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Authors:1-Mohamed Essam zaki. (Corresponding author)
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt. `
Email:[email protected] Voice: 01063620405
2-Ahmed Hassan El Zayet.
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt.
Email:[email protected] Voice: 012218902153-Amr Ahmed El Orbany.
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt.
Email:[email protected] Voice: 01113410270
4-Ahmed Abd El Razek Ahmed.
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt.
Email:[email protected] Voice: 01115615393
5-Essraa Taha Ali.
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt.Email: [email protected] Voice: 01098687576
6-Hala Mohamed Abd El Wahab.
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt .
Email:[email protected] Voice: 01114203301
7-Mai Ahmed Abd El Noor.
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt.
Email: [email protected] Voice: 01206723743
8-Samar Hamdy Abd El aziz.
Electronics & Communications department. Port said faculty of engineering
Port said, Egypt.
Email:[email protected] Voice: 01222449442
Area of Application: RF Mobile Communication field.
IOT
Intelligent Optimization Tool
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]7/21/2019 IOT-Intelligent Optimization Tool
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Project identification number: 140
AbstractIOT "intelligent optimization tool" is a mobile
communication software tool which optimizes the
physical configuration of sites, improves the main KPI s'
parameters of the network and determines the number
of needed resources in network in order to increase the
utilization of the network resources, solve the existing
and potential problems and achieve the balance among
coverage, capacity and quality in network through
optimization reports which are based on traffic statistics
analysis, drive test analysis and mathematical equations
to identify the probable solutions for existing problemsand visualize main problems in input files to help the
optimizer to take the correct decision.
INTRODUCTION
Cell planning and optimization is one of the most
complicated tasks as many aspects must be taken into
account and the optimization effect on other which
are not optimized as they are Overlapping significantly
so many aspects must be taken into considerations :
(traffic distribution, existing infrastructure, system
capacity, service quality and frequency bandwidth).
-Network planners task to manually place BSs and
their parameters is based on his personal experience
and some predictions.
-Manual process has to go through a number of
iterations and always not guarantee the optimum
solution.
Astraffic distribution is dynamic, so the automatic
techniques for planning and optimization of the
network are necessary.
-Other tools depend on prediction equations and some
propagation models and so it creates some decisions
by means of prediction, contrary to our case which
depend on real files measured from the field.
So the automatic techniques for planning and
optimization of the network are necessary, Hence the
importance to use our IOT "Intelligent Optimization
Tool" which is carried out in order to improve the
network performance with the existing resources, by
improving the service quality and resources.
Usage of the network with consideration of the
balance among coverage, capacity and quality through
intelligent
Algorithms to give accurate decisions not depend on
prediction such as before, hence the name
"intelligent".
IOT depends on intelligent algorithms which result to
accurate decisionsbecause we depend, Statistics
reports (KPIS), site database (DB), Log files, Dump
files.
IOT increases the utilization of the network resources,increases number of users with a good quality, solves
the existing and potential problems on the network and
identify the probable solutions for future network
planning through the following points:
Create better network plans that offer
improved coverage, capacity and quality.
Automatically plan large network clusters and
improve the productivity of the radio planning
department.
IOT produces optimization reports where theysuggest decisions which will have great
impact on network coverage, capacity and
quality .
Our solution designed to improve the network
performance through Fine tuning the results
coming from any part of tool.
IOT consists of three main modules:
2G&3G AUTOMATIC CELL PLANNINGMODULE (ACP).
2G EXPANSION MODULE.
2G & 3G SELF OPTIMIZATION MODULE(SOM).
In general, the following steps are followed during the
Radio Network Optimization:
Data Collection and verification.
IOT decisions are very accurate because it
depends on Traffic statistics analysis and drive
test analysis such as (Interference matrix,
Statistics reports (KPIS), Log files, Dump
files, site database)which are extracted fromthe real environment where sites existed.
Data analysis.
Intelligent OptimizationTool
(July 2012)
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Project identification number: 140
Here it is the time for data processing and
analysis to detect the existing problem in
network and determining its locations to
guarantee give the right decisions start to
optimize it in the optimum manner.
Parameter and hardware adjustment.
Here it is the stage of obtaining the suggestedproper decisions whether it result from ACP
or SOM to guarantee solving the existing
problems.
IOT results confirmation and reporting.
IOT produces optimization reports which
include the suggested solutions for network
problems, then visualizes results on maps
comparing the network before and after the
IOT resulted solutions and its impact on
network to ensure that the results will becorrect and Accurate.
In figure.1 we show a simple flow chart for the general
process of IOT
If we talk about our motivations for doing this project,
first we aim to help RF tuning teams to analyze the
radio situation, detect radio network problems in one
or more BTS and finally devise a way to optimize the
network and adopt corrective actions to finallyimprove network performance. we also should state
the most important two motivations from our point of
view; the first one is according to ourselves we will
have many benefits from working in this field such as
(We will have a great experience of the cellular
networks such as (GSM, UMTS, HSDPA), we will
have the ability to analyze the network problems and
detects them, we will have the ability to suggest the
proper decision in each case we will face in future and
finally we will have a great experience in treating with
network optimization problems and generally great
experience in mobile communication field by
comparing to any fresh graduated engineer), hence we
can start our first step in our career life, the second
motivation is according to companies IOT can
introduce many benefits for communication
companies such as: (Reduction of capital expenditures
(CAPEX), Reduction of operational expenditures
(OPEX), Get more revenue , etc..).
High Level Architecture of the Systems
IOT intelligent optimization tool is a mobile
communication software tool; it consists of three
modules as shown in figure 2:
Figure 1.General Process of IOT
2G & 3G AUTOMATIC CELL PLANNING
MODULE: (ACP) The Automatic Cell Planning
module optimizes the physical configuration of sites
(antennas' tilt ,azimuth and height) to achieve the
targeted combined goal of coverage, quality and
capacity, it also can check the hardware problem in RF,it consist of three algorithms:
Hardware problems algorithm: it discoversif there is Cross sector, Cross Feeder or
Fault DTRU and optimize a solution.
Poor Coverage Area algorithm: it discoversif there is poor coverage area or bad level
in another and optimizes a solution.
Interference Algorithm: it discovers if thereis interference in the uplink or in the down
link and optimizes a solution.
1-2G EXPANSION MODULE: it will tell methe number of needed resourcesin network
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Project identification number: 140
in the future. It may help me to check the
availability to add frequency in a network.
2-2G & 3G SELF OPTIMIZATION
MODULE: (SOM) is an intelligent solution
to improve the main KPI s' parameters of the
network. It can do most ofall the RF
Optimizer tasks & help him to take the rightdecisions in others which cant optimize
automatically.
2G Self Optimization Module ,it improvesthe main KPI's of the 2G network by many
intelligent algorithms such:
SDCCH Blocking, SDCCHblocking problem means that
users will face problems in the
following actions:call setup,location update, IMSI
attach/detach, Sending SMS in
idle mode [1].
SDCCH Drop,It is the failure ofsetup a call connection due to
SDCCH channel drop, when a
connection is dropped at call setup
it will affect the accessibility KPIs
[2].
TCH Blocking,It is a failure ofsetup a call connection due to
TCH congestion (high traffic).
Call Drop, It means that theestablished call is abruptly
terminated due toHardware
problems, Bad coverage, Missing
Neighbors or Incomplete BA lists,
Interference (bad quality), Wrong
parameters settings.
RACH Failure, RACH is aprocess when specific mobile is
sending Random Access burst to a
serving cell (cell which specific
mobile is camping on),RACH
failure means no response to MS
from the network side.
Handover Failure, It is sudden a
failure when the user make a call
and move from existing cell to
another and this failure due to Bad
frequency plan and this will cause"up link interference", Wrong
definition and missing neighbors,
Wrong parameter setting.,
Hardware problem, Bad quality
down link.
3G Self Optimization Module, it improvesthe main KPI's of the 3G network by many
intelligent algorithms such:
RRC setup Failure, Radio
resource Control (RRC) protocolis being used to configure and
control the radio resource
between the Node B and UE. This
failure may be due toHardware
problems, Transmission
problems, Poor coverage
problem, Power congestion,
Traffic congestion [3].
RAB Assignment Failure, Thisprocedure is triggered from CN
and is used to modify the list ofRadio Access Bearers established
over Iu interface for the given
UE. This failure may be due to
Hardware problems.,
Transmission problems, Poor
coverage problem, Power
congestion, Traffic congestion.
Congestion (Codes, Iub,downlink power and
interference),The WCDMAsystem is a self-interfering
system. As the load of the system
increases, the interference rises.
A relatively high interference can
affect the coverage and QOS of
established services. Therefore,
the capacity, coverage, and QOS
of the WCDMA system are
mutually affected.
Congestion control aims to
maximize the system capacity
while ensuring coverage and QOS
[4].
Call Drop, It means that the
established call is abruptly
terminated and this due to
Equipment Problem, Radio Link
Fault due to Coverage, Radio
Link Fault due to Interference,
Handover Problem, missing
neighbors Congestion problem,
IUB limitation [5].
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HSDPA Throughput,Get morethroughput (useful data rate) per
cell and higher bit rate per user.
HS/EUL Mobility, If EUL issupported in the network, EUL
mobility works in the same way
as HSDPA mobility and istriggered by the same cases,
Mobility might also trigger a
reconfiguration from HS-DSCH
to DCH in the cases where a
serving HS-DSCH cell change
cannot be done, or if bad
coverage is detected .This
problem is due to Hardware
Problem, E-DCH/HS-DSCH cell
change problem, UL Interference
[6].
Hard Handover,Inter-RATHandover prevents dropped calls
and thus allow for service
continuation on dedicated
channels for circuit-switched
services when the UE is moving
out from WCDMA RAN
coverage to an area where only
GSM network coverage exists,
Inter-Frequency Handover
prevents dropped calls and thusallow for service continuation on
dedicated channels when the UE
is moving between 2 cells and
this failure due to Hardware
Problem, IRAT delayed HHO
Problem.
Soft Handover mobility. In SoftHandover, the UE connection
consists of at least two radio links
established with cells belonging
to different RBSs, In Softerhandover, the UE connection
consists of at least two radio links
established with cells belonging
to the same RBS and this problem
due toHardware Problem, Pilot
Pollution Problem, Delayed HO
Problem, Ping Pong Problem [7].
4-Visualizing input files:
Our tool before optimized the solution, it provide anoption to visualize the Drive test file (log file) for
some algorithms to help the user to take the optimum
decision as shown in the figure.3.
Required Resources:
Our tool required data from the field such as:
STATS File, it includes the network statisticsof each cell such :
2G STATS File: it includes statistics and
counters about 2G cell such SDCCHBlocking(%) , SDCCH Drop(%),CALL DROP
due to Radio(%),CALL DROP due to
Handover(%), TCH Blocking Rate(%),
Handover Failure Rate(%), Handover Success
Rate(%), RACH Failure Rate(%) and other
counters of the Call Drop Reason s and
SDCCH Drop Reasons, etc.
3G STATS File:it includes statistics andcounters about Call Drop Rate(%),Call Setup
Success Rate(%),RRC setup success
rate(%),RRC Failure due to code
congestion(%),RRC Failure due to Channel
Element congestion(%),RAB setup success
Rate(%), RAB Failure due to code
congestion(%),RAB Failure due to Channel
Element congestion(%),RAB Failure due to
POWER CONGESTION(%),Soft Handover
Success rate(%), Inter frequency Hard
Handover Success Rate(%), IRAT Hard
Handover Success Rate(%), HSDPA Cell
throughput, etc.
HO_Count STATS, it includes Handover
Count between each cell and its neighbors.
Derive test file (log file),it includes the drivetest measurement at each point of his track to
each cell such:
2G Log file: it includes Rxlevel,RxQual at each point, Neighbors
BCCH, Neighbors BSIC Neighbors
Rxlevel, Hopping Frequencies and
Rxlevel of each freq, etc.
3G Log file: it includes CIPCH
EC/NO, CPICH RSCP at each point,
Active set
cells RSCP , Active set cells EC/NO,
Monitoring cells RSCP, Monitoring
cells EC/NO, The scrambling code of
each cell, etc.
Traffic Study file, it includes the traffic on cell
in 6 months.
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ERLANG.B.TABLE file, it includes thenumber of tch channels on cell, blocking
probability(%).
Neighbors file, it includes the Neighbors of
each cell.
DATA BASE file (DB), it includes the site datawhich planned such Longitude, Latitude,
Azimuth, Tilt, Effective isotropic Radiated
Power, Locationarea code, Mobile country
code , Mobile network code, etc.
DUMP file, it includes the soft parameters ofeach cell such:
2G DUMP file: it includes the 2G cellsoft parameters such cell reselection
hysteresis, cell reselection offset,
number of SDCCH channels, Power
control parameters, Handover
parameters, etc.
3G DUMP file: it includes the 3G cellsoft parameters such Radio link
Supervision timers, Reporting range
triggered of each action, timers of
each triggering, Handover parameters,
HSDPA parameters, Power control
parameters, etc.
Assuring the Quality of the System
Our tool after optimized the solution ,to ensure that its
decision is correct, it simulate the decision that is
depend on the real data (input files) in to 2D map
footprint and make prediction at by using
SPM(Standard Propagation Model) model to ensure
that its decision is correct and facilitates improving the
prediction reliability.
So it optimizes the coverage of some area and then the
quality will improve and make confirming of itsdecision before implementation.
Figure.2 General Architecture of IOT
Figure.3 Map visualizing main Problems
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practical deployment:
Operators (Mobinil, Vodafone, Etisalat,
Mobily, Zain,etc).
Vendors (Alcatel-lucent, Ericsson, Huawei,
etc.)
Subcontractors (Alcan, Mobiserve, Actel, etc).
Governmental Authorities like NTRA (National
Telecommunication Regulatory Authority) can
be using our tool to improve the network
performance.
CONCLUSION
Our tool can introduce many benefits for these
companies
Such as:
Reduction capital expenditures (CAPEX).
as 17% of wireless operator`s spent most
of money on engineering, installation
services and building new sites.
Reduction operational expenditures(OPEX).as 24% of typical wireless
operator`s spent a lot of money in network
operation, maintenance, training, support,
power, transmission.
Get more revenueour solution maximizes
the service of quality of existing network.
Our tool also can help in improvingOUTSOURCING industry in Egypt.
It solves the existing and potentialproblems on the network and identifies the
probable solutions for future network
planning through.
Create better network plans that offerimproved coverage, capacity and quality.
IOT produces optimization reports wherethey suggest decisions which will have
great impact on network coverage,capacity and quality .
Our solution designed to improve thenetwork performance by Fine tuning the
results coming from any part of tool.
Automatically plan large network clusters
and improve the productivity of the radio
planning department.
IOT depend on intelligent algorithms forexist accurate decisions not depend on
prediction such other tools.
REFERENCES
[1]Javier Romero, Juan Nalaro, Timo Halonen, GSM.GPR .and.EDGE. Performance .Evolution, John.Wiley.and.Sons, 2003.
[2]Subhash Panikar, Root Cause Analysis for Key PerformanceIndicators (KPI) for GSM Networks, Ericsson, 2006.
[3]Brian Dowell & Stevan Filipovic, Volume IIEricsson UMTSRF Key Parameters, Ericsson, 2003.
[4]Rashidi Elmi Zulkefli, WCDMA RNC W10 KPI Description,Ericsson, 2010.
[5]Wang Wei, UTRAN KPI Analysis Guide, Huawei TechnologiesCo, 2005.
[6] Huawei, WCDMA Handover Problem Analysis, HuaweiTechnologies Co, 2005.
[7]Ericsson, Handover WCDMA RAN, Ericsson AB ,2009.