University of Aalborg

RATE Section

Long Master Thesis

Empirical Modeling of Femtocell PathLoss in a Femto-to-Macro

Indoor-to-Outdoor Interference Scenario

Authors:

Lucas Alados Linares

Javier Gallardo Sánchez

Supervisors:

Troels B. Sørensen

Andrea F. Cattoni

Zhen Liu

May 31, 2011

Title:

Empirical Modeling of Femtocell Path Loss

in a Femto-to-Macro Indoor-to-Outdoor In-

terference Scenario

Project Period:

Fall Semester 2010 and Spring Semester 2011

Project Group:

10gr1206

Participants:

Lucas Alados Linares

Javier Gallardo Sánchez

Supervisors:

Troels B. Sørensen

Andrea F. Cattoni

Zhen Liu

External censor:

Mikael B. Knudsen

Copies:

6

Date of Completion:

31.05.11

Department of Electronic Systems

Radio Access Technology Section

Fredrik Bajers Vej, 7

9220 Aalborg (Denmark)

www.es.aau.dk

Abstract:

Indoor Broadband Wireless (IBW) systems based on

femtocells present a scalable and cost efficient solution to

overcome the unrelenting increase in the demand of indoor

wireless bandwith. To warrant the coexistence of Femtocells

networks with the former cellular deployment, the interference

impact between systems must be carefully regarded.

To assess this impact from femtocell Base Station (BS)

indoors to macrocell user (outdoors), an indoor-to-outdoor

path loss model is required. This specific model has not been

deeply studied yet. In the present thesis a measurement

campaign in a University Campus (UC) environment has

been performed and an empirical indoor-to-outdoor model has

been created. The new model has been compared in the

UC environment with previous studies obtaining better

estimations with the new model. The results of the

application of the new model in the UC environment point

out the importance of power control management for

femtocells networks. New measurement campaigns are required

to check the new model in different environments.

i

ii

Preface

This report has been written by Lucas Alados Linares and Javier Gallardo Sánchez,

members of group 10gr1206 and guest students in Mobile Communication Master in

Aalborg University.

It has been written in LATEX and consists of seven chapters and six appendices. A

CD is attached as support material including additional data about the measurement

campaign performed.

MATLAB c© has been used to give support to the different calculations and simula-tions performed. AirMagnet c© and NetStumbler c© have been used for data extractionand Microsoft Excel c© for some steps in data processing.

Lliterature references follow IEEE recommendations. Texts, figures, formulas and ta-

bles are referenced using number in brackets which indicates the position on the reference

list:

• Text [Reference Number]• Figure (number): Figure Description [Reference Number]• Table (number): Table Description [Reference Number]• [Reference Number]: Formula [units]

Javier Gallardo Sánchez Lucas Alados Linares

Aalborg University, 31st May, 2011 Aalborg University, 31st May, 2011

iii

iv

Acknowledgements

The authors would like to thank specially the supervisors Troels B. Sørensen, Andrea F.

Cattoni and Zhen Liu for their continuous support and interest in our work. Their help-

ful comments and guidance made us not losing the right track while still let us learning

from our mistakes. We would like to acknowledge also to the other members of RATE

section, technical staff of AAU and Nokia Siemens Networks workers who gave support

at any step.

Special acknowledgements to Pablo Ameigeiras who was the real starter of this

project by proposing us the chance of coming to Aalborg and giving us assistance in

the whole application process. We would like to make this statement extensive to all the

teachers in ETSIIT of University of Granada and classmates who gave us their best in

both technical and personal sides.

To permanent and visiting colleagues in A6-127 Room (Carlos, Igni, Fran, Luisfe,

Marta, Sara, Mario, Pablo, Mus...), thanks for bringing inspiration in our tough daily

work and for making hardcore research such an enjoyable activity. You made Aalborg

home during these months.

We would like to finish with some individual comments from the authors.

From Javier:

To family and friends, because there is no worthy success without anyone being glad for

you. Thanks for bringing me here.

From Lucas:

v

To family and friends, because of your continuous support and inspiration.

To my parents, Inma and Lucas, because this have been nothing but the fruit of your

efforts.

To Paloma, because you have walked with me all over this years, offering encouraging

words, specially when the going was tough.

Thank you all, because without you, I wouldn’t have reached up to here.

vi

”I have not failed. I’ve just found 10,000 ways that won’t work.”

Thomas A. Edison

vii

viii

Contents

1 Introduction 1

1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.1.1 Interference scenarios . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2 Project’s aim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 State of the art 9

2.1 WINNER II indoor-to-outdoor path loss model . . . . . . . . . . . . . . . 9

2.1.1 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.1.2 Scenarios assumptions . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.1.3 Conclusions: WINNER assumptions about outdoor-to-indoor and

indoor-to-outdoor path loss reciprocity . . . . . . . . . . . . . . . . 15

2.2 COST231 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.2.1 Building penetration loss at LOS conditions . . . . . . . . . . . . . 17

2.2.2 Comparison between WINNER II and COST231 . . . . . . . . . . 19

2.3 ITU-R P.1238 and ITU-R P.1411 . . . . . . . . . . . . . . . . . . . . . . . 20

2.3.1 ITU-R P.1238 (indoor propagation) . . . . . . . . . . . . . . . . . 21

2.3.2 ITU-R P.1411 (short-range outdoor propagation) . . . . . . . . . . 21

2.4 Other useful literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

2.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

3 Model description 25

3.1 Propagation effects to be included in the model . . . . . . . . . . . . . . . 25

3.2 Model equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

ix

CONTENTS

4 Measurement campaign 33

4.1 General description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

4.2 Pre-measuring studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.2.1 Measuring device calibration . . . . . . . . . . . . . . . . . . . . . 38

4.2.2 Trial measurement campaign . . . . . . . . . . . . . . . . . . . . . 47

4.3 Results: heat maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

4.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

5 Model results 57

5.1 Data processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

5.2 Model Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

5.2.1 Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

5.2.2 Coefficients values . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

5.2.3 Multi-tier model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

5.3 Model verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

5.3.1 Residuals statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

5.3.2 Residuals heat maps . . . . . . . . . . . . . . . . . . . . . . . . . . 73

5.3.3 Leave-one-out . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

5.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

6 Models comparison and system application 83

6.1 Models Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

6.2 System application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

6.2.1 Emitted power simulation . . . . . . . . . . . . . . . . . . . . . . . 89

6.2.2 Outage probability vs distance simulations . . . . . . . . . . . . . 91

6.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

7 Conclusions 95

Bibliography 99

A Other path loss models 103

B Devices description 107

C Measurement campaign planning 115

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CONTENTS

D Measurement campaign execution and results 149

E Data processing software 157

F Model results complementary material 159

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xii

List of Tables

2.1 Propagation scenarios specified in WINNER of interest [5] . . . . . . . . . 10

2.2 WINNER path-loss models of interest [5] . . . . . . . . . . . . . . . . . . 12

2.3 Assumptions of scenarios B4 and A2 in WINNER II and in studies about

their reprocity ([10], [11]) . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.4 Definition of cell types of interest in COST 231 [6] . . . . . . . . . . . . . 16

2.5 Recommended parameters values for building penetration loss at LOS in

COST231 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.1 Model parameters, and the modeled effects . . . . . . . . . . . . . . . . . 26

3.2 Used functions of model parameters . . . . . . . . . . . . . . . . . . . . . 29

4.1 Frequencies of IEEE 802.11 Channels . . . . . . . . . . . . . . . . . . . . . 43

4.2 Statistics of frequency dependence . . . . . . . . . . . . . . . . . . . . . . 44

4.3 Statistics of angular dependence measurements . . . . . . . . . . . . . . . 46

4.4 Averaged received power at different parts of the day . . . . . . . . . . . . 50

4.5 Average of the STDs of the received power in every point at different

parts of the day . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

5.1 Averaging techniques results comparison . . . . . . . . . . . . . . . . . . . 64

5.2 Model coefficients value . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

5.3 Model coefficients comparison . . . . . . . . . . . . . . . . . . . . . . . . . 66

5.4 Range of application of the model . . . . . . . . . . . . . . . . . . . . . . 67

5.5 Tiers comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

5.6 Model coefficients value for the different tiers . . . . . . . . . . . . . . . . 70

5.7 Study of residuals using leave-one-out technique . . . . . . . . . . . . . . . 80

xiii

LIST OF TABLES

6.1 Figures of merit comparison . . . . . . . . . . . . . . . . . . . . . . . . . . 86

6.2 Simulation data for the model . . . . . . . . . . . . . . . . . . . . . . . . . 90

6.3 Threshold distances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

xiv

List of Figures

1.1 Typical femtocell network deployment [4] . . . . . . . . . . . . . . . . . . 2

1.2 Interference Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Project structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1 A2 Scenario (WINNER II) [5] . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2 A2 environment (WINNER II) [5] . . . . . . . . . . . . . . . . . . . . . . 14

2.3 A1 scenario (WINNER II) [5] . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.4 Perpendicular distances [6] . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.5 Layout of regular street grids (WINNER II) [5] . . . . . . . . . . . . . . . 16

2.6 Building penetration loss at LOS conditions (COST231) [6] . . . . . . . . 18

3.1 Model parameters: dtotal, w, ϑ and We [6] . . . . . . . . . . . . . . . . . . 26

3.2 Model parameters: ϕ and nfloor . . . . . . . . . . . . . . . . . . . . . . . . 26

3.3 Trigonometric functions comparison for elevation angle function . . . . . . 30

4.1 General overview of the measurement campaign . . . . . . . . . . . . . . . 34

4.2 Outdoor spots positioning . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

4.3 Calibration setup in anechoic chamber . . . . . . . . . . . . . . . . . . . . 40

4.4 Frequency dependence analysis . . . . . . . . . . . . . . . . . . . . . . . . 44

4.5 Angular dependence lid opened - closed (AirMagnet) . . . . . . . . . . . . 46

4.6 NIC orientation in outdoor spots . . . . . . . . . . . . . . . . . . . . . . . 47

4.7 Averaged received power at different parts of the 1st day . . . . . . . . . . 49

4.8 STD of instantaneous received power at different parts of the 1st day . . . 50

4.9 Heat map for power of AP1 (Ground floor, no internal walls) . . . . . . . 52

4.10 Heat map for power of AP2 (Ground floor, 1 internal wall) . . . . . . . . 53

4.11 Heat map for power of AP3 (Ground floor, 2 internal walls) . . . . . . . . 54

xv

LIST OF FIGURES

4.12 Heat map for power of AP5 (1st floor, no internal walls) . . . . . . . . . . 55

5.1 Model results extraction steps . . . . . . . . . . . . . . . . . . . . . . . . . 58

5.2 Example of measured signal without processing . . . . . . . . . . . . . . . 58

5.3 Zeros-removed signal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

5.4 Zeros and outliers removed signal . . . . . . . . . . . . . . . . . . . . . . . 60

5.5 Spatial averaging technique at one single point . . . . . . . . . . . . . . . 64

5.6 Model parameters: dtotal, w, ϑ, We, dindoor and ddirect−path [6] . . . . . . 68

5.7 Residuals distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

5.8 Predicted vs Measured Path Loss . . . . . . . . . . . . . . . . . . . . . . . 72

5.9 CDF of residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

5.10 Residuals normalized histogram and Gaussian comparison . . . . . . . . . 74

5.11 Comparison of residuals distribution with normal distribution . . . . . . . 74

5.12 Residual heat map for AP1 (Ground floor, no internal wall) . . . . . . . . 76

5.13 Residual heat map for AP2 (Ground floor, 1 internal wall) . . . . . . . . . 77

5.14 Residual heat map for AP3 (Ground floor, 2 internal walls) . . . . . . . . 77

5.15 Residual heat map for AP5 (1st floor, no internal walls) . . . . . . . . . . 78

5.16 Leave one out regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

6.1 Visual Fit Comparison of WINNER II, COST231 and New Models . . . . 86

6.2 Comparison of CDFs of WINNER II, COST231 and New Model . . . . . 87

6.3 Comparison of Histograms of WINNER II, COST231 and New Model . . 88

6.4 UMTS Macro user received power from femtocell BS transmitting 0,10

and 20 dBm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

6.5 Study of outage probability in received power vs distance figure for a set

of transmission powers at the femtocell BS . . . . . . . . . . . . . . . . . . 93

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To our parents

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Chapter 1

Introduction

The unrelenting increase in bandwidth demand in wireless networks needs for a scalable

and cost efficient solution. Moreover, studies on wireless usage show that more than 50

percent of all voice calls [3] and more than 70 percent of data traffic originate indoors,

where the coverage is worse than outdoors, due to the propagation loss through the

building and walls.

Through reduced cell sizes and transmit distance is how the highest increase in wire-

less capacity is achieved. This gain comes out from higher area spectral efficiency [2].

In addition, allocating cells inside buildings will enhance the QoS for indoor users and

reduce outdoor wide-area system occupation.

Femtocells, a.k.a home base stations (BS), are short-range low-cost BS installed by

the final consumer to enhance the wireless coverage indoors. The user-installed device

communicates with the cellular network over a broadband connection such as Digital

Subscriber Line (DSL) (or even radio frequency backhaul) . In figure 1.1, the typical

femtocell network deployment is shown. A key advantage of femtocells is their little

upfront cost to the service provider [1].

Local Indoor Broadband Wireless (IBW) systems based on femtocells have been

pointed out as a good solution to overcome indoor coverage, providing sufficient data

rates for in-builiding end-users [1], [2]. This network deployment will also improve the

macrocell reliability absorbing indoor traffic, allowing the macrocell BS to redirect its

1

CHAPTER 1. INTRODUCTION

Figure 1.1: Typical femtocell network deployment [4]

resources to outdoor users.

1.1 Motivation

Depending on the operator scenario femtocells may use a dedicated carrier (dedicated

IMT-Band for femtocells) or share one with the macrocell network (co-channel with

macrocells). Also, two configurations for femtocells networks are possible: Closed Sub-

scriber Group (CSG) and Open Subscriber Group (OSG). CSG femtocell has a fixed

set of subscribed home users that are licensed to use the femtocell. OSG femtocells, on

the other hand, provide service to macrocell users if they pass nearby [1]. In any case,

interference between systems will arise.

In figure 1.2 the main different interference scenarios are shown. There, two simpli-

fied buildings divided by a street are depicted. One has two apartments, and the other

has one single apartment. Each femtocell User Equipment (UE), which is represented as

a mobile phone, is connected to its home femtocell Base Station (femtocell BS), which

is represented by a little antenna indoors. In the case of the macro UE, which is rep-

resented by the mobile phone outdoors or indoors, is connected with the macrocell BS,

which is represented as the big antenna outdoors. Femtocell UE is called F UE in the

figure, while Macrocell UE is denominated M UE. The same scheme is followed by the

BS (F BS and M BS)The dashed lines represent the interference.

2

1.1. MOTIVATION

Figure 1.2: Interference Scenarios

In order to have a look at the different interference situations, an easy and intuitive

idea would be to estimate the interference knowing the interferer path loss model for

each scenario.

• A, E cases: indoor-to-indoor interference.• B cases: outdoor-to-indoor interference.• C cases: indoor-to-outdoor interference.• D, F cases: indoor-to-outdoor-to-indoor interference.

All these cases will be discussed further in the section 1.1.1.

It is important to notice that the case in which the femto user is outdoors will be a

typical case of outdoor-to-outdoor interference, easy to study with the existings models

(Okumura-Hata, WINNER II [5], COST231 [6]...). Anyway, it is unlikely to happen

because, femto user outdoors should handover to macro BS.

In the situation of dedicated carrier, the interference will be adjacent channel inter-

ference, that is, interference between different nearby channels. The noise rise caused by

3

CHAPTER 1. INTRODUCTION

these interferences could be easily minimized [4].

In case of shared carrier, the in-band interference is severe especially when macro

users are “close enough” to indoor femtocells (typically near macrocells edges).

In the case of OSG the interference signal is managed allowing the user to handover

between cells if the interferer is strong, but in the case of CSG this interference can even

prevent macro users from receiving the desired service from the macrocell networks,

creating a dead zone, an area where the communication between the macro UE and the

macrocell BS is impossible.

1.1.1 Interference scenarios

Indoor-to-indoor interference scenario

Those will be cases of femto-to-femto, femto-to-macro and macro-to-femto interference.

The femto-to-femto interference can be divided in two other cases: interference from

femtocell BS to nearby femtocell UE (A1 in figure 1.2) and interference from femtocell

UE to nearby femtocell BS (A2 in figure 1.2). The femto-to-macro interference is the

case of interference from femtocell BS to nearby macrocell UE (E1 in figure 1.2) and

the macro-to-femto interference is the case of interference from macrocell UE to nearby

femtocell BS (E2 in figure 1.2). It must be commented that the last two are the most

harmful.The reasons are the high transmitted power of the macro UE to reach the macro

BS to overcome indoor-to-outdoor propagation path loss, and the high received power

from the femto BS by the macro UE in comparison to the power received from the macro

BS (outdoors and usually further).

The indoor-to-indoor path loss model is studied in several literature such as [6], [5]

and [7].

Outdoor-to-indoor interference scenario

That will be the case of macro-to-femto interference. It can be divided in two other

cases: interference from macrocell BS to femtocell UE (B1 in figure 1.2) and interference

from macrocell UE to femtocell BS (B2 in figure 1.2). Here, the most important is B2,

4

1.1. MOTIVATION

that could be severe if the macro user is near the macrocell edge, because it will transmit

at high power. B1 is less likely to be harmful due to the fact that the length of this

interferer path is very high and the received signal indoor will be very much lower than

the received from femtocell BS.

The outdoor-to-indoor path loss model is also widely studied in literature such as [6]

and [5].

Indoor-to-outdoor interference scenario

That will be a case of femto-to-macro interference. It can be divided in two cases:

interference from femtocell BS to macrocell UE (C1 in figure 1.2) and interference from

femtocell UE to macrocell BS (C2 in figure 1.2). It must be commented that the two

cases mentioned above have not the same importance. The case C1 is likely to be harmful

near the cell edge, where the received power from the macro node is low. Here, dead

zones size is likely to be larger than in the macrocell center, where the received power

from the macrocell is higher. The case C2 will appear if the femtocell UE were quite

near the macrocell BS, that is unrealistic.

In this case, it can be found out that the indoor-to-outdoor path loss model has not

been deeply studied in literature and the aim of this project will be to fill this gap.

Indoor-to-outdoor-to-indoor interference scenario

Those are cases of femto-to-femto, femto-to-macro and macro-to-femto interference. The

femto-to-femto interference can be divided in two different cases: interference from fem-

tocell BS to nearby femtocell UE (D1 in figure 1.2) and interference from femtocell

UE to nearby femtocell BS (D2 in figure 1.2). The femto-to-macro interference is the

case of interference from femtocell BS to nearby macrocell UE (F1 in figure 1.2) and in

the macro-to-femto interference is the case of interference from macrocell UE to nearby

indoor femtocell BS (F2 in figure 1.2). It must be commented that, as in the indoor-to-

outdoor interference scenario the last two are the most harmful.

The indoor-to-outdoor-to-indoor path loss model has not being deeply studied yet

either but it is supposed to be less harmful than the others because of the isolation

provided by at least two external walls in the interference path.

5

CHAPTER 1. INTRODUCTION

Literature about these topics [4] concludes that adaptative power control is the main

solution for intereference created by femtocells (Indoor-to-indoor, Indoor-to-outdoor,

Indoor-to-outdoor-to-indoor).

1.2 Project’s aim

As can be seen, an indoor-to-outdoor path loss model is needed to estimate the interfer-

ence from femtocells to macrocells.

Since path loss is generally assumed to be reciprocal, an existing outdoor-to-indoor

path loss could be used to model the indoor-to-outdoor path loss as it is done in WINNER

II model (see 2.1.3). But in this case there is a strong objection to this principle: the

environment near the source is different in the indoor-to-outdoor path from the outdoor-

to-indoor path (nearby obstacles, antenna heights, propagation constant...), indeed the

shadowing effect is more severe in the indoor-to-outdoor path than in the outdoor-to-

indoor one. Because of that, the reciprocity assumption cannot be used in principle here.

Nevertheless urban-microcell models (lower antenna heights than macrocells) may be a

good starting point.

The aim of this project is to construct (or complement an existing one) an Empirical

Indoor-to-Outdoor Path Loss Model which is expected to be useful to estimate the real

interference impact from femtocells to macrocells. This path loss model is supposed

to help in the interference avoiding and managing in the prospective femtocell network

deployment. It could bring interesting consequences for power control management for

femtocells: dead zone size, emitted power thresholds...

The new path loss model would be based on empirical data, therefore, a measure-

ment campaign will be carried out for that purpose. The new data obtained in the

measurement campaign model will help to check the validity of the existing models for

this concrete scenario.

To improve its usability, it should be a multitier model (the more data parameters

available about the environment the more complex submodel can be used).

6

1.2. PROJECT’S AIM

Figure 1.3: Project structure

Project structure

In figure 1.3 a brief scheme of the project structure is presented.

The State-of-the-art will be studied on chapter 2, where the various existing path loss

models for indoor-to-outdoor will be discussed and other literature about propagation

will be presented. On chapter 3 a description of the model will be provided, with details

about its parameters. The inspiration sources of it (from chapter 2) and their relation

with the results of the measurement campaign chapter is also included. Chapter 4 will

explain the measurement campaign performed for the data obtaining for the empirical

model, including the campaign planning, its execution and its results. On chapter 5 the

final model is presented, with the data processing executed, the optimization method for

the parameters coefficients obtaining, the final values for the model parameters coeffi-

cients and the model verification. On chapter 6 a comparison with the existing models is

accomplished and conclusions about the interference estimation obtained by simulation

of the new path loss model are presented. Finally on chapter 7 the project’s conclusions

are presented. Appendices contain further descriptions about several aspects along the

project.

7

CHAPTER 1. INTRODUCTION

8

Chapter 2

State of the art

In this chapter the state-of-the-art of indoor-to-outdoor path loss models is exposed.

Additionally, some useful studies for the path loss model development will be discussed.

The Urban-Micro-Cells models for Line Of Sight (LOS) conditions present a good start-

ing point for this study, because they provide the most similar environment to the one

to be studied (lower antenna heights and propagation distances than macrocells).

Along this line, in the following sections WINNER II indoor-to-outdoor path loss

model [5], COST231 building penetration at LOS conditions [6], and other propagation

studies complementary for this project are presented (such as ITU-R P.1238 for indoor

propagation prediction method [7] and ITU-R P.141 for outdoor propagation prediction

method [8]).

2.1 WINNER II indoor-to-outdoor path loss model

In this section the WINNER II indoor-to-outdoor model will be introduced. The rele-

vant recommendation ITU-R-M.2135 (IMT-Advanced) [9] is originated from WINNER

II . IMT-Advanced (International Mobile Telecommunications Advanced), from ITU-R

organization, specifies the requirements for 4G standards.

To start, table 2.1 presents the propagation scenarios specified in WINNER II that

are of interest in this study. A2 indoor-to-outdoor model (see figure 2.1)is the one that

fits to the scenario of the study, but B1 outdoor and B4 outdoor-to-indoor are required

9

CHAPTER 2. STATE OF THE ART

Figure 2.1: A2 Scenario (WINNER II) [5]

Scenario Definition LOS/

NLOS

Mob.

km/h

Frequency

(GHz)

CG Environment

A2 Indoor to outdoor NLOS 0-5 2-6 LA AP inside UT

outside.Outdoor

environnment urban

B1 Hotspot Typical urban mi-

crocell

LOS/

NLOS

0-70 2-6 LA,

MA

B4 Outdoor to in-

door, microcell

NLOS 0-5 2-6 MA -Outdoor typical ur-

ban B1.

-Indoor A1

Table 2.1: Propagation scenarios specified in WINNER of interest [5]

because A2 model is developed from them (see section 2.1.1). To see the B1 typical

urban and A1 indoor environments go through section 2.1.2.

2.1.1 Model

Before showing the WINNER II path loss model, the definition of path loss used in the

presented models at the chapter 2 must be commented, it is defined as the total path

loss between two isotropic antennas. That definition differs from the one used for the

new model (see chapter 3). This fact will be important for the models comparison in

chapter 6.

Path loss models for the various WINNER scenarios are typically of the form in

equation 2.1, where d is the distance between the transmitter and the receiver in [m], fc

10

2.1. WINNER II INDOOR-TO-OUTDOOR PATH LOSS MODEL

is the system frequency in [GHz], the fitting parameter A includes the path loss expo-

nent, parameter B is the constant term, parameter C describes the path loss frequency

dependence, and X is an optional, environment specific term.

[5] : PL = A log10(d[m]) +B + C log10

(fc[GHz]

5.0

)+X [dB] (2.1)

The models can be applied in the frequency range from 2-6 GHz and from different

antenna heights. The interesting path-loss models related to this study are summarized

in table 2.2, which either defines the parameters of equation 2.1 or explicitly provides

a full path loss formula. The distribution of the shadow fading is log-normal, and the

standard deviation for each scenario is given in table 2.2.

PLB1 is the Typical urban microcell path loss in WINNER II (Path Loss in case

B1), dout is the distance between the outdoor terminal and the point on the wall that is

nearest to the indoor terminal, din is the distance from the wall to the indoor terminal,

ϑ is the angle between the outdoor path and the normal of the wall. nFl is the floor

index (starts from the ground floor which has index 1 and increases for the upper cases).

d′BP=4 h′BS h

′MS fc/c where fc is the center frequency in Hz, c = 3.0x10

8 m/s is the

propagation velocity in free space, and h′BS and h′MS are the effective antenna heights at

the BS and the MS respectively. The effective antenna heights are computed as follows:

h′BS = h′BS -1.0 m, h

′MS = h

′MS -1.0 m, where hBS , hMS are the actual antenna heights,

and the effective environment height in urban environments is assumed to be equal to

1.0 m.

While the general equation (2.1) for the WINNER II models is quite simple,a it can

be seen that the equations proposed for the environments B4 and A2 are more sophis-

ticated, including angle dependent penetration loss, and indoor linear attenuation by

distance.

In the indoor-to-outdoor model in WINNER II there is no account for floor height

gain (decrease in path loss due to to the increase in the number of floor were the receptor

is located), since at LOS, or partial LOS conditions (mostly valid for urban micro-cell),

the penetration loss is quite independent of the floor height. That happens because, the

floor gain regards for the increase of probability of LOS conditions due to higher floor.

11

CHAPTER 2. STATE OF THE ART

Shadow Applicability range,

Scenario Path loss [dB] fading antenna height default

STD[dB]values

B1 LOS A = 22.7, B = 41.0, C = 20 σ = 3 10m < d1 < d′BP

PL = PLb + PLtw + PLin, σ = 7 3m < dout + din < 1000m

hMS = 3nFl + 1.5m

B4 NLOS hBS = 10mPLb = PLb1(dout + din)

PLtw = 14 + 15(1− cos(ϑ))2

PLin = 0.5din

3m < dout + din < 1000m

A2 NLOS Same as B4, except antenna heights hBS = 3nFl + 2m,

hMS = 1.5m

Table 2.2: WINNER path-loss models of interest [5]

12

2.1. WINNER II INDOOR-TO-OUTDOOR PATH LOSS MODEL

If the typical situation in urban micro-cell is LOS, the mentioned effect does not occur.

As can be inferred from table 2.2, based on the studies [10], [11] WINNER II states

A2 is reciprocal to B4.. Moreover, B4 path loss model is created based on B1 path loss

model. The B1 option used will be B1 LOS, because in the scenario of study there will

be LOS between the antenna outdoors and the building external wall where the signal is

supposed to go through. Also, for larger distances between the receiver and transmitter

there is another B1 LOS equation available in the model, but for this scenario (short

propagation distances) it will be enough with the one presented.

In [10], [11] comparisons between indoor-to-outdoor and outdoor-to-indoor propaga-

tion characteristics are done respectively. In section 2.1.2 the scenario assumptions in

B4 and A2 and the experiment environment of the study of [10], [11] will be discussed

and in section 2.1.3 the conclusions about the reciprocity study are regarded.

2.1.2 Scenarios assumptions

In table 2.3, assumptions of scenarios B4 and A2 in WINNER II and in studies about

their reprocity ([10], [11]) are presented. There are some ideas that come out from the

study of table 2.3. The studies about reciprocity are done in the band of 5.25 GHz that

is not the only one where the femtocells can be deployed. Moreover, the frequency span

was very little. In addition the outdoor environment of studies [10] and [11] (University

campus) is completely different from the one described in A2 and B4, however indoor

environment is similar. On the other hand, the antenna heights in A2 and [10], [11], fit

to the typical indoor-to-outdoor femtocell-to-macrocell interference scenario.

In figures 2.2 and 2.3 WINNER A1 environment (indoor office) can be seen.

WINNER B1 environment is a urban area where streets are laid out in a Manhattan-

like grid (see figure 2.5). Notice that indoor distance is always defined as the perpen-

dicular distance from the indoor receiver to the illuminated external wall. Then, in an

indoor-to-outdoor or outdoor-to-indoor path the outdoor distance is the distance from

the intersection of the external wall with the perpendicular distance defined indoor to

the BS or UE outdoor (see figure 2.4 from COST231, where the indoor perpendicular

distance is d and S is the outdoor one). This will happen also in all the models that will

be explained later. Remind at this point that ground floor has floor index of 1.

13

CHAPTER 2. STATE OF THE ART

Scenario BS antenna

height

MS antenna

height

Frequency

[GHz]

Environment

A2 (outdoor): 1 - 2 m (indoor): 2 - 2.5m

+ floor height

2 - 6 Indoor:

WINNER A1.

Outdoor:

WINNER B1.

B4 (outdoor): below

roof-top, 5 - 15

m depending on

the surrounding

buildings height.

(indoor): 1 - 2 m

+ floor height

2 - 6 Indoor:

WINNER A1.

Outdoor:

WINNER B1.

[10], [11] (indoor): 2 m +

1st & 4th floor

(outdoor): 1 - 1.5

m

5.2 - 5.3 University

Campus.

Table 2.3: Assumptions of scenarios B4 and A2 in WINNER II and in studies about

their reprocity ([10], [11])

Figure 2.2: A2 environment (WINNER II) [5]

14

2.1. WINNER II INDOOR-TO-OUTDOOR PATH LOSS MODEL

Figure 2.3: A1 scenario (WINNER II) [5]

Figure 2.4: Perpendicular distances [6]

2.1.3 Conclusions: WINNER assumptions about outdoor-to-indoor and indoor-to-

outdoor path loss reciprocity

Reciprocity between scenarios B4 and A2 stated by WINNER II comes out from a study

in the band of 5.25 GHz. It is not decided yet in which range of frequencies femtocells

will work, but a study in another frequency bands (such as IMS band) would throw more

light on the validation of reciprocity principle in this environment.

Moreover, the studies from [10], [11] do not even completely agree:

• [10] conclusions: “The results show that both outdoor-to-indoor and indoor-to-outdoor scenarios behave very similar, so we suggest to merge these two cases”.

15

CHAPTER 2. STATE OF THE ART

Figure 2.5: Layout of regular street grids (WINNER II) [5]

• [11] conclusions: “The results show that the scenarios are not as reciprocal as onemight assume even though the correlation of certain parameters is high”.

In conclusion, it seems that there is not a strong conclusion about the reciprocity

used to create the indoor-to-outdoor model in WINNER II.

2.2 COST231

In COST231 there can not be found specific indoor-to-outdoor path loss models for

femtocells. Nevertheless, there is a general study about building penetration from results

from different types of buildings, miscellaneous distances and angles between the outdoor

antennas and the surfaces of the external walls. The most similar scenarios in COST231

to the one of study, will be Microcells and Picocells, which use the case of LOS of building

penetration study (see section 2.2.1). In table 2.4 the summary of the different cell types

of our interest in COST231 is shown.

Cell type Typical cell radius Typical position of base station antenna

Microcell Up to 1 km Outdoor; mounted below medium roof top level

Picocell /

inhouset

Up to 500 m Indoor or outdoor (mounted below roof-top

level)

Table 2.4: Definition of cell types of interest in COST 231 [6]

In microcells the base station antennas are mounted generally below roof tops. Pic-

ocells are applied to cover mainly indoor or very small outdoor areas. In any case the

16

2.2. COST231

base station antenna of a picocell is mounted inside a building or fairly below roof-top

level in outdoors.

2.2.1 Building penetration loss at LOS conditions

COST231 building penetration study at LOS conditions is the one used in microcel-

lular/picocellular environments, where there can be LOS conditions between the mi-

cro/pico BS to the external wall of the building (microcellular/picocellular environments

will also have NLOS situations, where the “Building penetration at NLOS conditions”

of COST231 must be used, but the LOS situation fits better to the scenario of interest

in this project).

For these LOS conditions, there is no account for floor height gain. The same thing

happened for WINNER II (see section 2.1.1).

In COST231 work for microcell scenario, at short distances there is a considerable

variation in the combined loss due to the penetration and the propagation inside the

building. This comes out from the angle dependent penetration loss also seen in WIN-

NER II. For line of sight conditions with one dominant ray, the power of the reflected

ray at the external wall can be considerable at small grazing angles, giving rise to a large

penetration loss compared to perpendicular penetration.

The building penetration loss approach defined in COST231 is described below. The

parameters in the model are defined in figure 2.6.

Definition of grazing angle θ and distances D,S and d can be seen in figure 2.6. In

the building of figure 2.6 an example of a possible wall layout at one single floor is shown.

The distance d is a path through internal walls and the distance d′ is a path through a

corridor without internal walls.

The total path loss between isotropic antennas is determined with the following

expression:

17

CHAPTER 2. STATE OF THE ART

Figure 2.6: Building penetration loss at LOS conditions (COST231) [6]

[6] : L = 32.4 + 20 log10(f) + 20 log10 (S + d)

+We +WGe

(1− D

S

)2+max(Γ1,Γ2) [dB] (2.2)

Γ1 = Wip [dB] (2.3)

Γ2 = α′(d− 2)

(1− D

S

)2[dB] (2.4)

D and d are the perpendicular distances and S is the physical distance between the

external antenna and the external wall at the actual floor. All distances are in metres,

frequency is in GHz. The angle is determined through the expression sin(θ) = D/S.

The only case when θ = 90 degrees is when the external antenna is located at the same

height as the actual floor height and at perpendicular distance from the external wall,

i.e. when D = S. Hence, θ changes considerably with floor height at short distances D.

We is the loss in dB in the externally illuminated wall at perpendicular penetration θ =

90 degrees. WGe is the additional loss in dB in the external wall when θ = 0 degrees.

Wi is the loss in the internal walls in dB and p is the number of penetrated internal walls

(p = 0, 1, 2...). In the case in which there are no internal walls, as along d′ shown in

figure 2.6, the existing additional loss is determined with α′ in [dB/m]. The suggested

model assumes free space propagation path loss between the external antenna and the

illuminated wall and is not based on an outdoor reference level. The parameter values

recommended in the model can be seen in table 2.5.

18

2.2. COST231

Parameter Value

We 4 - 10 dB, (concrete with normal window

size 7 dB, wood 4 dB)

Wi 4 - 10 dB, (concrete walls 7 dB, wood and

plaster 4 dB)

WGe about 20 dB

α′ about 0.6 dB/m

Table 2.5: Recommended parameters values for building penetration loss at LOS in

COST231

This building penetration model may be used in the indoor-to-outdoor path using the

reciprocity principle as in WINNER II. There are not any conclusions about reciprocity

in COST231.

2.2.2 Comparison between WINNER II and COST231

It can be seen that COST231 has some differences with WINNER II. At first, the propa-

gation constant is higher in WINNER II. COST231 also accounts for internal wall losses.

On the other hand, both of them take into account a linear distance attenuation

indoors and neither of them takes into account the floor gain. In addition, while it

seems that the modeling of the angle dependent penetration loss is different (WINNER

II uses the cosine while COST231 prefers the sine), in fact, is the same treatment, as ϑ

of WINNER II is the complementary angle of ϕ in COST231.

In the case of the recommended values for the parameters coefficients there are also

some differences. While in WINNER IIWe (external wall penetration loss) has a constant

value of 14 dB, in COST231 it has a range of 4 - 10 dB. WGe (the additional loss in dB

in the external wall when θ = 0 degrees) is fixed to 15 dB in WINNER II and to 20 dB

in COST231 (it can be concluded that COST231 gives more importance to this angle

dependence and less to the external wall penetration loss). Finally they have a similar

value for the linear distance propagation constant, but COST231 again considers the

effect stronger than WINNER II (0.6 in COST231 and 0.5 in WINNER II). Propagation

19

CHAPTER 2. STATE OF THE ART

constant in WINNER II (α=22.7) is slightly higher than the one in COST (it considers

free space propagation: α=20).

2.3 ITU-R P.1238 and ITU-R P.1411

In this section two interesting studies about propagation are shown. They are not useful

by themselves for the scenario of interest of this project, but together they can throw a

little more light on this study. A further explanation of both of them can be found in

Appendix A.

ITU-R P.1238 is a recommendation for “Propagation data and predictions methods

for the planning of indoor radiocommunications systems and radio local area networks

in the frequency range 900 MHz to 100 GHz”, while ITU-R P.1411 is a recommendation

for “Propagation data and prediction methods for the planning of short-range outdoor

radiocommunication systems and radio local area networks in the frequency range 300

MHz to 100 GHz”.

Both of them are of interest here, because they model the indoor and outdoor con-

ditions of the scenario of study respectively. Moreover, while they are neither indoor-

to-outdoor nor outdoor-to-indoor models, but indoor and outdoor ones, both of them

made a reference to each other in case of a mixed situation. Along this line, at ITU-R

P.1238 it can be read: “Recommendation ITU-R P.1411 provides guidance on outdoor

short-range propagation over the frequency range of 300 MHz to 100 GHz, and should be

consulted for those situations where both indoor and outdoor conditions exist,...”. Similar

statement but in the opposite way can be seen at ITU-R P.1238 in cases where indoor

propagation also occurs. This statement does not mean that they can be used together

to create either an indoor-to-outdoor or outdoor-to-indoor path loss model, but that one

of them can be used and some considerations about propagation from the other must be

taken into account, to do those kind of predictions (i.e using ITU-R P.1411 for outdoor

propagation adding external wall penetration loss and indoor propagation constant along

indoor propagation). As a consequence of all the explained above, a general inspection

of both of them in the scenarios of interest may be useful for this study.

20

2.3. ITU-R P.1238 AND ITU-R P.1411

2.3.1 ITU-R P.1238 (indoor propagation)

ITU-R P.1238 models for indoor propagation take into account the main differences

between indoor and outdoor radio systems. It states, mainly, that in the indoor case,

the extent of coverage is much affected by the geometry and materials of the building.

Furthermore, the very short range of indoor radio systems means that they are sensitive

to small changes in the inmediate environment of the radio path.

The main indoor-effects are reflection and diffraction in objects, walls, floors..., trans-

mission loss through walls, floor and others, channeling effect in hallways, and motions

of persons and objects. These indoor-effects give rise to non-free space propagation con-

stant, temporal and spatial variation of path loss, multipath effects...

ITU-R P.1238 made some general conclusions, the main ones for this study are pre-

sented on this paragraph. Path with LOS have a distance power loss coefficient of around

20, large open rooms also. Corridors present a distance power loss cofficient of 18 and

propagation around obstacles and walls adds considerably increase on distance power

loss coefficient up to 40. This conclusions are consistent with the previous studied mod-

els (WINNER II and COST231).

A comment must be made to this study. Although several models predict a floor

gain in case of macrocells (height gain), and no floor gain in case of microcells (such as

in COST231), ITU-R P.1238-6 predicts a floor loss. That occurs due to the fact that

the different floors act as isolators of the signals.

2.3.2 ITU-R P.1411 (short-range outdoor propagation)

This recommendation provides guidance on outdoor short-range propagation over the

frequency range 300 MHz to 100 GHz. Information for LOS and NLOS conditions is

given. But LOS conditions models will fit better to the studied scenario.

ITU-R P.1411 states that over paths of length less than 1 km propagation is affected

mainly by buildings and trees.

21

CHAPTER 2. STATE OF THE ART

2.4 Other useful literature

In this section the main conclusions of some useful studies about propagation in similar

environments and scenarios to the one of study are presented.

Outdoor-to-Indoor Propagation Loss Prediction in 800-MHz to 8-GHz Band for an Urban

Area [12]

After a measurement campaign to analyze the building penetration loss on 71 floors in

17 buildings in a urban area using four frequencies in the 800 MHz to 8 GHz band and

microcells and macrocells, the main conclusions obtained are that in the conditions of

the study the penetration distance coefficient is 0.6 dB/m, the floor height gain is 0.6

dB/m (when story height is 3 m), the frequency coefficient is 0 (no frequency dependence

of the penetration loss) and the constant value for penetration loss is 10 dB.

Radio Propagation Into Buildings at 912, 1920 and 5990 MHz Using Microcells [13]

In this study, propagation into buildings experiments with microcells below roof top

level at 912, 1920 and 5990 MHz were conducted. The main conclusions of the study are

that in its conditions higher penetration losses were experienced at higher frequencies.

It stated also that in buildings with lower surroundings constructions and macrocell BS

above roof top there is a floor gain approximately from 1.5 to 2 dB per floor for the first

floors (when there is NLOS from the macrocell to the iluminated wall in the building).

Multi-frequency Path Loss in an Outdoor to Indoor Macrocellular Scenario [14]

This study comes out from multi-frequency path loss measurements in an outdoor-to-

indoor macrocellular scenario. The experiments were carried out in the band of 460-5100

MHz and the BSs were located on the roofs of 29 meters buildings. The propagation

distance was up to 600 m. The main conclusions were the confirmation of the expected

decrease of loss with increasing floor height (floor gain) with a value between 2 and 4

dB/floor, and that, while small frequency dependence of building penetration loss be-

tween 460-1860 MHz is found, in the band 1.8-5.1 GHz, the increase in loss is noteworthy.

22

2.4. OTHER USEFUL LITERATURE

Radio-Wave Propagation for Emerging Wireless Personal-Communication Systems [15]

The paper summarizes some radio-propagation measurements and models for wireless

personal-communication systems. In this part, some of the main ideas are depicted.

Indoor-channel measurements show that large signal variations occurs in different

buildings (path loss exponent variation from 14 to 38). Also, in the same building, a

dynamic range of 30 dB was found for fading inside the building with slow temporal vari-

ations. The effect of height gain is accounted here with a value of 1.9 dB/floor. Different

external wall materials were studied and it was found that metallic walls attenuate more

than brick walls.

When building has a large number of windows, penetration loss is lower. In fact

windowed areas exhibit penetration loss 6 dB lower than non-windowed areas. On the

other hand, shielded windows (that use metallic film to reflect sun light), exhibit higher

penetration loss up to 12 dB.

But the striking conclusion is the one obtained about the frequency dependence of

building penetration loss, justified by the dielectric nature of walls (frequency selective).

It was found out a decrease in penetration loss with frequency. For frequencies of 900

MHz, 1800 MHz and 2300 MHz the building penetration loss was 14.2 dB, 13.4 dB and

12.8 dB.

Prediction of Outdoor and Outdoor-to-Indoor Coverage in Urban Areas at 1.8 GHz [16]

This study is based on a huge amount of measurements from the Global System for

Mobile Communications 1800 network of E-Plus from small macrocells. It states that

the accuracy of the models can be improved by considering vegetation effects and also

multipath propagation up to a distance of 500 m. Moreover it claims again for the use

of height gain model.

Rec. ITU-R P.833: Attenuation in vegetation [17]

This recommendation studies the attenuation in vegetation for a range of frequencies

from 30 MHz to 60 GHz. The specific attenuation in a woodland (the worst case and

23

CHAPTER 2. STATE OF THE ART

not likely to happen in urban area) between 2 GHz and 5 GHz is between 0.7 and 1

dB/m.

2.5 Conclusions

From the observed models it can be seen that there are no existing specific femtocell

indoor-to-outdoor path loss model. Even though WINNER II has an indoor-to-outdoor

path loss model, there are no specific studies on the band of 2.4 GHz and there are

suspicions that reciprocity does not hold in the scenario of study.

The need to check the indoor-to-outdoor WINNER II path loss model out or create

a new specific indoor-to-outdoor path loss model for femtocells, is quite well justified.

This model should keep in mind the studies presented in this chapter. Some of the main

ideas will be presented on the next paragraphs.

In the femtocell scenario, a floor gain is supposed to appear because of the rise of

LOS probability when the transmitter is higher.

Vegetation and multipath effects are not going to be taken into account, because

they are usually used only in complex ray-tracing tools. The effect of vegetation in the

frequency of interest and the environment of study will be negligible.

There are contradictory opinions about the frequency dependence of building pene-

tration loss in the band of interest in this study.

Indoor wall penetration loss and penetration angle loss seem to be good parameters

for the femtocell model (better indoor path description) and perpendicular indoor path

(see section 2.1.2) is the most extended approach. External wall penetration loss (used

in COST231 but not in WINNER II) is a parameter to include to have an accurate

model. COST231 seems to be a good inspiration for creating a new model.

On the next chapter, the new model description will be presented and justified.

24

Chapter 3

Model description

In this chapter a description of the created model is given. All the parameters present

in the created model will be explained and justified based on previous studies (see chap-

ter 2) and on the observation of the measurement campaign results (see chapter 4).

Therefore, the idea is to first propose a model equation based on previous studies and

then check the model structure against the measurements performed in the measurement

campaign (see chapter 4).

Besides, some ideas for the creation of a multi-tier model will be depicted. The

weights for the different parameters and the different tiers will be presented on chapter

5.

3.1 Propagation effects to be included in the model

Along this section the propagation effects that are included in the model are detailed.

They are inspired mainly in COST231 and WINNER II (see chapter 2) but also some

ideas are taken from the other studied models. In table 3.1 the model parameters and

the modeled effects can be seen. Besides, on figures 3.1 and 3.2 a graphical description

of the parameters can be observed.

The space propagation effect is modeled by including the total distance factor (dtotal),

using perpendicular indoor distances. This parameter is used widely in path loss mod-

els, with the possibility to choose between free space propagation constant or not. In

25

CHAPTER 3. MODEL DESCRIPTION

Figure 3.1: Model parameters: dtotal, w, ϑ and We [6]

Figure 3.2: Model parameters: ϕ and nfloor

Parameter Name Modeled effect

dtotal Total distance Friis Free-space propagation

w Number of indoor walls Power loss at the indoor walls along

the path

θ Penetration angle Penetration angle dependent propa-

gation loss

ϕ Elevation angle Elevation angle dependent propaga-

tion loss (for nfloor > 1)

nfloor Number of floor Height gain

We Outdoor wall penetration loss Penetration loss at the outdoor wall

Table 3.1: Model parameters, and the modeled effects

26

3.1. PROPAGATION EFFECTS TO BE INCLUDED IN THE MODEL

this case, following COST231, the Friis free space propagation constant (α=20) is chosen.

The number of walls through the perpendicular path indoor is modeled by including

w. This parameter is also used in COST231.

Angle dependent penetration loss seen in COST231 and WINNER II is modeled by

including θ.

The floor gain effect is modeled by including nfloor, that is the number of the floor

where the transmitter is located. The definition for this parameter is the same than the

one used in WINNER II for nFl. It has value of 1 for the ground floor and increases for

higher levels. It was selected as a parameter based on the observations of the results of

the measurement campaign (chapter 4). Despite it is neither used in WINNER II nor

COST231, it is a way to take into account the easier LOS conditions when the trans-

mitter is located above ground level (nfloor > 1). The problem of this parameter is that

the measurement campaign was performed using only ground and first floors, therefore,

to improve the accuracy of results, a deeper investigation into this parameter for higher

number of floors is needed.

The elevation angle effect is an attempt to take into account the matter that, when

the transmitter is located above ground level and the receiver is very near to the external

wall, it is found a strong NLOS case, that increase the path loss. It was selected as a pa-

rameter based on the observations of the results of the measurement campaign (chapter

4). It is defined by ϕ = tan−1(htransmitter/doutdoor), where htransmitter is the difference

of height between transmitter and receiver. This parameter has the same problem than

the previous one (number of floor). It has not been checked for a floor higher than the

first. This parameter is neither explicitly included in COST231 nor WINNER II, but in

COST231 is contained in θ parameter.

The external wall penetration loss effect is modeled by including We, that is the

propagation loss due to the external wall. It is used in COST231 and WINNER II. In

the case of WINNER II is a constant value (14 dB), while in COST231 it can take a

range of values (4-10 dB). In the presented model, it will be external wall specific, that

27

CHAPTER 3. MODEL DESCRIPTION

is, it will require the external wall loss penetration loss as an input to the model.

3.2 Model equation

Along this section, the model equation is presented (see equation 3.3) and the function

used for the parameters of the model are shown and justified. In table 3.2 the parameters

and their functions are presented. The values of the coefficients (b, c, d, e, f ) will be

estimated based on the optimization of the data obtained in the measurement campaign

detailed on chapter 4.

It must be take into account the path loss model definition used in the created model

(see equation 3.2). Path loss is usually defined as the difference between the received

power at the receiver and the transmitted power in the transmitter. However, in this

case, to get rid of the coupling factor (CF ), antenna coupling factor (AF ) and receiver

and transmitter antenna gains (Gr and Gt), it was defined as the difference between

the received power at the receiver at the desired position and the received power at the

receiver at 1 m from the transmitter. That selection has been made, because when sub-

tracting the 1 meter reference measurement to the measurement at the desired position,

the received power will have 4 constant terms (coupling factors and antennas gain) that

will be suppressed with this subtraction. The aim of this path loss model formulation

is to have an accurate result without having accurate information about this hardware

parameters.

The antenna coupling factor (AF ) is defined by equation 3.1 as a function of the

wavelength κ. This antenna coupling factor comes out from Friis free space propagation

equation (see [18]).

[18] : AF = −20 log10( κ

4π

)[dB] (3.1)

If there is the need of using the model without information about the 1 meter ref-

erence measurement, it will be necessary to include in the model equation the antenna

gains and the coupling factors. Because of that, these parameters have to be added, to

make a comparison between this new model and the previous presented on chapter 2. In

28

3.2. MODEL EQUATION

Parameter Parameter function

dtotal (Total distance) 20 log10(dtotal)

w (Number of indoor walls) w

θ (Penetration angle) (1− sin(θ))2

ϕ (Elevation angle) (1− cos(ϕ))2 (for nfloor > 0)nfloor (Number of floor where the

transmitter is)

nfloor

We (External wall loss) We

Table 3.2: Used functions of model parameters

equation 3.4 the model using definition of path loss seen in chapter 2, that is, received

power at the receiver minus transmitted power at the transmitter is shown. Basically, if

CF , AF , Gr, Gt are supposed to be constant, the only different between equations 3.3

and 3.4 is the constant term f which will be higher for equation 3.4.

PL [dB] = Pr(desired point)− Pr(dtotal = 1m) [dB] (3.2)

PL [dB] = 20 log10(dtotal) + b · w + c · (1− sin(θ))2 +

d · (1− cos(ϕ))2 + e · (nfloor − 1) +We + f [dB] (3.3)

PL [dB] = 20 log10(dtotal) + b · w + c · (1− sin(θ))2 +

d · (1− cos(ϕ))2 + e · (nfloor − 1) +We + f + CF +AF +Gr +Gt [dB] (3.4)

The function used for the total distance parameter is just the Friis free space prop-

agation function also used in COST231. w, nfloor and We are used raw.

The function used for the elevation angle (ϕ) was chosen from a set of possible func-

tions. The idea is that there is strong NLOS near the walls for (nfloor > 1) and the

effect is high very close to the wall but it changes almost abruptly when it is not. A

29

CHAPTER 3. MODEL DESCRIPTION

Figure 3.3: Trigonometric functions comparison for elevation angle function

threshold distance definition for modeling this effect is not a good choice because of the

difficulty of choosing it, therefore a set of trigonometrical equations were tested.

The function used for the penetration angle θ was tested in a similar way to ϕ. Fi-

nally the selected function was the same used in COST231 and WINNER II.

The function should work in the following way: when ϕ is little (receiver far from

the wall) it should not do anything, otherwise (big angles due to short distance to the

external wall) it should introduce a fast increase in path loss. Therefore, a function

whose slope is very little at the small angles and increase fast with big angles is needed.

On figure 3.3 the different candidate functions are shown. The one finally used was

(1−cos(ϕ))2 because was the one that fits best to the desired behavior explained before.

Based on the measurement campaign explained on chapter 4, a multi-tier model will

be created. The multi-tier model consists in a set of sub-model equations, of increasingly

number of parameters and accuracy. The decision about the sub-model to use is taken

based on the availability of the different parameters. The purpose of this multi-tier

approach is to reduce the complexity of the model, when less accuracy is needed, while

maintaining its resiliency. The model different equations are presented in chapter 5.

30

3.3. CONCLUSIONS

3.3 Conclusions

In this chapter, the model equation has been presented. The parameters functions used

on the model have been justified and the relation of the parameters with the propagation

effects to be modeled has been explained some of them based directly on the measure-

ment campaign performed in chapter 4. In chapter 4 the measurement campaign is

detailed, while in chapter 5 the final model with the proper values for the coefficients is

shown.

Besides, the multi-tier approach was presented and it will be shown in detail in

chapter 5.

31

CHAPTER 3. MODEL DESCRIPTION

32

Chapter 4

Measurement campaign

The development of an empirical model requires of a big set of data covering as much

variability as possible for the studied phenomenon. Because of the nature of the mea-

surements for the model (indoor-to-outdoor wireless power measurements), a wide de-

ployment and an extensive data collection stage are needed in the frame of this thesis.

The coordination of all the devices present in the measuring process such as APs,

laptops and measuring software requires a carefully regarded planning. Also, the selec-

tion of the locations of the APs and the outdoor spots is a sensible part because bad

decisions can lead to polarized and not diverse enough results.

Along this chapter, a summary of the measurement campaign planning, execution,

data obtaining and results will be discussed. For further details, the reader is referred

to the measurement report included in Appendices C and D.

4.1 General description

To get the measurements, a reproduction of the femtocell indoor-to-outdoor propagation

scenario must be deployed. This scenario must include emitting antennas inside build-

ings and any power measuring device outdoors. Moreover, every device must be located

in a well-known location so that the characteristics of the path between emitters and

receiver can be perfectly studied and described.

33

CHAPTER 4. MEASUREMENT CAMPAIGN

Figure 4.1: General overview of the measurement campaign

A general overview of the measurement campaign deployment can be observed in

figure 4.1. There are several APs which will be permanently emitting beacons and a

control laptop indoors (represented in light blue color). A measuring laptop can be

found outdoors. This last device will be moved from one outdoor spot (black circles) to

another to cover the full area of the courtyard and get measurements of received power

in many different points for every AP.

The measuring outdoor area is a courtyard among the buildings of the Electronic

Systems Department of Aalborg University (AAU) and Nokia Siemens Networks (NSN)

premises in NOVI building. The outdoor spots correspond to the corners of a grid made

of 4-by-4 meters squares. Due to the dimensions of this area, a total of 136 points can

be fitted. In figure 4.1 a smaller number of points was plotted for simplification.

Although the exact values of the parameters describing the propagation path from

the AP to the measuring laptop must be known, the accuracy in the location of these

34

4.1. GENERAL DESCRIPTION

Figure 4.2: Outdoor spots positioning

outdoor spots is not an important point. The exact localization of the measurement

points respect to the buildings will be extracted by using the distances from these points

to reference points in the walls of the buildings around. These reference measurements

can be achieved with the help of a laser gauge. The main idea of this can be observed

in figure 4.2. For extended information about this process, see appendix C.

Owing to the incipient deployment of femtocells networks and to the use of licensed

spectrum for this technology, carrying out a measurement campaign with specific fem-

tocell devices would be difficult. Therefore, the indoor network is deployed with IEEE

802.11 WLAN technologies, a.k.a. WiFi. The WLAN consists of a total of 15 Access

Points (APs): 10 of them self-deployed and located in the ground and 1st floors of the

Electronic Systems Department buildings and 5 more already deployed belonging to the

NSN wireless network deployment.

The accuracy of the values extracted for the coefficients of the different parameters

35

CHAPTER 4. MEASUREMENT CAMPAIGN

of the model equation is directly related to the amount of significant data that the final

optimization algorithm will be provided with. The achievement of this significance in

the data has to be deeply regarded while deciding the location of the APs.

Seeing that, it is desirable a careful choice of the characteristics of the AP placements.

These characteristics can be divided in two groups: joint and individual characteristics.

As a whole, the group of APs should include many different combinations of val-

ues for the parameters of the model such as number of walls, indoor distance or floor

number. This variety will enrich the subsequent model because more situations will be

included in the extraction of the empirical data and because the increase of the range

of the values of the parameters will improve the prediction of the general behavior for

these parameters.

On the individual side, the more valid points an AP provides, the better the location

is. If the location of the AP is far away from the inner walls of the building adjacent

to the courtyard, the outdoor area where the wireless signal has power enough to be

sensed with the available hardware will decrease. It will involve a smaller number of

power measurements coming from this AP, therefore less information to the model.

The requirements of these two matters lead to conflicting situations when deciding

the location of the devices, e.g., increasing the range of number of walls between the AP

and the measurement point to higher values is ”jointly” good, though if the number is

over certain threshold, no data will be collected during the measuring. As a consequence

of these conditions, a trade-off must be made. Maps with the exact location of these

devices are also included in the measurement report in appendix C.

The device used to register the power level received in every point outdoors is a lap-

top with an external IEEE 802.11 Network Interface Card (further referred to as NIC)

equipped with specific software. The laptop is located over a pedestal of 0.7 meters

height to reproduce the regular height of the receiving device of the scenario. To facili-

tate the control and configuration of the measuring device, it is remotely controlled from

the indoor laptop by using a desktop sharing software operating via Internet.

36

4.1. GENERAL DESCRIPTION

The procedure for the data obtaining is changing the location of the laptop to all

of the different positions in the grid. In every point, a measurement of the registered

received power from every AP is saved and also the values of the distances from the

points in the grid to the reference points in the walls of the buildings.

The data needed can be divided in 3 different groups regarding the way they are ob-

tained: 1-meter reference power measurements, received outdoor power measurements

and the values for the raw parameters for the propagation path between every AP and

every outdoor spot.

The 1-meter power reference measurements are performed for every AP by mea-

suring with the laptop at a distance of 1 meter from the device. Due to the non-

omnidirectionality characteristic of the sensing device (see section 4.2), 8 different power

measurements have to be performed rotating the laptop around the vertical axis in steps

of 45o each .

The received power outdoors is obtained directly with the laptop using the measur-

ing software. The software will produce a text file for every measurement that will be

processed afterwards to obtain the value in every point.

The values for the parameters of the equation for every measurement such as number

of walls or distance can be obtained locating the outdoor spots in scaled digitalized maps

of the buildings of AAU and NSN. For the location of the points, the distances to the

reference points in the walls of the surrounding buildings are used. After this step, the

values of the parameters can be obtained using Computer Aided Design (CAD) software.

For examples of the layout, see appendix D.

By executing this measurement campaign minding the observations included in the

next section (4.2), an appropriate set of data was obtained.

37

CHAPTER 4. MEASUREMENT CAMPAIGN

4.2 Pre-measuring studies

In order to improve the quality of the data obtained, two operations were performed

whose results brought some implications in the measuring procedure. Those operations

were a precise calibration of the measuring device (laptop equipped with external WiFi

NIC) and a trial measurement campaign.

4.2.1 Measuring device calibration

The calibration was carried out to get a full knowledge of the characteristics of the de-

vice that would be used for the data obtaining and consequently take into account the

possible effects that the maladjustments in the sensing process could introduce.

The calibration of some different features of the communication process between an

AP and the NIC was made in two stages. A former study of this hardware in the same

scenario than the one that will be described for the second session was available in pre-

vious studies [19].

The points analyzed in the previous calibration session were:

• Frequency dependence of emitted power with the slight frequency variations be-tween the different WLAN channels

• Angle of NIC orientation dependence

• Power adjusting measurement

• Power burst measurement

After examining the results obtained in this earlier experiment and the materials

which compose the laptop, the thinking about the importance of the influence of the lid

shadowing arose. It led to the repetition of the calibration session with the lid closed

in the frame of this thesis to compare both results (lid opened / closed), specially the

characteristics which could be more affected by this effect of lid shadowing: frequency

and angle dependences. Besides, these ones are the most important in connection with

the measurement campaign planning and execution since they could introduce critical

changes.

38

4.2. PRE-MEASURING STUDIES

The new calibration session was carried out in the same anechoic chamber in AAU

facilities than the one before. The calibration setup for the experiment was the same

than in the original planning with the only difference of the position of the lid. A sketch

of the scenario is shown in figure 4.3.

39

CHAPTER 4. MEASUREMENT CAMPAIGN

Fig

ure

4.3:

Cal

ibra

tion

setu

pin

anec

hoi

cch

am

ber

40

4.2. PRE-MEASURING STUDIES

The AP emits its signal that is sent via the horn antenna and sensed in the NIC of

the measuring laptop. The horn antenna introduces some gain and directivity to the

signal emission. The data communication necessary to run the desktop sharing VNC

client-server tool is carried out using the internal WLAN antenna of the measuring lap-

top so it did not interfere in the measurements.

The function of the WLAN antenna included inside the anechoic chamber was just

to add some diversity in the communication and make the data connection feasible, com-

pensating the difficulties that the lack of reflections inside the chamber introduces. The

coupler is used to protect the Spectrum Analyzer (SA) from high power at the input. It

produced a reduction of 10 dBs in the SA input signal power. The variable attenuator

was not used in this second calibration session because the sense of this was measuring

the power adjustment. However, this element was kept in the scenario to make this

configuration as similar as possible to the one before.

There are two available softwares for the register of the measurement values: Air-

Magnet and NetStumbler. In the case of the calibration, the selection of the program

is not very important, since the results that are needed depend on the relative values,

not the absolute ones. Nevertheless, the measurements produced with AirMagnet will

be more precise because this program does not just show the instantaneous received

power value, but produces a file with the received power values along the time. For the

calibration and the measurement campaign, AirMagnet is used. A comparison of the

values for both tools is available in Appendix C.

As an addition, to validate the values obtained in the calibration process, a theoret-

ical calculation of expected received power for the scenario has also been performed. It

is included in the measurement report in appendix C.

As previously mentioned, the most important characteristics in relation to their in-

fluence in the measurement campaign planning and execution are angular and frequency

dependences. The study of them will be analyzed in detail in the following subsections

where the implications of their results will discussed as well.

41

CHAPTER 4. MEASUREMENT CAMPAIGN

For the other two features also included in the former calibration session “Power

bust measurement” and “Power adjusting measurement”, the corresponding measure-

ments were not repeated. In the case of the power burst, it can be stated than the

small variations in the burst emitted by the AP do not have effect in the measurements

performed with the device. For the power adjusting, which measures how the reception

of the signal can vary depending on the absolute value of the emitted power (i.e. if there

is saturation or any other non-linear effect of any of the components in the system),

the result is the same, there are no proofs of a direct influence of this feature in the

final results. For further details and concrete results about these two characteristics, the

reader is referred to the corresponding section in appendix C.

Frequency dependence

Emitting and sensing devices in measurement campaign were supposed to be frequency

independent in 802.11b frequency range. The study of this characteristic was executed

in the calibration session by changing the WLAN channel used in the AP for the trans-

mission. The frequencies for the different WLAN channels are included in table 4.1.

The evaluation was made for 5 non-correlative channels (2, 4, 6, 8 and 10) which would

provide information enough for the purpose of the study.

There was a post-processing data stage to improve the accuracy of this experiment.

In this process, the output values extracted directly from the sensing software were com-

pensated with the difference in the emitted power from the AP which varies slightly with

the channel, i.e., the emitted power is somewhat frequency dependence. The obtaining

of these differences in the emitted power was made with the help of a Vector Signal

Analyzer (VSA). For details about how the data were obtained and the VSA configured,

see appendix C.

After the removal of this effect, it can be stated that the variations of the received

signal with the frequency are due only to the characteristics of the receiving device, such

as variations of NIC antenna gain.

The results obtained after averaging 1 minute measurement extracted with AirMag-

42

4.2. PRE-MEASURING STUDIES

Channel number Center Frequency (GHz)

1 2.412

2 2.417

3 2.422

4 2.427

5 2.432

6 2.437

7 2.442

8 2.447

9 2.452

10 2.457

11 2.462

12 2.467

13 2.472

14 2.484

Table 4.1: Frequencies of IEEE 802.11 Channels

43

CHAPTER 4. MEASUREMENT CAMPAIGN

Statistic Value

Mean -49.5560 dBm

Maximum difference (max - min) 2.3090 dB

Standard deviation 0.8784 dB

Table 4.2: Statistics of frequency dependence

Figure 4.4: Frequency dependence analysis

net and applying the correction factor are plotted in figure 4.4. In table 4.2, the most

important statistics coming out from the data are shown.

Regarding the data, it can be observed that the variation is small, or at least not

big enough to think that this could affect severely to the measurement campaign. The

maximum difference of 2.3 dB is very small when compared with the values of the fading

effects in radiowaves propagation.

This matter brought one advantage that is used in the measurement campaign plan-

ning. Since the device is considered to be frequency independent, APs configured in any

IEEE 802.11b channel can be used. It means that the ones in the self-deployed WLAN

(fully controlled by us) and also the ones in another surrounding networks (like the ones

in the WLAN setup at NSN premises, whose working WiFi channel cannot be changed

but with well-known locations) can be used without using any compensation factor.

44

4.2. PRE-MEASURING STUDIES

Angular dependence

This characteristic is of the utmost importance in the planning of the measurement cam-

paign. The NIC used as signal sensor is plugged in the PCMCIA port of the laptop,

located in one lateral of it. It seems logical to think that the point of main impact of

the wave in the device could change the sensing accuracy, i. e. the NIC can be in the

direct line of sight (LOS) or in the opposite side of the laptop where the own device will

shadow the received signal.

For that reason, this section tries to quantify this effect and find out its influence.

It will determine whether the relative position of the laptop in each measuring location

respecting to the cardinal points should be noticed or not. In case of having any effect,

a suitable way to limit the effect that this not-omnidirectionality could have in the mea-

surements must be regarded.

The experiment performed to get these measurements consisted in setting a fixed

configuration for the AP and afterwards turning the laptop around using the revolving

platform above the pedestal. This platform could be controlled from the control room

with high precision in the angle determination. The main characteristics of this setup

are included in appendix C.

The data was obtained with NetStumbler and AirMagnet. A comparative radiation

pattern of the results for both programs is showed in appendix C.

In figure 4.5 there is a comparative radiation pattern of the situations with the lid

opened and closed and table 4.3 shows some statistics which will help to assess the data.

The suspicions about the effect of the lid shadowing get confirmed with this graph:

the lid makes the directionality of the device more pronounced. In spite of the correction

by closing the lid, it is still noticeable that the radiation pattern of the antenna presents

some directionality with a value high enough not to be neglected when planning the

measurement campaign.

45

CHAPTER 4. MEASUREMENT CAMPAIGN

Figure 4.5: Angular dependence lid opened - closed (AirMagnet)

Measurement AirMagnet - lid closed (dB)

STD of data 2.2454

Mean -49.4312

Max variation 7.7749

Table 4.3: Statistics of angular dependence measurements

The solution adopted for the mitigation of this effect is changing the orientation of

the laptop in the different points of measuring. So, the non-omnidirectionality effect will

be mitigated by spatial averaging, i.e., for every one of the four positions which make up

a “measuring square” the orientation will be turned 90o regarding the previous one. Se-

lecting the measurement points in this way, a whole circle will be covered in every group

of four positions, and the effect will be spatially averaged by a right handling of the data

obtained in this way in the post-processing stage. A map indicating the orientation of

the NIC in every outdoor spot in the courtyard which can help to the understanding of

the process is shown in figure 4.6. The dashed blocks represent buildings.

46

4.2. PRE-MEASURING STUDIES

Figure 4.6: NIC orientation in outdoor spots

4.2.2 Trial measurement campaign

The air interface is very changing and can be affected by many factors such as obstacles

or interferences from other systems using it. Due to the extension of the measurement

campaign, its execution takes very long time. This is why a study about the influence

that the variations in th