSM scanner, and the CLARIFY high dynamic

range receiver. The system is equipped with external GPS and

RF antennas with the same characteristics, maintaining similar

path loss conditions.

The CW receiver has a 30 kHz band with a sensitivity of

-122 dBm. The scanner can measure and report the RSL, as

well as decode BSIC (Base Station Identification Code) if the

C/I (Carrier to Interference ratio) value of the surveyed BCCH

channel is greater than 2 dB. Due to the sophisticated signalprocessing techniques, CLARIFY can measure and associate

RSL signal to a specific sector, if the C/I value is above

-18 dB.

Every drive measurement system contains a laptop with

appropriate measurement software for automatic data

collection and location data association.

Figure 1. Suburban drive test area (Melbourne, FL, USA)

Figure 2. Urban drive test area (Orlando, FL, USA)

Figure 3. Drive-test equipment set-up

3. Data analysis

The primary goal of the data analysis is to establish the

level of difference between CW, scanner and CLARIFY


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measurements. An assumption is made that the CW

measurements are de facto benchmark and the analysis

compares the measurements of the alternative devices against

the ones obtained using CW. The comparisons may be made

on two principle levels. On the first level, one may compare

measurements themselves and determine how data collection

results differ. For example, of a great interest are the sizes of

the area over which the instruments collects data, existence of

bias between the instruments, the level of the data scatteringabout general trends, or the overall statistical behavior of the

data. On the second level, the comparison may be made

between the outcomes that result from the data application.

For example, one may use the data to optimize RF propagation

models and then compare how close the parameters of the

resulting models are.

Before analyses, all collected measurements are binned.

This is a standard process used in practice and it refers to

spatial averaging of the individual RSL measurements over a

small geographical area called bin. The binning process tends

to eliminate impact of the fast fading. In this study, the

binning process is performed in accordance with

=

=iN

j

j

i

iRSL

NRSL

1

1(1)

wherei

RSL is the averaged RSL in i -th bin,j

RSL is the RSL

of the signal expressed in dBm found in i -th bin, andi

N is the

total number of samples in i -th bin.

The size of the bin is usually determined by the terrain

resolution used in the RF propagation modeling tool. Some

common bin sizes are 30 m, 50 m and 100m. In this study, the

analysis is done with bin sizes of 30 m and 50 m. The

differences between the results for the two bin sizes are

negligible and for the sake of brevity only 30 m results are

reported.

3.1. Measurable Sector Area (MSA)

Measurable sector area (MSA) is defined as the size of the

area in which the signal from the selected sector can be

measured using a given tool. MSA can be expressed in either

number of bins with measurements, or the physical size of the

area with measurements. One should remember that in this

paper, a bin is 30 m by 30 m square, so the conversion

between the bin count an the area size is straightforwrad.

Representative MSAs obtained from measured data for the

three devices are presented in Figs. 4-5. In the Figs., the CWs

MSA is presented with a red trace; the scanners MSA is

illustrated with a blue trace, while CLARIFY MSA is shownwith a green trace. In the case of suburban environment, it can

be seen that a very good match exists between CW

measurements and the measurements obtained through

CLARIFY. For the traditional GSM scanner the overlap is

significantly smaller. In the case of urban environment, both

the scanner and CLARIFY exhibit significantly smaller MSA

relative to CW. The reason is predominantly due to the very

tight frequency reuse deployed in the urban area under the test.

The cells with co-channel and adjacent channel BCCH

assignments are highlighted in Fig 5. Co-channel and adjacent

reuse sectors are highlighted in red and yellow respectively.

As seen, within this relatively small area there are four co-

channel BCCH reuses and there are seven adjacent BCCH

assignments. Such a tight reuse of frequencies decreases C/I

which in turn directly impacts the capability of both GSM

tools in taking the path loss measurements.

The MSA size values for both environments are

summarized in TABLE II. As seen, the limited dynamic rangeof the GSM scanner results in significant reduction of the

MSA. Therefore, from the standpoint of MSA size, the GSM

scanner may be used only in parts of the network with a low

frequency reuse. On the other hand, the MSA of CLARIFY

receiver seems to be quite comparable to that of CW in the

case of suburban environment. That indicates that in cases of a

low to moderate frequency reuse, CLARIFY receiver is a

viable substitute for the CW measurement set. This is good

news since the areas of low to moderate reuse are typically in

rural and suburban environments where the cells are of larger

sizes. In these environments, capability of taking

measurements for multiple cells at the same time results in

large cost savings. The table also contains the total number ofbins common to both CW and the compared GSM tool.

TABLE II. MSA RESULTS

Drive

Device

Parameter

CW

scanner

GSM

scanner

CLARIFY

receiver

MSA in bins 8133 5342 7703

MSA relative to

CWn/a 65.68% 94.71%

Suburban

No. of common

bins with CW

n/a 5032 7703

MSA in bins 4534 1031 2021

MSA relative to

CWn/a 22.74% 44.57%

Urban

No. of common

bins with CWn/a 1031 1802


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Figure 4. MSAs for the suburban area for the sector in blue

Figure 5. MSAs for the urban area for the sector in blue

3.2. Path loss analysis

A representative portion of the RSL measurements using

the three tools is presented in Figure 6. The traces are offset

for easier representation. The CW RSL measurements arepresented with the lowest (in horizontal layout) and left (in

vertical layout) traces. The middle (in both horizontal and

vertical layout) traces illustrate the CLARIFY receivers path

loss data. The scanner path loss measurements are presented

with the top trace in horizontal layout) and right (in vertical

layout) traces.

From Fig. 6, one may readily observe high agreement

between RSLs collected by the CW and CLARIFY receiver.

However, in the vicinity of co-channel and adjacent channel

interferers, the performance of both the traditional scanner and

CLARIFY receiver is affected. The impact is more evident in

the case of traditional scanners, in whose case the result

manifests as missing sample points or incorrect readings. In

the case of CLARIFY receiver, owing to its high dynamic

range receiver and its higher tolerance to co-channel and

adjacent channel interference, there are more sample points

and also more sample with correct readings.

The RSL measurements and the EiRP values fromTABLE I are used to determine the path losses. For each

common bin, the pair wise differences between the path loss

measurements are obtain using

[ ] [ ]dBdB toolCWtoolCW PathLossPathLoss = (2)

where tool can be either the scanner or the CLARIFY

receiver.

TABLE III. contains the principal results of the path loss

(PL) statistical analysis. For the suburban drive, the mean

values of the differences between scanner and CW as well as

the difference between the CLARIFY receiver and CW are

both very close to zero. This implies that all three tools

express very similar PL calculations on average. However,

the variations of PL values are in range of 2 dB and 4 dB for

the CLARIFY receiver and the scanner respectively. For the

urban environment, almost zero PL difference in case of the

CLARIFY receiver is preserved. However, PL measurements

of the scanner are significantly degraded due to the impact of

co-channel and adjacent channel interferers. These

degradations may have considerable impact on the model

tuning process during the RF propagation modeling.

Figure 6. An example of the path loss measurements using different tools

TABLE III. PATH LOSS RESULTS

Drive

Device

Parameter

GSM

scanner

CLARIFY

receiver

Mean (cw device) [dB] -0.47 0.33

Suburban

St. dev. (cw device) [dB] 4.12 2.26


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Mean (cw device) [dB] -5.42 -0.69

Urban

St. dev. (cw device) [dB] 3.73 3.83

Figure 7. PDF/CDF for PL differences between the CW and the GSM

scanner for the suburban drive

Figure 8. PDF/CDF for PL difference between the CW and the CLARIFY

receiver for the suburban drive

Typical normalized histograms of the differences between

the PL measurements, as well as cumulative distribution

functions are presented in Figs. 7-8. From the shape of the

curves, the PL differences seem to exhibit largely a lognormal

character with means and standard deviations as reported in

TABLE III.

3.3. Empirical CDF comparison (K-S test)

In order to compare the CDF functions (as presented on

Fig. 7-8), the Kolmogorov-Smirnov test (K-S test) of

goodness-of-fit is used. The K-S test is a good test to identify

which tool, if any, provides PL measurements comparable to

CW tool, which is used as the benchmark. The test is

structured as follows. In the first step, the empirical cdf

functions are constructed. In the second step, a statistic,

denoted by ( )nD , is found using

( ) ( ) ( )xFxFnDtoolCWX

= max (3)

where ( )xFCW

represents CDF developed using the CW data,

and ( )xFtool

corresponds to CDF found for either scanner or

CLARIFY receiver data. In other words, ( )nD equals to thelargest absolute deviation between two functions when all

values ofx are considered. It is important to notice that the

statistic does not depend on the form of ( )xF , but only on thesample size, denoted by n . The statistic ( )nD can becomputed with respect to different confidence intervals.

Usually, the sampling distribution of ( )nD is presented intables, for different confidence levels and number of samples

[4].

The null hypothesis for the K-S test is that both data sets

are drawn from the same continuous distribution. The

alternative hypothesis is that they are drawn from different

continuous distributions. In this report, the hypothesis is

accepted if the test is significant at the 95% level. Typical

CDF functions obtained from the three tools are illustrated in

Figs. 9-10.

From Fig. 9, one can easily observe a significant

difference between CDF functions formed using the CW andthe scanners data. On the other hand, the almost overlapping

CDF functions are constructed using the CW and the

CLARIFY receiver data. Formally, the K-S test passes the

null hypothesis for the CLARIFY receiver in both suburban

and urban environments. The null hypothesis is accepted for

GSM scanner data only in the suburban environment.

70 80 90 100 110 120 130 1400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

PL [dB]

F(x)

Empirical CDF

CDF developed with CW PL data

CDF developed with s canner PL data

Figure 9. An example of empirical CDF functions for the CW receiver and

the GSM scanner


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80 90 100 110 120 130 1400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

PL [dB]

F(x)

Empirical CDF

CDF developed with CW PL data

CDF developed with Receiver PL data

Figure 10. An example of empirical CDF functions for the CW receiver

and the CLARIFY receiver

3.4. Model tuning

The path loss measurements collected by the three

instruments are used to perform the model tuning for the

selected sector. A simple Lee macroscopic RF propagation

model [3] is selected and the measurements are used to

determine the optimum values for the slope and the intercept

parameters of the model. The results of the model tuning are

presented in TABLE IV.

As seen, despite differences in MSAs the models

developed using CW and CLARIFY data are almost identical

in both suburban and urban environments. The slope and

intercept values are within 0.5 dB of each other in both cases.

Therefore, it seems that even though the size of the MSA is

affected by the frequency plan, the application of the

CLARIFY receiver data in model tuning leads to models that

are very close to the ones developed on the basis of the CW

data collection.

TABLE IV. PMO RESULTS

Drive

Device

Parameter

CW

scanner

GSM

scanner

CLARIFY

receiver

Optimized intercept

[dBm]-64.8 -65.4 -64.4

Optimized slope

[dB/decade]-40.5 -35.8 -40.1

Mean (measured and

predicted) [dBm]0 0 0

Suburban

St. Dev. (measured and

predicted) [dBm]6.6 7.2 6.5

Optimized intercept

[dBm]-66.6 -61.2 -66.4

Optimized slope[dB/decade]

-38.8 -37.9 -38.5

Mean (measured and

predicted) [dBm]0 0 0U

rban

St. Dev. (measured and

predicted) [dBm]5.1 6.1 6.4

The models obtained using the GSM scanner data seems

to be quite optimistic when compared to the CW based model.

In a given scenario, the optimistic nature of the GSM scanner

based model may result in a considerably higher one mile

intercept or in a considerably lower slope. The optimistic

model is a result of inability of regular GSM scanners to deal

with the co-channel and adjacent channel interference.

4. Observations and conclusions

This paper considers the feasibility of using GSM

scanners and CLARIFY receivers as substitutes for CW-based

test systems. A side-by-side comparison of the measurements

collected by the three device types was performed and the

findings may be summarized as follows.

The MSA of the GSM scanner is affected by the

frequency reuse and is considerably smaller than the MSA

for the CW receiver.

Due to frequency reuse interference, the GSM scannershows a noticeable bias towards underestimating the path

loss. The bias depends on the frequency plan and

resulting amount of co-channel and adjacent channel

interference.

If the GSM scanner data is used for model tuning, theresulting models are the over-predicting path loss.

The MSA of CLARIFY receiver is quite close to the MSAof the CW receiver in cases of low to moderate frequency

reuse (N > 15). In urban areas of high frequency reuse,

the MSA of the CLARIFY receiver is reduced.

The average difference between the path lossmeasurements between the CW tool and the CLARIFY

receiver is negligible (< 1 dB).

As per Kolmogorov-Smirnov test of goodness-of-fit, thestatistics of CW data are in very good agreement with the

CLARIFY receiver data for both environments. Incontrast, GSM scanner exhibits good fit with the CW test

only in a light frequency reuse environment.

The CLARIFY receiver data leads to virtually identicalRF propagation models as the ones developed using the

CW measurements.

The results of the study reported in this paper indicate that

the CLARIFY receivers with high dynamic range

(C/I >-18 dB), represent a viable practical alternative to CW

testing. This is especially the case in networks with low to

moderate frequency reuse factor (N > 15). Even in the areas of

high frequency reuse, the estimates of the RF propagation

model parameters obtained from the CLARIFY receivers dataseem to be quite close to the ones obtained from the CW

measurements. On the other hand, the measurements obtained

by regular GSM scanners seem to be quite sensitive to the co-

channel and adjacent channel interference and they may

approximate CW measurements only in limited scenarios when

the frequency reuse is low.


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5. Acknowledgments

Authors would like to express a sincere appreciation to

Mr. Dale Bass, from PCTEL, Inc. RF Solutions Group,

Germantown, MD. The authors are grateful to ATT Wireless

for allowing use of their network, as well as PCTEL Inc. and

Envision Wireless for providing exceptional support and tools.

Data analysis was performed with data post processing

platform Gladiator from QualiTest Technologies, Inc.

6. References

[1] N. Mijatovic, I. Kostanic, S. Dickey, Comparison of ReceiveSignal Level Measurement Techniques in GSM CellularNetworks, in proceedings of CCNC 2008, January 10-13, 2008.

[2] I. Kostanic, N. Mijatovic, Repeatability of Received SignalLevel Measurements in GSM Cellular Networks, inproceedings of ISWPC 2007, San Juan, Puerto Rico (2007)

[3] W.C.Y. Lee, Wireless and Cellular Communication, McGraw-Hill, 3rd Ed. 2005.

[4] J. Neter, W. Wasserman, G. A. Whitmore,Applied Statistics, 2ndEdition, Allyn and Bacon, Boston, 1982.

7. Authors

Nenad Mijatovic, Ivica Kostanic

(Florida Institute of Technology, Melbourne, FL, USA)

Greg Evans

(at&t wireless, Orlando, FL, USA)

[Adapted From Use of Scanning Receivers for RF Coverage

Analysis and RF propagation Model Optimization in GSM

Networks Mijatovic, Kostanic & Evans; 2008; Originally

presented at EW2008, June 22-25 2008, Prague, Czech

Republic.]

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2009114 Clarify in Gsm Network Pmo Cl092009