1. CustomerA Optimization Service
360Cellutions Case Study
February 2012

2. P a g e | 3
Mission Statement
To bring quantitative improvement in CustomerA network through
enhanced visibility, extensive field testing, comprehensive statistical
analysis, precise technical recommendations and an efficient follow up
process

3. P a g e | 4
Executive Summary
The 360Cellutions Optimization service for the SSS network has been a resounding success.
In the short time of four months, 451 recommendations were given by the 3 team out of
which 202 have been implemented. 38% of the implemented recommendations resulted in
the problem being solved, 41% are under investigation. Only 20% showed no change and 1%
showed degradation.
All network KPIs have shown a significant improvement: CINR 15%, Throughput 15%,
Utilization 5%, Usage 27%, QPSK 8%, BaseDiversity 11%. The details are given in the next
section titled Network Improvement Summary. Less than 2% of recommendations have
required addition of CapEx (new site or sector).
In addition to the considerable network performance improvement, 360Cellutions has
provided vital help in other areas. An advanced method of viewing statistics was introduced
called SYS, which CustomerA team has appreciated so much that they have decided to model
their main statistics interface on the same lines (health-check report). SYS has helped
increase network visibility by the design of customized reports like Daily Dashboards, City
Reports, Worst-Cell Reports.
Comprehensive drive test of the three major cities has been done daily by the 360Cellutions
team and analyzed using an advanced post-processing software called FDI, which has
revealed issues previously unknown. This has contributed immensely to the successful results
mentioned above.
A scanning interface called JET was provided by 360Cellutions to address the absence of a
scanning tool in CustomerA. Scanning mode drive test is widely regarded as the most
relevant and important way of drive testing a nomadic Wimax network like CustomerA’s, JET
filled this void with its simple interface and efficient sampling capability.
In addition to this, 360Cellutions had noticed around 400 AP sectors’ stats were missing, and
hence not visible in any statistics analysis. 360Cellutions provided a solution for making
them visible so their performance can be monitored and faults detected and fixed.
360Cellutions has explored new data sources, like Dereg codes, which has given a new
perspective on Network Performance, and helped solve chronic problems by correlating these
data
sources with conventional data sources like AP stats and drive test.
A constructive and cordial working relationship between 360Cellutions and CustomerA
teams has prevailed and it has been evident in the results.

4. P a g e | 5
Network Improvement Summary
The graphs below show statistical improvement on sectors where recommendations have
been implemented.
• CINR Good (RF Quality) has improved by 15%
• Usage in Mega Bytes has increase much more sharply (27%) than Utilization (5%)
showing new traffic added is mostly of good quality and at higher data rates
• The above point is further confirmed by two methods: change in coding scheme
distribution (QPSK has been lowered by 8% and QAM-64 increased by 4%) and by the
fact that Base Diversity has reduced by 11% and replaced by MIMO
• Throughput increased by 15%
0
20
40
60
80
100
120
140
3-Oct
11-Oct
19-Oct
28-Oct
5-Nov
13-Nov
21-Nov
30-Nov
12-Dec
20-Dec
28-Dec
NESR UL NI CINR Good
0
5
10
15
20
25
30
35
3-Oct
11-Oct
19-Oct
28-Oct
5-Nov
13-Nov
21-Nov
30-Nov
12-Dec
20-Dec
28-Dec
RF_DL_Util RF_UL_Util
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
9,000,000
10,000,000
3-Oct
12-Oct
22-Oct
31-Oct
9-Nov
18-Nov
28-Nov
11-Dec
20-Dec
29-Dec
DL sector usage MB
Total sector usage MB
0
10
20
30
40
50
60
70
80
90
100
3-Oct
11-Oct
19-Oct
28-Oct
5-Nov
13-Nov
21-Nov
30-Nov
12-Dec
20-Dec
28-Dec
QAM64 (%) QAM16 (%)
QPSK (%)
0
10
20
30
40
50
60
70
80
90
100
3-Oct
11-Oct
19-Oct
28-Oct
5-Nov
13-Nov
21-Nov
30-Nov
12-Dec
20-Dec
28-Dec
MIMOA DL MIMOB DL
BaseDiv DL
0
0.2
0.4
0.6
0.8
1
1.2
1.4
3-Oct
10-Oct
17-Oct
25-Oct
1-Nov
8-Nov
15-Nov
22-Nov
30-Nov
11-Dec
18-Dec
25-Dec
1-Jan
DL_RF_Throughput

5. P a g e | 6
Analysis Solution
Stats and
Drive Analysis
On field
testing
Enhanced
Visibility
Technical
Recommendations
Data collection
Introduction
The mission statement of this project clearly identifies the objective, strategy and methodology
for the implementation of the project. The objective of the project is to bring quantitative
improvement in CustomerA network performance. The strategy is divided into three phases:
Data Collection, Analysis and Solution. This is translated into four distinct sections.
1. Visibility
2. Field Testing
3. Stats and Drive analysis
4. Technical Recommendations
This report will cover in detail these four sections.
The fifth section of the report will provide the details of the follow up process designed
and adopted during this project.
The last section, Extra mile, will highlight additional initiatives taken by 360Cellutions to
directly and indirectly help accomplish the overall goal of improving the CustomerA network.

6. P a g e | 7
1. Visibility
Telecommunication networks generate a colossal amount of data related to the performance of
the network. All of this data is useful and can potentially indicate faults. It’s a challenging task to
develop a system to organize this important data and give visibility of network faults to the
network engineers.
360Cellutions has provided a comprehensive system of gaining visibility to the CustomerA
network and its performance. This can be divided into the following sections, each section will
be explained in the following pages:
 SYS Service – A method to store and analyze network statistics
 KPI Formulating and Threshold – Key Performance Indicator definition and
prioritization
 FDI Service – A method to store and analyze drive test data
 Daily Reports – The creation and design of reports on various network aspects for a
variety of audiences
 Dereg – A procedure for export and storage of Dereg codes
 Alarms – A procedure for export and storage of AP alarms
1. SYS Service
SYS is a KPI and statistics analysis tool for cellular networks. It's multi-vendor, scalable and
customizable, as per the client requirements. It has a simple and efficient interface and
produces comprehensive reports. Stats downloaded from the CustomerA server are loaded
in the SYS database through a fully-automated process. SYS is used for the following tasks:
 Detailed reports
 Worse cell compilation
 Intuitive graphical view
 Correlation with Alarm logs, Dereg codes and CAPC stats
 Multiple time intervals (hourly, daily, BI)
 Custom reports
 Custom KPI definitions
 Multiple level grouping (city, network, cell)
SYS provides a comprehensive platform for network stats, organized in the following
categories:
 Intervals – Daily, Busy Interval and hourly
 Entities – CapC, AP
 Grouping is done by cities and cells
SYS outputs graphical as well as tabular data, an example of a report is given below. Its called
Health Check and shows the complete performance of a network entity in one screen:

7. P a g e | 8
2. KPI formulation and threshold setting
360Cellutions in consultation with CustomerA team formulated a system of Key Performance
Indicators (KPIs) to monitor the network efficiently. The different aspects of this initiative
are as follows:
 A criteria was formulated by 360Cellutions in cooperation with CustomerA team to
come up with 5 most important and diverse KPIs which form the Worst Cell
Report. This report is regularly used to indicate the faulty cells in the network. For
each of these cells HealthCheck is run to confirm the problem and recommend a
solution.
 HealthCheck is a one page report which gives a complete snapshot of a network
entity (sector, AP, city, network etc). The 26 KPIs that form the healthcheck were
carefully selected to ensure that all aspects of the entity are represented.
360Cellutions engineers as well as CustomerA team have become familiar with the
health check format and in one quick glance they are able to pinpoint the fault.
Otherwise this could have taken hours and many issues would have been missed, if
the traditional way of looking at tabular data was used.
 Some new KPIs were introduced by 360Cellutions to make the stats analysis more
comprehensive. An example is the End to End NESR analysis using CapcC stats, and

8. P a g e | 9
breaking NESR into three parts: Air Interface, Authentication and Registration,
which gives the success rate of a new connection over all interfaces.
3. FDI service
FDI is a drive test post-processing software, which takes drive based optimization to the next
level. It provides optimizers with previously unheard of features which are designed to
intelligently pin-point network issues, and effectively solve problems. It has many advanced
features, like best server option for scanned mode drives, binning over user defined grids for
any layer, theoretical layers of low coverage and interference for scanned mode drives using
user defined parameters. As will be shown in the following sections, numerous coverage,
interference and other issues were precisely found and rectified with the help of FDI by the
360Cellutions team.
4. Daily Reports
 Network Dashboard: contains 5 major KPIs listed for last 2 days. It gives a quick
glance at any improvement or deterioration in last 2 days, and is a quick glance for
senior management to see the overall network performance. Any deterioration is caught
at a glance and hence leads to further analysis and trouble shooting. All Network
Dashboards sent can be found on the accompanying DVD.
 City Report: contains detailed health check graphs of each city Karachi, Lahore and
Islamabad/Rawalpindi. Both daily and Busy Interval analysis are included in this report.
All City Reports sent can be found on the accompanying DVD.
 Worst Cell Report: contains cells that underperform on a particular day. Performance
of cells for this report is analyzed using five performance metrics (KPIs) namely;
o Average Uplink Noise and Interference
o Network Entry Success Rate
o Base Diversity Downlink Slot Utilization
o MIMO B Downlink Slot Utilization
o Downlink RF Quality by Kilobyte Low (QPSK)
 Down Sites: contains detailed health check graphs of cells that are not working. Down
Cells are traced using network stat Average Uplink Noise and Interference. It’s an
important report and shows cells whose outage could potentially be causing in the loss of
revenue and poor coverage. All Down Sites Reports sent can be found on the
accompanying DVD.
 Low Traffic Cells: contains cells with low usage. This report is generated using stats of
last day and a week prior to last day. Only cells which had high usage earlier are
included to indicate cells underperforming and discard cells that have low usage
regularly. All Low Traffic Reports sent can be found on the accompanying DVD.
5. Deregistration Codes
When a customer disconnects from CustomerA’s network it generates a Deregistration
reason code depicting the reason for its disconnection. These codes are stored in the network
for retrieval and analysis. Only the latest Dereg codes are available in the APs, and older ones
are regularly deleted due to limited space on the AP.
360Cellutions, for the first time in the CustomerA network extracted these important codes
and used these codes in CustomerA network analysis. These codes are now permanently
stored in SYS. Several issues were identified as a result of this analysis. CPEs that were

9. P a g e | 10
causing KPI deterioration persistently and Sites (AP’s) that were causing degradation have
been identified.
6. Alarm analysis
Network elements generate alarms whenever an active element malfunctions. 360Cellutions
has formulated a process of extracting Network Alarms from CustomerA and Alarms are now
stored permanently in SYS.

10. P a g e | 11
1. Field Testing
Field testing is one of the important sources of data for any wireless communications network.
On field data collection provides important information related to coverage, interference and
over shooting. In this project, 360Cellutions team conducted two different types of field testing.
1. Scan Mode
Scan mode drive test collects the RF information of all the frequencies in the network. This
is most important and frequent type of field test for Wimax network as it provides
information about Coverage level (RSSI), Carrier to Interference Ratio (CINR) and site
attributes (BSID, Preamble, frequency). The scan mode field data coupled with state of the
art FDI service provided a very detailed drive analysis. The 360Cellutions team detected,
low coverage issues, high interference areas, database mismatches, swap sectors and cell
over shoots by analyzing scan files through FDI.
Initially, Agilent E6474 was used to collect the on field data using Motorola USB Wimax
device. Later, scan mode data collection over Green packet was made possible through
introduction of JET, a scan mode data collection tool.
2. Dedicated Mode
Dedicated mode drive test was conducted to further investigate worse cells detected
through stats analysis. It provides information regarding modulation scheme, UL/DL
throughput and MIMO type. In this mode relevant sector frequency is locked and drive is
done in the coverage area of that cell while uploading and downloading files. Since it
provides information related to one cell at a time the dedicated mode campaign was
specific to worse cells. In total, the testing was conducted on 46 sites in Karachi (where
dedicated mode drive test kit was available).
In order to monitor the data collection and analysis activity Cities are divided into clusters of
reasonable size. The cluster strategy also helped CustomerA team to implement recommended
changes in chunks. Karachi city was divided in 14, Lahore in 17 and Islamabad/Rawalpindi in 6
clusters. Table 3.1 shows the list of clusters with naming convention containing information of
the covered area. During field testing speed was kept below 35km/h to get samples for all the 5
frequencies at a particular location.

11. P a g e | 12
Table 3-1: List of clusters
Karachi Lahore Islamabad/Rawalpindi
KHI01_E_01 LHR01_E_01 ISB01
KHI01_E_02 LHR01_E_02 ISB02
KHI01_E_03 LHR01_E_03 ISB03
KHI01_E_04 LHR01_E_04 ISB04
KHI01_E_05 LHR01_E_05 ISB05
KHI01_E_06 LHR01_E_06 ISB06
KHI01_E_07 LHR01_E_07
KHI01_E_08 LHR01_E_08
KHI01_E_09 LHR01_E_09
KHI01_E_10 LHR01_E_10
KHI01_E_11 LHR01_E_11
KHI01_E_12 LHR01_E_12
KHI01_E_13 LHR01_E_13
KHI01_E_14 LHR01_E_14
LHR01_E_15
LHR01_E_16
LHR01_E_17

12. P a g e | 13
Implementation Status
The first round of scan mode drive test and analysis is finished in all three cities. Whereas
the second round is 60% completed for Lahore. The initial schedule was disturbed due to
unavailability of drive testing equipment. Table 3.2 provides the detail of the drive
schedule.
Scan mode drive test of Karachi, Lahore and Islamabad/Rawalpindi is completed. Figure
3.1, 3.2 & 3.3 provide snap shot of drive test done in Karachi, Lahore and Islamabad
respectively.
Figure 3-3: Islamabad scan drive updated
Figure 3-1: Karachi scan drive update Figure 3-2: Lahore scan drive update

13. P a g e | 14
This was an important service as it provided the information leading to many fault removal. For
example; there are 41 swap sectors detected till date through field testing and analysis. Figure
3.4 shows on of the detected cases.
Figure 3-4: Swap sectors detected through Scan Drive. Post drive shows the condition after
implementation of recommendation
Pre Post

14. P a g e | 15
2. Network Analysis
Network analysis is of two types:
1. Stats and KPI Analysis
• Worst Cell Report is a routine process to identify the worst performing cells and give
recommendations for performance improvement on a regular basis
• Congestion Report identifies the worst congested cells and give recommendations to
solve congestion on these cells
• Low Traffic Cells Report identifies the lowest traffic cells
• Down Sites Report identifies Down sites
2. Drive Data Analysis
A drive analysis report on cluster basis, giving details of each problem found in the drive test
and giving recommendations for solving these problems
The details of stats and drive analysis are given below divided into three sections: Worst Cell
Report; Other KPIs analysis; Drive Analysis. Insight into the methodology used and some
examples are given to show how this analysis has helped in fixing faults and improving network
performance.

15. P a g e | 16
1. Worst Cell Report
Worst cell report contains the daily worst cells of the network due to the following KPIs
KPI Name Meaning Criteria Data Sources for
Analysis
Common Cause
and Solution
Network Entry
Success Rate
(NESR)
Percentage of times
CPEs successfully
connect to an AP
sector
• Entry attempts >
1000
• Peak CPEs daily
average > 10
• NESR < 20%
• Atleast 2 days
• AP stats
• Dereg codes
Faulty or
unauthorized
CPEs trying to
access.
Dereg codes can
identify these
CPEs which need
to be removed or
replaced
Uplink Noise
Interference
(NI)
High Noise
Interference in the
Uplink direction
• NI > -125
• Atleast 2 days
• NI = 95
indicates down
sector
• AP stats
• Alarms
Frequency
Interference,
misaligned ODU,
hardware fault
High Base
Diversity (BD)
Instead of using
MIMO the AP sector
is using Base
Diversity affecting
the performance
adversely
• Peak CPEs daily
average > 10
• Base Div % =
100%
• Atleast 2 days
• AP stats
• Alarms
Transceiver,
passive elements
and RF head need
to be checked for
fault
Zero MIMO-B MIMO-B enhances
sector capacity and
average throughput
• MIMO-A > 10%
• MIMO-B = 0%
• Atleast 2 days
• AP stats
• Alarms
Antenna or
passive elements
need to be
checked for fault
High QPSK High percentage of
QPSK modulation
usage
• QPSK > 10%
• Peak CPEs daily
average > 10
• Atleast 2 days
AP Stats Bad coverage,
faulty hardware
A few examples are given below. The details of each recommendation given by 360Cellutions
can be found in all the Worst Cell reports given on the accompanying DVD.

16. P a g e | 17
Poor NESR Example:
0
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140
3-Oct
8-Oct
13-Oct
18-Oct
27-Oct
1-Nov
6-Nov
11-Nov
16-Nov
21-Nov
27-Nov
2-Dec
11-Dec
16-Dec
21-Dec
26-Dec
31-Dec
5-Jan
10-Jan
15-Jan
20-Jan
25-Jan
30-Jan
4-Feb
9-Feb
NESR UL NI
• MUI90_B had poor NESR of below 50%
since October 2011
• Dereg codes were analyzed
• CPE with MAC 00:1b:dd:77:4d:c9 was
found to be sending repeated unsuccessful
attempts
• Case sent to CompanyA and faulty CPE
removed from network
• Current NESR stays more than 80%

17. P a g e | 18
High Base Diversity Example:
Zero MIMO-B Example:
0
20
40
60
80
100
3-Oct
11-Oct
19-Oct
30-Oct
7-Nov
15-Nov
23-Nov
2-Dec
14-Dec
22-Dec
30-Dec
7-Jan
15-Jan
23-Jan
31-Jan
8-Feb
MIMOA DL MIMOB DL BaseDiv DL
• Sector GIJK_C Base Diversity 100% since
October 2011
• Reported by 360Cellutions as worst cell
• RF Head faulty confirmed by CompanyA
operations and fixed
• Now very little Base Diversity
• Usage and throughput increased by more
than 200%
0
500
1000
1500
3-Oct
9-Oct
15-Oct
24-Oct
30-Oct
5-Nov
11-Nov
17-Nov
23-Nov
30-Nov
10-Dec
16-Dec
22-Dec
28-Dec
3-Jan
9-Jan
15-Jan
21-Jan
27-Jan
2-Feb
8-Feb
DL sector usage MB Total sector usage MB
0
2
4
6
8
10
3-Oct
9-Oct
15-Oct
24-Oct
30-Oct
5-Nov
11-Nov
17-Nov
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10-Dec
16-Dec
22-Dec
28-Dec
3-Jan
9-Jan
15-Jan
21-Jan
27-Jan
2-Feb
8-Feb
DL_RF_Throughput
• Sector XYZ_A MIMO-B 0% since
October 2011
• Reported by 360Cellutions as worst cell
• Faulty Hardware fixed
• Now MIMO-B about 40%
• Usage and peak CPEs increased
significantly

18. P a g e | 19
2. Other KPI based analysis
KPI Name Meaning Criteria Data Sources
for Analysis
Common Cause and
Solution
Congested
Cell
(High RF
Utilization)
Cells with high
data utilization
which results in
poor customer
experience due
to low data
rates
•DL RF Utilization
> 80%
•DL RF
Throughput >
4Mbps
•6 consecutive
days
AP stats High number of users
with high data usage.
Network redesign like
downtilt, uptilt of
neighbouring cell etc
can mitigate this
issue
Low Traffic
Cell
(Low Data
Usage)
Sectors with
very low data
usage
•Peak CPEs daily
average < 1
•DL Usage >
50MB
•Aleast twice in 7
days
AP stats Few users in the
vicinity. The sector
can be removed and
used elsewhere.
Down Cell
(NI = 95)
Sectors with no
activity due to a
fault
•NI = 95
•Peak CPEs daily
average = 0
•RF Thput = 0
•RF Usage = 0
AP stats,
Drive
Hardware faulty
needs to be replaced
Congested cells report can be found on the accompanying DVD.
Low traffic cell report can be found on the accompanying DVD.
Down cell report can be found on the accompanying DVD.

19. P a g e | 20
Down Cell Example:
• Sector KRCH_B NI
95 between Dec 18 –
28
• Utilization is 0
• Throughput is 0
• After issue
resolution, all stats
back to normal

20. P a g e | 21
3. Drive Analysis
Drive test in scanned mode is the primary source of drive data analysis. In a nomadic Wimax
network like CustomerA (no mobility) scanned data is the most relevant drive data and it is
analyzed comprehensively. The following issues were analyzed in all cluster drives and
recommendations for each problem were given in cluster analysis reports. All cluster analysis
reports can be found on the accompanying DVD.
As has been pointed out earlier dedicated mode drives are only done in specific issues i.e. to
confirm if a certain modulation scheme is not available on a cell.
Issue Type Meaning Criteria Data Sources
for Analysis
Common Cause and
Solution
Low
Coverage
Insufficient RF
coverage for
satisfactory user
experience
•RSSI < -80
•CINR < 10
Scanned
Mode Drive
No sites nearby, or
site not transmitting
properly. New site,
network redesign or
fault resolution.
Interference Sectors with very
low data usage
•RSSI > -80
•CINR < 10
Scanned
Mode Drive
Wrong frequency
assignment, needs to
be corrected
Swapped
Sector
Sector radiating in
the wrong
direction relative
to the direction
installed
N/A Scanned
Mode Drive
Improper
installation, needs to
be physically
corrected
Database
Issues
Field data and
network database
mismatch
N/A Scanned
Mode Drive
Either the database
needs to be changed
or site parameter
changed

21. P a g e | 22
An example of issues found during drive test is given below:
Low Coverage:
• Snapshot shows Block F Model Town, Lahore has low coverage.
• Pre drive test conducted on 28th October 2011
• Following changes requested by 360Cellutions:
o LDRC_A: Change mechanical tilt of antenna from -7 to -5
o LHFB_C: Change mechanical tilt of antenna from -7 to -5
• Above changes were implemented by CompanyA on 10th December 2011
• Post Drive test was conducted to validate changes on 10th January 2012
• Post drive plot shows coverage has improved considerably after changing the
parameter suggested by 360Cellutions.
Pre Post

22. P a g e | 23
3. Redesign Recommendation
The enhanced visibility, extensive on field testing provided the ingredients for comprehensive
analysis. To have an impact on network performance, all analysis should lead to precise and
practical recommendations. These recommendations are the solution for the observed problem.
In this project, 360Cellutions adopted a systematic approach to provide and finalize the
recommendations. The types of recommendations were fixed and each type was reached after a
standard investigation process. Following are different types of recommendations;
 Up Tilt Antenna
 Site Reboot
 Replace faulty Hardware
 Site Health Check
 Change Preamble
 Check CPE Provisioning
 Replace Faulty CPE
 Change Azimuth
 Down Tilt Antenna
 Retune Frequency
 Increase Power
 Rectify Sector Swap
 Enable Stats
 Bring Site up
 Add new Sector Addition

23. P a g e | 24
1. Total status
Since the start of the project total, 451 technical recommendations are forwarded to
CustomerA team for implementation. Table 4-1 provides the details of these
recommendations. These precise recommendations are provided after extensive analysis and
correlation of different data sources.
Table 4-1: Recommendation details
Recommendation type No of recommendations
Up Tilt 161
Frequency 37
Sector Swap 46
Site Health Check 35
Stats 19
Azimuth 28
Site Down 15
Down Tilt 12
Preamble 13
Sector Reboot 56
Check CPE Provisioning 5
Other 9
Power Increase 9
Replace Faulty CPE 2
Site Reboot 2
Sector Addition 1
Hardware 1
0
40
80
120
160
200
UpTilt
Frequency
SectorSwap
Drive
SiteHealthCheck
Stats
Azimuth
SiteDown
DownTilt
Preamble
SectorReboot
CheckCPEProvisioning
Other
PowerIncrease
ReplaceFaultyCPE
SiteReboot
SectorAddition
Hardware

24. P a g e | 25
2. Implementation status
Out of total 451 recommendations, 202 recommendations are implemented (45%). The
recommendations are verified and implemented by relevant CustomerA departments. The
rest, 249 recommendations are being evaluated or under implementation. Once implemented
in totality these are bound to bring more improvement in the network performance. Figure 4-
2 shows implementation status per type
Figure 4-1: Implementation status per type
0
20
40
60
80
100
120
140
160
180
Implemented Underimplementation

25. P a g e | 26
3. Improvement Status
Once implemented, the effect of recommendation is carefully analyzed by conducting a pre-
post benchmarking. So far 38% of implemented recommendations have resulted in network
improvement. 41% of implemented recommendations are under investigation. Figure 4-3
shows status pie chart
Figure 4-2: Improvement Status
Improvement examples
Figure 4-4,& 4-5 show pre- post benchmark of implemented recommendations.
Figure 4-4: Pre-post benchmarking of Sector down identification for site M7651_D
Deteriorated
1%
NoChange
20%
Solved
38%
UnderInvestigati
on
41%
Deteriorated NoChange Solved UnderInvestigation
Pre Post

26. P a g e | 27
Figure -5: Low coverage removal through uptilt of M4232_C through antenna uptilt
Pre Post

27. P a g e | 28
4. Follow up process
Numerous improvement recommendations have been sent to CustomerA from 360Cellutions by
analyzing Network Statistics, Deregistration Codes and Network Alarms through SYS tool and
Drive Test results through FDI tool.
These recommendations are recorded into an automatic database called Tracker. It provides
summary reports with implementation and improvement status. It also helps in monitoring the
progress of the whole project. A conscious effort is made to keep update process simple and
automatic.
Figure 5.1 illustrates the flow chart for the tracking process
The tracker reports are shared bi-weekly with CustomerA teams to track implementation of
change recommendations. Furthermore, a weekly conference call is conducted to discuss
important cases under implementation. This strong follow up and tracking process binds all
three phases; Data collection, Analysis and solution and is one of the key reasons of achieving
good network performance in such a short time span.
Figure 5-1: Follow up and tracking process flow chart

28. P a g e | 29
Agilent JET
5. Extra mile
During the course of the project 360Cellutions team added additional value by providing
solution and analysis which was out of the project scope. The main objective of these value
additions was to facilitate CustomerA team in their network improvement drive. Following are
the different initiatives taken during this project.
1. Data collection tool (JET)
360cellutions has developed a new scanning interface: JET. This allowed scan mode drive
test to be conducted without the need for a dedicated scanner or Agilent E6474A-X dongle.
Table 6-1 shows advantages of JET over Agilent. Figure 6-1 shows a comparative snapshot of
JET data collection tool with Agilent.
Figure 6-3: Agilent Vs JET
Feature
Agilent JET
Green Packet
Compatibility
Not compatible with Green Packet,
only with Motorola CPE (beceem),
which is now discontinued by
CustomerA
Fully compatible and tested
with Green Packet
Better Sampling
Rate
One sample about every 9 seconds One sample every 6 seconds,
Comparison shown on a map.
BSID
representation
BSID is not correctly exported for
scanned mode
BSID correctly exported for
scanned mode, makes drive
analysis much more precise
Map Trail Map trail is not visible, only current
location is visible
Map trail as well as current
location is visible
64-bit OS
compatibility
Cannot be used on Windows 64-bit
machines
Can be used on 64-bit as well
as 32-bit OS
Exporting Exporting of Agilent log files is
required to csv format which is used
as FDI input (post-processing tool)
No need for exporting, the log
files can be directly input into
FDI
Figure 6-1: Snap shot of Agilent and JET Data collection

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2. Special Feature testing
Preamble comprises introductory bits of DL Data Map in Wimax standard. It tells the data
about ciphering(permutation) schemes.
360Cellutions initiated series of tests in CustomerA’s network to determine efficient use of
Preamble codes. Such efficient utilization and strategic planning of preamble codes can
render greater percentage of network resources free as compared to the current utilization of
resources, by removing interference in network considerably.
360Cellutions suggested a three phased trial. The Trial included following objective
•Phase 1: Effect of Segment ID on interference
•Phase 2: Effect of Preamble on interference
•Phase 3: Effect of same Segment ID and same Preamble on interference
•Phase 4: Effect of PSUC1/3 on interference improvement
A detailed testing methodology was shared and agreed with CustomerA team. The result of
this trial concluded that PUSC 1/3 cannot be implemented in the CustomerA network due to
the older version of software release. The report can be found on the accompanying DVD.
3. Missing Cells Identification
While analyzing reports in SYS it was observed that there are a lot cells missing from the AP
stats. If there were less than four sectors in the raw stats the entire AP (site) was ignored
since there was no way of finding out the sector IDs. 360Cellutions devised a change in the
CustomerA script that extracted raw data from EMS. Now each Sector ID is included in the
raw stats and hence no sector is ignored when loading raw stats into the SYS server. About
20% of the overall AP sectors had missing stats which were recovered using the solution
given by 360Cellutions.

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6. Conclusion
The optimization service provided by 360Cellutions has shown how important it is to
continually monitor and analyze network performance to keep a wireless network in a
healthy condition. There is room for further improvement. Some important projects have
been planned for the future like Spectrum Strategy Optimization. It will also be worth
considering an expansion of this service to include other cities.