IntroductionIntroduction

Why should simulation be performed in WCDMA radio network planning?

Simulation Is One of Important Steps for CDMA Radio

Network Planning Simulation Is One of Important Steps for CDMA Radio

Network Planning

Simulation is oriented to simulate the running situation of networks under the

current network configuration so as to facilitate decision-making adjustment.

Adopt the planning software to perform simulation based on various types of

BTS coverage area, the number of BTSs within the coverage area, and the

configuration of each BTS. All these are obtained from traffic coverage

analysis. AtollAtoll网络规划软件网络规划软件

Introduction to Atoll Software Introduction to Atoll Software

Be a professional radio network design tool, supporting

GSM/TDMA, GPRS-EDGE, cdmaOne,W-CDMA/UMTS and CDMA

2000/1x RTT/EVDO. It is specially designed for 3G.

Realize mobility of planning design, supporting both single system

configuration and Enterprise server-based network configuration.

The single system configuration does not require connecting

external database and users still can share engineering data.

Feature modern software structure as well as open and extendable

platform

Simulation step by step -UNet(Atoll)Simulation step by step -UNet(Atoll)

Coverage by transmitter

Traffic model

Simulation

Coverage prediction

Are Parameters ready? (site, transmitter, cell…)

Parameters modification? (site, transmitter, cell…)

Result Result OK?OK?

NN

OverOverYY

Table of ContentsTable of Contents

Chapter 1 Importing a Digital MapChapter 1 Importing a Digital Map

Chapter 2 Data Importing

Chapter 3 Atoll Propagation Model

Chapter 4 Analog Prediction

Chapter 5 Traffic Model

Chapter 6 Monte carlo Simulation

Composition of a Digital MapComposition of a Digital Map

A digital map basically consists of the following three components,

stored under three directories respectively.

\Heights

Digital elevation model (DEM): describe basic landforms of this area and

directly participate in radio propagation model calculation

\Clutter

Digital clutter model (DOM): clutter classification data describes clutter

coverage on the ground, such as forest, lake, open area, industrial area,

urban area, high-storey building area. It is used during calculating radio

propagation path loss.

\Vector

Linear vector model (LDM): linear clutter vector data describes plane

distribution and space relationship of linear clutters, including speedway,

street and river.

Selecting coordinate system

Selecting coordinate system

• Primary coordinate system: It is a coordinate system of

geographical database

• Display coordinate system: it is a coordinate system for

display and data-input. All the geographical coordinates are

displayed and input according to this system. If the

projection coordinate system and the display coordinate

system do not match with each other, U-Net will adjust

them.

U-Net works with the following two coordinate systems at the same time:

Table of ContentsTable of Contents

Chapter 1 Importing a Digital MapChapter 1 Importing a Digital Map

Chapter 2 Data Importing

Chapter 3 Atoll Propagation Model

Chapter 4 Analog Prediction

Chapter 5 Traffic Model

Chapter 6 Monte carlo Simulation

Antenna Data and Lobe PatternAntenna Data and Lobe Pattern

Input antenna type, manufacturer a

nd antenna gain in [General].

Import the corresponding attenuatio

n table at each angle of the antenna

in [Horizontal pattern ] and [Vertical

pattern].

Input Beamwidth, FMax, FMin or ot

her user-defined parameters in [Oth

er properties ].

Right click “Antennas－ >Propertie

s” in the “Browse-Data” window to o

pen antenna attributes box.

Data ImportingData Importing

Sites information:

refer to BTS equipment type and channel element data Include the following p

arameters: BTS name, longitude and latitude, height above sea level,

Transmitter TMA, feeder and BTS equipment:

CELL information:

Microsoft Excel ¹¤×÷±í

Table of ContentsTable of Contents

Chapter 1 Importing a Digital MapChapter 1 Importing a Digital Map

Chapter 2 Data Importing

Chapter 3 Atoll Propagation Model

Chapter 4 Analog Prediction

Chapter 5 Traffic Model

Chapter 6 Monte carlo Simulation

Introduction to Propagation ModelsIntroduction to Propagation Models

Typical models are from repeated CW tests.

Table of ContentsTable of Contents

Chapter 1 Importing a Digital MapChapter 1 Importing a Digital Map

Chapter 2 Data Importing

Chapter 3 Atoll Propagation Model

Chapter 4 Analog Prediction

Chapter 5 Traffic Model

Chapter 6 Monte carlo Simulation

Coverage PredictionCoverage Prediction

There are ten analog predictions in all, but only the first three can be performed at the current stage because simulation results are unavailable.

A “Coverage bytransmitter” analog prediction is the precondition for simulation.

Coverage PredictionCoverage Prediction

Setting the following parameters:

Signal level threshold value: defaulted as -110dBm and the maximum

value has no upper limit.

All and Best signal level: usually select Best signal level so as to be

convenient to observe the coverage of the best cell.

Signal level margin of the best cell: defaulted as 0

Reliability: 50% is usually set.

Carrier wave: it is usually set to “All carrier waves” for coverage area

computation.

Coverage PredictionCoverage Prediction

Drawing a computation area

Select “Draw” from “Computation zone” in the “Tools” menu in the Atoll

software. And then draw a polygon with the mouse on the zone to be

researched. The computation zone is within the red line.

Shadowing margins

Compute shadowing margins in each type of landform by inputting

the standard variance of each clutter and improving Reliability Level.

Reliability level is 50% Calculate or Calculate all by default.

Table of ContentsTable of Contents

Chapter 1 Importing a Digital MapChapter 1 Importing a Digital Map

Chapter 2 Data Importing

Chapter 3 Atoll Propagation Model

Chapter 4 Analog Prediction

Chapter 5 Traffic Model

Chapter 6 Monte carlo Simulation

Traffic ModelingTraffic Modeling

Traffic data involved in traffic modeling includes service

type, terminals, mobility type, user profile, environment

and traffic map.

Creating a Traffic MapCreating a Traffic Map

Based on Environments (raster): refer to the raster map based on traffic model

Based on User profiles (vector): refer to the vector map based on user profile

Based on Transmitters and Services (throughput): refer to throughput map based on

sector and service type

Based on Transmitters and Services (#users): refer to users map based on sector and

service type

Table of ContentsTable of Contents

Chapter 1 Importing a Digital MapChapter 1 Importing a Digital Map

Chapter 2 Data Importing

Chapter 3 Atoll Propagation Model

Chapter 4 Analog Prediction

Chapter 5 Traffic Model

Chapter 6 Monte carlo Simulation

Monte Carlo SimulationMonte Carlo Simulation

The process of Monte-Carlo simulation is as follows:

Perform Monte-Carlo simulation based on traffic map. Atoll randomly

distribute user location and user profile on the traffic map based on the

number of users and density.

Perform uplink/downlink power simulation based on results from step 1.

Static SimulationStatic Simulation

1. Generate a certain quantity of network instantaneous state—“Snapshot”

Here, some terminals are distributed based on a certain rule (such as

random even distribution) at each “Snapshot”.

2. Acquire connection capability between terminals and networks by

incremental operation.

Here, it is required to consider the possibility of multiple connection

failure (uplink/downlink traffic channel maximum transmit power,

unavailable channels, low Ec/Io and uplink/downlink interference).

3. Measure and analyze results of multiple “Snapshots” to have a overall

understanding of network performance.

Monte Carlo simulation is one type of static simulation.

100%100% 100%100%20%20% 60%60%

0%0% 75%75% 40%40%60%60%

100%100% 100%100%20%20% 60%60%

0%0% 75%75% 40%40%60%60%

Monte Carlo Simulation－ Coverage ProbabilityMonte Carlo Simulation－ Coverage Probability

The following takes coverage probability for an example to further

understand how Monte Carlo simulation is performed.

Simulation ReportSimulation Report

Analysis Report on Simulation ResultsAnalysis Report on Simulation Results

Statistics In the Request is total users accessed into the network, uplink/downlink total

volume required by the network, and details classification of each type of

service.

In the Result is refused users and relevant causes, users successfully

accessed, actual volume of the network, and details classification of each

type of service.

Sites

Include BTS rated maximum channel elements, FCH and SCH channel

elements actually used for uplinks and downlinks, channel elements of

uplink/downlink overhead channels for soft handoff, speech/data volume of

uplink/downlink FCH and SCH channels.

Analysis Report on Simulation ResultsAnalysis Report on Simulation Results

The following initial conditions must be satisfied: Setting global parameters of the transmitter Setting original parameters of this simulationSetting parameters related to landform, such as the orthogonal factor and standard variance of each type of landform

Propagation Model TuningPropagation Model Tuning

Propagation Model TuningPropagation Model Tuning

Propagation Model Tuning FlowPropagation Model Tuning Flow

YES

NO

NO

YES

Change Model Parameter

Perform Appropriate Filtering

CW Data

SPM Model

Document Change

SPM CELIBRATION

Analysis Results

Error Satisfactorily

Low?

Goto Next Parameter

Is Filtering Necessary

Propagation Model TuningPropagation Model Tuning

Establishing a model

Establish a standard macrocell model to be tuned.

Select the effective antenna height.

Select a calculation method of diffraction loss.

Importing data

Import CW test data file into the project.

Propagation Model TuningPropagation Model Tuning

Map correction GPS locating in CW test usually adopts WGS84 and UTM

projection. However, digital maps in China do not use such

projections and reference plane. Correct digital maps if CW test

data does not correspond to them.

Correction method:

Correct four parameters on rectangular coordinates in a

digital map to realize the optimal match with the test data.

Propagation Model TuningPropagation Model Tuning

Setting Filtering Distance filtering:

Filter the data of which r is less than 150m or r is greater

than 3000m.

Signal strength filtering:

Filter the data of which Signal is greater than -40dBm or

Signal is less than -121dB.

Clutter filtering

Filter the Clutter in which sampling points are less than 300.

Propagation Model TuningPropagation Model Tuning

Parameter tuning

L=K1 + K2log(d) + K3log(Heff) + K4×Diffraction

+ K5log(d)×log(HTxeff) + K6(HRxeff)

+ Kclutterf(clutter)

Tune such parameters as log(d), log(Heff), Diff,

log(d)log(Heff), Hmeff and Klutter to finally tune SPM

propagation model.

Propagation Model TuningPropagation Model Tuning

Propagation Model TuningPropagation Model Tuning

calculated values for the variable

ERROR (measurement – prediction)

Regression line

Propagation Model TuningPropagation Model Tuning

Propagation Model TuningPropagation Model Tuning

Correction of propagation model parameters in a city

Parameter

K

Reference value

K1 23.2

K2 44.90

K3 5.83

K4 0.5

K5 -6.55

K6 0

Propagation Model TuningPropagation Model Tuning

Analysis of correction results Analyze correctness of the acquired model after correction.

Evaluate the correctness of the model with Std Dev, which refer

to the binding degree of the acquired model and actual test

environment.

Make Std Dev less than 8 as much as possible in actual model t

uning, which indicates that the tuned model and actual test envir

onment are well bound.

Th

ank yo

u!