IOT-Intelligent Optimization Tool

7/21/2019 IOT-Intelligent Optimization Tool

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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.


Port said, Egypt.

Email:[email protected] Voice: 012218902153-Amr Ahmed El Orbany.


Port said, Egypt.


4-Ahmed Abd El Razek Ahmed.


Port said, Egypt.


5-Essraa Taha Ali.


Port said, Egypt.Email: [email protected] Voice: 01098687576

6-Hala Mohamed Abd El Wahab.


Port said, Egypt .


7-Mai Ahmed Abd El Noor.


Port said, Egypt.

Email: [email protected] Voice: 01206723743

8-Samar Hamdy Abd El aziz.


Port said, Egypt.


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]


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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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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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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.

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IOT-Intelligent Optimization Tool