Abstract

Nowadays the traffic demand grows fast that requires careful chosen deployment strategy to

increase capacity, but save investments. Another important subject is to save a power consumed

mostly by base station itself and its backhaul network. So, what type of base stations must be

chosen, what spectrum characteristics it has and what backhaul link is connected to it. All this

aspects requires different approaches, as they have different capacity and cover characteristics.

The motivation is to compare the solutions using different base station types and various

backhaul solutions. The question if the spectral efficiency allows to increase the traffic

throughput, it would decrease or increase power consumption and cost.

The modern technologies propose several options, ones of them are macro cellar and femtocell

network. The macro cell has a great ability to cover a big area, while the femtocell has a good

capacity possibilities. Moreover, femtocell partially are paid and installed by end-users that

decrease the installation and electricity cost for operators. However, operator can reuse existed

sites which decrease investment cost of macrocellular network. So, the first milestone is to find

the way how to fairly compare two different types of technologies.

In this thesis the proposed scenario is composed in a very careful way to predict demand types,

base stations possibilities and characteristics as well as the backhaul architecture. Then the more

accurate model to deploy a femtocellular network has been described in detail. The more detailed

cost strategy is introduced for backhaul solutions and described in detail. The power

consumption calculations has been described in more clear way, to show the range of metrics,

what value should it has: negative or positive. Some formulas is remade to reach more correct

results. Another milestone is to bring all parameters to unique format that has been done to

achieve right results. In the microwave backhaul solution, the topology case added and carefully

i

described, because every topology case requires different formulas, in this thesis, the calculation

steps for star and ring topologies presented. Steps how to calculate the base station radius

depends on power characteristics of base station is provided.

Since this thesis introduces improvements in several points, It is good guide to keep in track the

received results and control the calculation process.

ii

Acknowledgments

I would like to thank my supervisor Ashraf and for all help and valuable feedback, as well as

discussions and providing me with ideas and references for this research. I would also like to

thank Jan Markendahl for advising me a choice of a research field, Cicek Cavdar for advices and

being helpful and Sibel Tombaz for presenting a related work in the beginning of research.

Ashraf Awadelakrim Widaa has been a good academic supervisor who provided me with

valuable feedback of the report and presentations.

I am thankful to family for a support and to my closest friends.

iii

iv

Content

1 Introduction 1

1.1 Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.3 Research Questions and problem formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 Network architecture 8

2.1 General description of the mobile network architecture. . . . . . . . . . . . . . . . . . . . . . 8

2.2 Radio Access Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.3 Backhaul solutions and topologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.3.1 Fiber optic solution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.3.2 Microwave solution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.3.3 Topologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.3.4 Core network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3 Deployment methodology 16

3.1 General description. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3.1.1 Coverage demand and assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

3.1.2 Capacity demand and assumptions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

3.2 Cost and Power Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.2.1 Cost model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213.2.1.1 The number of cells to deploy the network . . . . . . . . . . . . . . . . . 21

3.2.2 Power model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

3.2.2.1 The power model of one base station . . . . . . . . . . . . . . . . . . . . . 24

3.2.2.2 The power model of backhaul part of network . . . . . . . . . . . . . . 25

3.3.2.2.1 Fiber-based backhaul solution . . . . . . . . . . . . . . . . . . . . . . 25

v

3.3.2.2.2 Microwave-based backhaul . . . . . . . . . . . . . . . . . . . . . . . . . . 26

4 Results and discussion 30

4.1 The number of femtocell and macro cell base stations. . . . . . . . . . . . . . . . . . . . . . . 30

4.2 Power consumption results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.2.1 Result presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.2.2 Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

4.3 Cost results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

4.3.1 Result presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

4.3.2 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

5 Conclusion and future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

vi

vii

List of Figures and Tables

Fig. 2.1. Brief architecture of network architecture. . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 8Fig. 2.2. The difference between thr macro cell and femtocell . . . . . . . . . . . . . . . . . . . . . 9Fig. 2.3. The nowadays choice of modern backhaul technologies . . . . . . . . . . . . . . . . . . 10Fig. 2.4. Brief architecture of network with backhaul . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Fig. 2.5. AGGP-aggregation point supplies several base stations via a wireless link. . . . 12Fig. 2.6. Backhaul topologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . .. . . . 13Fig. 3.1. Deployment area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Fig. 3.2. Wall attenuation (WA) influence on a radius (R1>R2) of one base station . . . . 22Fig. 3.3. a) horizontal view, the floor area is 1 square km ; b) vertical planning, 5 floors 23Fig. 3.4. Tree topology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Fig. 4.1. The number of macro base stations to meet the capacity demand. . . . . . . . . . . . 31Fig. 4.2. The number of femto base stations to meet the capacity demand. . . . . . . . . . . . 31Fig. 4.3. Detailed view of power consumption of macro base station . . . . . . . . . . . . . . . 33Fig. 4.4. Macro cellular network. Comparison of macro cellular network power

consumption using microwave or fiber solutions.. . . .. . . .. . . .. . . .. . . .. . . .. . . 33Fig. 4.5. Power consumption of one base station. Femto cell.. . . .. . . .. . . .. . . .. . . .. . . . 34Fig. 4.6. Femtocellular network power consumption. Comparison of microwave and

fiber solutions. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. .. 35Fig. 4.7. Cost of macrocellular network with a fiber backhaul 1st year. Comparison of

the green deployment(all sites are new) versus using existing macrocell sites.... 37Fig. 4.8. Net Present value of macrocellular network with fiber backhaul. Comparison

of the green deployment(all sites are new) versus using existing macrocell sites.. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . 38

Fig. 4.9. Cost of femtocellular network with a fiber backhaul, 1st year. . . .. . . .. . . .. . . . 38Fig. 4.10. NPV of femtocellular network with a fiber backhaul . . .. . . .. . . .. . . .. . . .. . . . 39Fig. 4.11. NPV of macrocellular network with a microwave backhaul. Comparison of the

green deployment(all sites are new) versus using existing macrocell sites... 39Fig. 4.12. NPV of femtocellular network with a microwave backhaul. . . .. . . .. . . .. . . .. . 40

viii

ix

List of Acronyms and Abbreviations

BS Base station

BW Bandwidth

CAPEX The investment cost

dB Decibels, the unit to measure the power consumption

EARTH Energy Aware Radio & network tecHnologies

Gbps Gbits per second

NPV Net present value

O&M Operation and Maintenance

OPEX Running cost

TRX Transceiver

QoS Quality of service

WA Wall attenuation

x

xi

CHAPTER 1

Introduction

This chapter gives a brief introduction to the description of research questions along with a

definition of the research gap considered in this thesis. The project’s scope, related works,

research questions and methodology are described as well.

1.1 Background

The tremendous increase of data traffic usage of mobile and wireless broadband motivate

companies to look for different solutions and new technology. Companies want to spend less

for more powerful technology. In order to support a growing demand, there are 3G and 4G

technologies that are “hungry” for spectrum, but it is a high expenditure to buy a license thus

one solution is to look for improvements in the hardware level with regard to spectral

efficiency. The network cost differs depending on spectral efficiency, bandwidth, frequency

and other factors. These factors is determined in this work considering coverage and capacity

demand which supposed to have different approaches and base station technology and

backhaul. It means the motivation of thesis is to consider the influence of these factors on the

final cost and final power consumption.

Nowadays, the question of power consumption becomes more popular due to the climate

issue. According to research [1], 0.5 percent of global energy consumption is consumed by

mobile networks today and the number is projected to increase manifold in the close future. It

1

arises a question what type of base stations consumes less power. Since base station sites are

responsible for 80 % of the energy consumption [2]. However, even if one type of base

station can consume less than another, it does not mean that it is the same when operator

begin planning a whole network with backhaul. An interesting question is about what type of

base stations is better to choose, femto or macro cells and what technology is better to use

with them. So there is the possibility to decrease power consumption on the architecture level,

but it is also important to take into account the backhaul solution and its power consumption

model and cost model as well. Backhaul solution for indoor usage includes a topology and

technology compromise that is required to be cost and power efficient and able to support a

capacity growth with fair access to all users. These problems meet a question what required

number of base stations is needed to meet user demands which in turn depends on coverage

and data requirements in the chosen scenario.

The increasing trend of data usage does not allow the operator to stay with the same type and

quantity of technologies, expansion of broadband access territory is necessary. Some literature

claim that new technologies must be implemented that requires deployment from the scratch,

another source [3] claim that it is necessary first to consider the thought of upgrading the

existing network infrastructure. Steps should be taken as soon as possible, but what steps

should be taken here? The problem is that an inaccurate methodology can affect the quality of

service (QoS). The calculation steps are required to make a plan of network, but it is hard to

find it in a well described and organized order. This missing point is described and fulfilled in

this thesis.

To solve the problem it is necessary to select the type of base stations that consume less

energy and to choose the right architecture taking into account the capacity, budget, indoor

environment and backhaul solution.

1.2 Literature review

The Earth project [4] has several deliverables that describes the process of decreasing of

power consumption. First deliverables [5] [6] helps to find a way to evaluate energy

consumption of different types of base stations and to derive accurate metrics for this report.

It also gives a clear comparison of several network solutions while considering conflicts of

2

interest to meet low power and high quality requirements. Thus, it becomes easier to exclude

or include these network solutions to find an optimal network design. As a result, researchers

of “EARTH” project have concentrated on an energy-oriented design, while the cost and

spectrum designs have been skipped.

A comparative study of macro and femto networks is explained in [3] and gives a good

example of a way to study the problem and prepare a scenario. This research also shows a

believable cost-oriented design includes usage of spectral efficiency and wall penetration

losses. However, energy consumption of the whole network has not been considered yet.

An extensive explanation and implementation of “EARTH” framework to count energy

consumption is described in [7] where a backhaul solution is taken into consideration. This

work concludes that backhaul influence the energy consumption of whole network and

depending on topology and technology it is able to decrease it. However, what topology and

technology is better for indoor environment is still unclear.

Another research described in [8] is about using macro cells for outdoor usage and femto cells

for indoor usage or only macro cells for both type of usage. This approach makes a

comparison difficult additionally to the problem how to fix user demand and what metrics

(units) to use. The fairness of access for suburban user is an important issue. The data for the

experiment has been chosen randomly. Furthermore, buildings have only one floor and many

problems and losses are not counted, where one is interference when using macro and femto

cells simultaneously.

After study of related works, a gap has been found. On one hand, some papers [5] [7] consider

an evaluation of power efficiency and its metrics carefully, on the other hand [3], the problem

is considered from the techno-economic side without looking into the level of power

consumption.

Mostly, related works propose formulas without clarification what measurement units it must

used W, kW or dBm and so on. Then while calculation process, important to know if a

calculated value is in the right range, it was not found in the related works. Then how to

locate a femto cells in the building is not presented in any related work. It is hard to find a

clear description of cost structure for network with backhaul, because depends on backhaul

link type changes a little bit the cost structure of radio access network. It is hard to understand

from related works how to calculate power consumption of specific backhaul topology, if to

3

look into formulas then there is no difference, is means the formulas are not adopted for

different topology cases.

Finally, the gap is that the power consumption and cost calculation steps described very

briefly and there is hard to begin research, because the beginning step are not described, how

to plan network, how to calculate the needed number of base stations, the power

characteristics of base station such as transmission power, radius of transmitted signal, then

topology-depended power consumption and cost investment and others above described gaps.

This work composes the beginning and final steps, at the same time adopted existed formulas

in the right way.

Then the report focus is the merging of several research projects and papers to make a proper

network comparison of macro cells and femtocells for indoor usage, taking into account its

power efficiency metrics and ability to support several types of demand, penetration rate, cost

model and spectrum characteristics.

Since the backhaul transmission influences on a power consumption of the network, the report

is considering a topology and technology that maximally satisfy indoor requirements.

The idea is to propose an optimal solution and to look into different methods of planning

networks focusing on decreasing power consumption and network cost.

1.3 Research questions and problem formulation

Before research begins, it is important to set up several questions which have to be answered

in the result consideration. They are presented below:

1. How does the backhaul technology and equipment influence the cost and power

consumption?

This question reflects one main point of this thesis, because the final cost and final power

consumption includes both network: end-user network and backhaul network. Meanwhile the

possibility to upgrade equipment is presented in the research, it means the existed sites is

within the deployment territory able to decrease the investment cost. Therefore the big

4

territory is chosen to be research, such as a university territory where is easier to measure the

backhaul influence and topologies impact.

2. How to compare macro and femto cell base station costs, power consumptions and

spectrum usages?

This question means how to find a fair conditions which allows to compare them to discover

their strong and weak places. Therefore the two types of demand would be introduced in the

assumptions part of this thesis work.

3. How does the spectrum characteristics influences the cost and power consumption?

In this thesis, the spectrum characteristics means used spectral efficiencies and bandwidths

within the same frequency range. Dynamic model of traffic at peak hours has been

considered, it means the work hours is taken in account as the highest traffic demand hours.

After this time the traffic might decrease significantly. If network is able to meet a traffic

demand in peak hours then it is easily support a decreased after peak hours traffic.

4. What method and calculation frameworks to use in estimation of energy consumption?

These base stations have as well as similarity in estimation process as differences that are

connected with cover and capacity possibilities, such as radius, transmission rate, looses,

transmitter power and what type of demand they are going to meet. It means energy

consumption calculation framework varies depending on base station type and backhaul

solution, where environment factor plays significant role, such as wall attenuation.

This work includes collecting all calculation results in systematic order to discover

advantages and disadvantages of the chosen models. The consideration includes:

a. Upgrade existing sites. If there is a chance to reuse existing infrastructure, it

can help to decrease CAPEX;

b. Coverage demand;

c. Usage demand;

d. Wall penetration;

5

e. Power consumption.

Metric values are up to date to make a fair comparison in the three dimension system: cost,

spectrum efficiency and energy consumption. The cost is considered as investment cost called

CAPEX and operation cost OPEX in 5 years period.

Evaluation framework strategy and calculation requires considering the metrics derived from

literature study to make them satisfy the thesis idea and define the steps of calculation and

dependencies.

6

7

CHAPTER 2

NETWORK ARCHITECTURE

This chapter 2 gives a basic description of architecture required to understand the next

calculation steps and research that were made. A reader has been introduced to the main

concept of core network and backhaul.

2.1 General description of the mobile network architecture

Research is provided in terms of using a mobile network. Mobile network consists of three

main parts: a radio access network (RAN), core network and backhaul network. The radio

access network consists of number of base stations and it is located between user equipments

(UEs) (such as laptop, desktop computer, smartphone and so on) and core network.

Fig.2.1. Brief description of network architecture

8

2.3 Backhaul solutions and topologies

Usually, the choice for network operators is between fiber and microwave leased line, due to

high capacity potential and increased traffic demand in future. The microwave and fiber are

different in their structure and way of connect to base stations. The microwave is used the

microwave link to connect with base stations. The difference is shown in the Fig.2.3.

Fig.2.3. The nowadays choice of modern backhaul technologies [11]

The architecture of backhaul consists of several aggregation nodes, switches/hubs and

wired/wireless links to all base stations. Each aggregation node handle the traffic of several

base stations that are connected to it. The way is how to connect the base station is decided by

topology choice, which is considered in the paragraph 2.3.3 below.

10

2.3.3 Topologies

All base stations should be organized in groups for the effective traffic management, because

aggregation point has limited capacity. It means it can support the limited number of base

stations. This number of base stations that connected to one AGGP also can depend on the

type of topology, how the base stations is connected. The backhaul has three topology options:

star, ring and tree. In the star topology, link from AGGP to base station must be able to handle

the one base station maximum traffic ability. While in the ring topology, the link must be able

to support the traffic that sends by all base station in this group, as it can be visible from

Fig.2.6. In this research the maximum amount of connected base stations in the star topology

is 16, in the ring topology is 10. In the fiber backhaul solution, the star topology is usually

used as the most effective solution, because, for example, the ring topology is too expensive

due to the long cover distance.

Fig.2.6. Backhaul topologies

Then if microwave backhaul is ring-based then each base station in this topology has to have

the additional switch that forwarded the traffic to the next base station, where the AGGP

handles the final traffic of this base station group. In the ring topology, one switch is enough

for one group of base stations. So in star topology, there is only one hub or switch that

collects and forwards data, while in ring topology each base station has to have a switch that

able to forward the traffic through one base station to another ones.

13

2.4. Core network

The core network is the central part of mobile network which control the basic switching and

roaming services between different devices from different subnetworks. It means its function

includes the aggregation of network devices(routers, switches), control of the authentication

process, interconnection of networks and charging. The core network connects by backhaul

link to the radio access network and decides where to send data and how charge it.

14

15

CHAPTER 3

DEPLOYMENT METHODOLOGY

The chapter 3 describes calculation steps and presents values of necessary parameters to

evaluate power and cost of access network and its backhaul. A description of a scenario and

research assumptions is provided for an experimental study.

3.1 General description

The research considers the big deployment area that can be new university/college campuses,

labs, conference halls and several student dormitories. It necessary to introduce ability to

consider backhaul topology influence and backhaul itself. Then the idea is to consider two

type of base station: macro cells or femtocells to meet the anticipated indoor demand. The

outdoor demand is eliminated. Some ideas of the proposed scenario can be found in [3].

There is 2 types of deployment. First is green field deployment, where all base station would

be installed from scratch. Second case is when within territory macrocell sites already exist,

they needed to be upgraded, it can decrease the investment cost. Reuse of existed sites on

actual territory is an additional influence on cost structure, where Inter-site distance (ISD) of

existed sites is 500 m.

Generally, research is focused to plan deployment in terms of deployment cost, running cost,

power consumption considering both of radio access network part and backhaul network.

16

Backhaul technologies are chosen to be a fiber-based network or microwave-based network.

The microwave backhaul is presented in two topologies: star and ring. The more detailed

overview of technologies is described above in Chapter 2.

3.1.1 Coverage demand and assumptions

The first demand is to cover the whole area within which is located anticipated end-users that

users would able to connect to internet. It is called the coverage demand [14]. In this case,

frequency factor impacts the radius of each base station [15], it is able to decrease or increase

base station’s cover ability. For study purpose, frequency is chosen to be 2,6 GHz. Because,

for macro cells and outdoor environment, 900 MHz frequency could be used because its

radius cover big territory with a few sites and easily meets the outdoor demand. But this

frequency is not so good decision for indoor environment, especially in case of femtocells

where the small coverage area is beneficial in indoor environment. Therefore only 2,6 GHz

frequency is used to make a calculation.

The examples of deployment area can be new university/college campuses, where the

population density is 1 000 person per building. The number of buildings is 10, each has a

square 0.5 km2, because there is a need to check the topology difference for a microwave-

based network and it is better to do using a big area. Each building has 5 floors, each floor has

2 m height. Since the height of whole building is 13 m. The whole territory where all

buildings are located has a square around 5,67 km2.

17

Fig.3.1. Deployment area

The border walls and floor wall has a wall attenuation around 20dBm, while the intermediate

wall has 6 dBm of wall attenuation because of another material. It is important to know when

it comes to dimensioning the cover ability of base station.

3.1.2 Capacity demand and assumptions

The second demand is to serve enough amount of traffic to all anticipated users at the same

time especially in peak hours. It is called a capacity demand [14].

The capacity considers the bandwidth 5 / 10 / 20 MHz. and two types of spectral efficiency:

0,67 and 1,67 bps/Hz.

Values source is [3]. Each user consumes 14,4 GB per user per month. In sum, 10 000

workers are within the area, their demand is 2 Gbps during work/busy 8 hours. However the

usage level fluctuates around 10% and 50%, then user demand is 0,2 Gbps (10% usage) and 1

Gbps (50% usage).

18

Macro 5 10 20 40 80

0,67 10 20 40 80 160

1,67 25 50 100 200 400

Femto 5 10 20 40 80

0,67 3 6 13 26 53

1,67 8 16 33 66 133

Table 3.1. The capacity of base station

According to influence on each other of spectral efficiency, bandwidth and cell size, the

capacity (Mbps) of TRX is changing as shown in the Table 3.1 above, where the calculation

based on a multiplication of bandwidth and spectral efficiency.

3.2. Cost and Power Models

3.2.1 Cost model

Cost model has been divided on CAPEX and OPEX. Deployment is going to be done in first

year, while the maintenance and a bill for a power consumption is every year duty. Therefore,

the price for deployment is including in CAPEX, the maintenance is in OPEX.

To calculate CAPEX, first is necessary to count it for 1 unit equipment for 1st year, then using

price erosion (5%) determine each CAPEX for next year if it is deploying for several years,

CAPEXi,k=CAPEXi,k-1*0,95 where i-RAT type, k-year, k-1- is a last year CAPEX. The same

steps should be done with OPEX Calculation. However in our scenario, the deployment is

considering only for one year. Because for comparison is enough to know the 1st year

number.

CAPEX= Σ CAPEXi,k; ( Eq. 3.1 ),

OPEX=Σ OPEXi,k; ( Eq. 3.2 ),

Cnetwork= (CAPEXi,k + OPEXi,k)*N, ( Eq. 3.3 ),

where N-number of cells (#cell) i-type

19

Fiber has a cost of link that measured in covered distance and number of aggregation nodes.

The microwave backhaul the cost of link, the spectrum fee and aggregation points. For last

mile network the deployment cost includes:

Ctot=Cinfra+Cenergy ( Eq. 3.4 ),

The leased line, E1, O&M (CAPEX*0,1), electricity bill includes. In this case the cost of

whole network Ctot includes the annual cost of each base station type C0 multiple number of

base station Nbs and annual energy consumption C1 [kEuro/dBm].

Ctot=Nbs*C0+Pwh*C1 ( Eq. 3.5 ),

There C0 includes the CAPEX and OPEX of core and backhaul network where

FemtoCapex=Nbs*(FemtoCellBS+EthernetCables+DataLineInstallation) ( Eq. 3.6 ),

Fiber Capex = 7856+Nbs*0,58 ( Eq. 3.7),

FiberOpex=LeasedLine(12)*Nbs+(Femto/MacroCapex+FiberCapex)*0.1 ( Eq. 3.8 ),

MicrowaveCapexStar=CostSink CostSwitch*Nbs/16+10*Nbs ( Eq. 3.9 ),

MicrowaveCapexRing=CostSink+CostSwitch*Nbs+10*Nbs/10 ( Eq. 3.10 ),

MicrowaveOPEXfemto=(MicrowaveCapex+Femto/MacroCapex)*0.1 ( Eq. 3.11 ),

MicrowaveOPEXmacro=(MicrowaveCapex+Femto/MacroCapex)*0.1+SiteLease*Nbs

( Eq. 3.12 ),

CAPEX=Femto/MacroCAPEX+Fiber/MicrowaveCAPEX ( Eq. 3.13 ),

OPEX=Fiber/MicrowaveOpex+Electricity ( Eq. 3.14 ),

Fiber/MicrowaveCapex means the CAPEX but it depends on what type of backhaul it has

been calculated. The type of base station is Femto/Macro, the type of backhaul

Fiber/Microwave. Where Femto/MacroCapex is a CAPEX of all base station of Macro or

Femto type. FiberOpex is OPEX of whole network with fiber backhaul.

MicrowaveOPEXfemto/macro the microwave backhaul OPEX depends on type of base stations to

which it is connected. Some costs are presented in table below:

Cost [kEuro]

Equipment

Femto base station+Ethernet cables 1

Macro base station 25

20

Macro additional cells 15

Sink node, CostSink 40

Switch, CostSwitch 1.2

Installation and buildout

Macro BTS site installation/Site construction 20

Macro BTS buildout/Site construction 40

Data Line Installation per site 5

Running cost(annual cost per unit)

Leased Line 12

Site Lease, Macro BTS 6

O&M 10% of CAPEX

NPV

Discount rate 5%

Table.3.2. Cost characteristics and its values

Also CAPEX and OPEX changes in the case of reused sites, but it is only in macrocellular

deployment. Deployment is considering in 5 years, when all investments are done in first year

and other years is only running cost. Every year OPEX is increasing on 10%. The price of

electricity for industry is taken as 0,021 kEuro per dBm per year [26].

3.2.1.1 The number of cells to deploy the network

If, there is only need to meet a coverage then: the whole territory must be considered to

determine a number of macro base stations; or the area of one floor must be considered firstly

to count a number of femto base station.

If, there is only need to meet a capacity requirements: the traffic demand of all users is

considered for macro cellular deployment; or of one building/floor is considered for femto

cells.

Meanwhile, the research aim is to meet both demands. Therefore, it is good to look how it can

be done depends on base station type.

In case of macro cells, the issue is the lack of capacity for hot-spots that allocated in every

building. It means to meet capacity demands, the number base stations higher than to meet a

coverage requirements. UserDemand is a number of Mbps (Mbits per second) that is an

aggregated traffic in peak hours, while BaseStationCapacity the number of Mbps that a base

station is able to handle.

Nbs=UserDemand/BaseStationCapacity (Eq. 3.15)

21

3.2.2 Power model

Backhaul power model depends on passing-through traffic. While a base station power

consumption depends on chosen spectral efficiency, frequency and bandwidth.

3.2.2.1 The power model of one base station

To calculate the power of the whole network, there is two main parts should be considered: a

base station and backhaul power consumption.

The power consumption of base station depends on a frequency and a spectral efficiency, and

energy consumption depends on the traffic load of the whole network.

Pin=Ntrx*(a*Ptx+bradio), 0 ≤ Ptx ≤ Pmax (Eq. 3.19), [23],

There Pin is a power consumption of one base station depended on Ptx - its output power. Pmax

depends on a country regulation about the maximum level of a transmit energy. By the way, a

is responsible for a power amplifier and existed losses, bradio describes the level of using power

by cooling and the major energy consumer is a signal processing.

The power model of backhaul depends on number and quality of switches, and the traffic

load. The Table 3.3 presents the upgraded value of needed metrics. The Ptx values is taken

from related work [23].

MACRO FEMTO SOURCE

Pmax, dBm 46 17 [ 7]

a 5,32 7,5 [ 7]

bradio, dBm 52,71 36,02 [ 7]

Antenna Gain, dBi 14 6 [ 7]

Table 3.3. The values of necessary metrics

The power is calculated in dBm to avoid a big numbers and dimension the scale of figures.

dBm=10*log(Power in milliwatts) (Eq. 3.20 ), [18],

Ntrx is mostly about macro cellular network where the base station has been upgraded to 3

TRX, while femto cells has only one.

24

(Eq. 3.23), [7],

where Pi is a power consumed on i-type base stations that has additional factor as ci-SFP

interface power consumption.

Pi=ai+bradio,i+ci (Eq. 3.24), [7],

To find the total number of all uplinks of all switches should be calculated next way:

Nul= [Agtot/Umax]*(Nbs/Nports) (Eq. 3.25),

25

The whole network power consumption is ƤMW includes the power consumption of a core

network that are using wireless link and the power consumed by microwave technologies to

send and receive the signal.

28

29

CHAPTER 4

Results and discussion

This chapter presents a result analysis that have been drawn from this experimental study. The

figures shows the comparison between femto cell and macro cellular network. The drawn

result are considered and described in terms of cheaper or more power efficient network

deployment.

4.1 The number of femto and macro cell base stations

The calculations have been made taking into account the capacity demand as well as the

coverage demand for both types of base stations. Then, optimal results have been chosen

using next assumptions:

• macro cell deployment has to be able to meet capacity demand. Because the macrocell

has a wide area of coverage, but low capacity. The numbers have shown when it needs

to meet the capacity demand, the higher number of cells is required. The Fig.4.1

shows that number of base stations changes depend on capacity demand.

• femtocell deployment has to be able to meet coverage demand. Because a femtocell

has high capacity, but a low radius. The Fig.4.2. shows that the number of femtocell

base stations does not depend on the capacity demand. It depends on the coverage

demand which is to cover whole area.

In Fig 4.1, the results of a high demand satisfaction are shown with distinguish of the highest

and lowest number of base stations. The main point is to have enough numbers to cover area

30

For example, the macro cell base station is able to cover a big area, therefore it is easily can

cover 5.67 km2 of demanded area with 14 base stations (5MHz, 0,67bps/Hz). However, 14

base stations are not able to satisfy a user demand because they do not provide enough

capacity for such high demand, only 100 units with the same characteristics are able to meet

coverage and capacity demand. It means the higher bandwidth and spectral efficiency make

impact on decreasing number of base stations, as shown on Fig.4.1-4.2.

Though, in femto cells case, the frequency 2.6 GHz influences on the transmitter power and

the radius of each base station. The radius of base station is the main point to meet both

demands, since femto cell has already a high capacity. If to install a number of BSs taking in

account only a capacity demand then the cover area will be very small and the connection will

fail if too many users will be concentrated in these several points.

If reused the existing network:

The re-use factor in the macro cell deployment impacts the cost of CAPEX, because the

installation cost can be eliminated that decreases a cost.

The Inter Site Distance of existed sites in urban has been taken as 500 m. As result, around 58

sites exists and can be reused, it means there is no need in installation of new sites. However

in case of meet the high demand by base station with BW=5 MHz, there is need to install 42

new sites.

Though the deployment of macro definitely requires lower number of base station, there is the

need to check what type consumes less electricity.

4.2 Power consumption results

This section describes power consumption results. Then there is given the explanation to the

interesting results.

4.2.1 Result presentation

Firstly, the power of one base station is calculated by using a dynamical model depended on

bandwidth, spectral efficiency and type of user demand.

32

transmitter architecture should be revised and improved. For future work, there is need to look

into the architecture level of transmitter to decrease the power level in the future.

If to compare femto and macro base stations, the femto BS consumes very small amount of

power consumption. It is almost in 20 times less than macro BS consumption if 1.6 bps/Hz

used. In 12 times less than macro BS consumption if 0,67 bps/Hz used.

However when it comes to the power consumption of whole femtocellular of macrocellular

network, the trend might change. This thesis's macrocellular network spectral efficiency

consumes more energy on 0.67 bps/Hz efficiency level, while in case of femtocellular

network is 1.67 bps/Hz consumes more energy. It means that trend of one base station is saved

only if it comes to the numbers of femto base stations. It can be explained by the changes in

the number of base stations, where macro base station number depends on capacity of base

station. The higher spectral efficiency allows to utilize traffic better almost twice, then the

required number of macro base stations decreases. It allows to compensate the high power

consumption by twice smaller number of macro base stations. Therefore, it is better to choose

1,67 bps/Hz if there is need to meet the high capacity demand.

If to look into results with different bandwidths, the macro base station consumes twice less

when the bandwidth is increased. For example, 20 MHz bandwidth consumes twice less than

10 MHz bandwidth. Even if in backhaul this difference is less mentionable, it is still better to

use 20 MHz bandwidth.

Fiber backhaul itself consumes less than microwave. In femtocellular network, fiber still

consumes less. In macrocellular network, microwave backhaul consumes less. So both of

these backhaul types can be useful for indoor environment. But fiber is better to deploy in

case of femtocells and microwave is better in case of macrocells. It can be explained that

macro base station is located outside of building, so building structure impacts the quality of

signal less. In femtocell case, microwave has to transmit stronger signal to penetrate the

building and increase the number of microwave antennas to handle the network load.

Finally it is shown that the trends of increases and decreases can be impacted by type of

demand. If one base station consumes less than another, it does not mean that the same will

happen when the group of base stations is going to be installed. It depends on the type of

demand which lead to calculation of the number of base stations taking in account other

characteristics, such as frequency, spectral efficiency and bandwidth.

36

efficient in macrocell case. As it can be seen from the Fig.4.11, the microwave backhaul is

very cheap to maintain and it is cheaper than using fiber-based backhaul.

Macrocellular network deployment is cheaper in comparison to femtocell deployment. The

reason in the additional equipment, the number of femto base station is much higher that

macro BSs number, it means more link and more switches must be used.

There is obvious that the whole microwave-based network is the cheapest with macro cells

deployment. It means that fiber is a good decision for indoor environment that are stable and

has a growing demand even if the price a very high.

41

42

CHAPTER 5

Conclusion and future work

The main challenge is to look inside the network architecture for each base station type, it has

different approaches that requires careful modeling of scenario and formulas, because it is

easy to calculate the power consumption or cost of one base station, but when it comes to the

deployment/planning level, then important to define what kind of equipment is going to be

used for each base station, backhaul and what values it should have. Then depends on type of

demands, base station has been described as coverage or capacity limited, then depends on it

the different planning and calculating strategies have been chosen to maximum imitate the

real environment. For instance, in this thesis, when femtocells are planning indoor demand, it

is important to consider the building in two dimensions: horizontal and vertical to decrease a

number of used base stations and avoid unnecessary interference. Then it means a careful

planning of indoor walls and its wall attenuation. Moreover, the number of user that base

station able to serve simultaneously must be founded according to base station possibility.

While macrocell deployment consider the whole area. Macrocells should be located between

building to better utilize it is range and to meet one main wall to decrease a wall attenuation

and signal loses.

As we know, macrocells usually already exist and high-densed in the urban territories and less

densed within rural territories. There is the green deployment is more expensive, but still

cheaper than femtocell deployment.

43

The result is that higher bandwidth and spectral efficiency give the minimal number of both

base station types.

In the beginning femto base station is the cheapest and consumed less option than macrocell.

Probably, if study were provided in terms only one type of demand, then this trend would not

be changed. In case to meet only coverage demand, the macrocells is the best decision, in case

to meet only capacity demand, the femtocells are the best solution. In this thesis, the

requirement to meet both type of demand brings the result that macrocell deployment is more

effective than femtocells. Macrocellular network consumes less if it has the microwave

backhaul, femtocellular network consumes less if it has the fiber backhaul. The most power

and cost efficient spectral efficiency is 1.67 bps/Hz for macrocell deployment, and 0,67

bps/Hz for femtocellular deployment.

However femtocells is partially paid by a customer who take most care about femtocell

installation and some cost payment. In this case it can be useful for future to consider the

participation of user payments in the finance planning of CAPEX and OPEX.

The higher bandwidth gives better results in both cases, while spectral efficiency is react on a

type of demand and therefore macro and femto base stations have a different power efficient

spectral efficiencies.

Mostly, big expenditures in NPV is OPEX, and mostly OPEX is higher than CAPEX because

of power consumption. Therefore the base stations(mostly macro) architecture requires the

investigation to understand where to begin a shortage of power consumption. Some problems

has been managed thanks to a spectral efficiency and higher bandwidth, it can be continued in

this way or in the hardware way.

Net present value shows that OPEX is a dominated part of network cost, because OPEX is

required to be spent each year and most part of OPEX is a power consumption, it is almost 70

percent of OPEX.

The microwave is a great way to cut expenditures, however it is better decision in case of

macro cellular network, as the number of aggregation points are less and therefore the power

consumption cost is much less than in case of high number of femtocells required a big

number of aggregations points.

44

The future investigation can be made in next areas using the above presented parameters.

Depends on a spectrum regulation in different countries the cost of spectrum could be

different, it could be even free. Therefore, it is better to choose the type of spectrum scenario

basing on the choice of regulations and might to choose a specific country.

When network has been deployed it is good to find a good management mechanism which

will turn off or send a base station to a sleep mode, when the pick hours finished.

Then, introduce, if there is an interest, a heterogeneous deployment. It is useful to use the

results above, when it is known which parameters influence in decrease or increase of a power

consumption and a cost, its CAPEX and OPEX.

45

46

References

[1] Vodafone, Accenture, “Carbon Connections: Quantifying mobile’s role in tackling cli-

mate change”, report, July 2009

[2] GSM Association, “Mobile’s Green Manifesto 2012”, Report, [Online]. Available:

http://www.gsma.com/publicpolicy/wp-content/uploads/2012/06/Green-Manifesto-

2012.pdf , GSM Association

[3] Markendahl, J.; Mäkitalo, O., "A comparative study of deployment options, capacity and

cost structure for macrocellular and femtocell networks," Personal, Indoor and Mobile

Radio Communications Workshops (PIMRC Workshops), 2010 IEEE 21st, International

Symposium on , vol., no., pp.145-150.

[4] “EARTH project deliverables and description of project”, 2011 EARTH consortium, [On-

line]. Available: https://www.ict-earth.eu/

[5] “EARTH project. Deliverable D2.4 Most suitable efficiency metrics and utility functions”,

INFSO-ICT-247733 EARTH, January 30, 2012, [Online]. Available: https://bscw.ict-

earth.eu/pub/bscw.cgi/d70454/EARTH_WP2_D2.4.pdf

[6] “Deliverable D3.3. Final Report on Green Network Technologies”, INFSO-ICT-247733

EARTH, July 16th, 2012, [Online]. Available: https://bscw.ict-

earth.eu/pub/bscw.cgi/d70472/EARTH_WP3_D3.3.pdf

[7] Sibel Tombaz, “Towards Green Wireless Access Networks: Main Tradeoffs, Deployment

Strategies, and Measurement Methodologies”, Licentiate Thesis in Information and Com-

munication Technology, KTH Royal Institute of Technology, Stockholm, Sweden 2012,

[8] Zhihao Zheng, Master thesis, “Energy Efficiency Performance Improvements Through

Two-Tier Cellular Networks”, Master of Science Thesis, KTH Royal Institute of Technol-

ogy, Stockholm, Sweden 2012

[9] James F. Kurose, Keith W. Ross, “Computer networking. A top-down approach”, Fifth

edition, ISBN-10: 0136079679, March 31, 2009

47

[10] Darrell Davies, “Briefing paper: Femtocells in the Home”, December 2007, [Online].

Available:

http://www.motorolasolutions.com/web/Business/Solutions/Technologies/Femtocells/_Do

cuments/Static%20files/Femtocells_Briefing_Paper.pdf

[11] “Mobile backhaul networks”, TransPacket AS (R), 2013, [Online]. Available:

http://www.transpacket.com/hybrid-networks/mobile-backhaul-networks/

[12] “TECHNICAL BRIEF | Microwave Backhauling - Meeting the Capacity Challenges of

4G/LTE and Beyond”, Ceragon Networks Ltd. (NASDAQ: CRNT)

[13] “Microwave backhaul set to beam support for next-generation networks.” RCR Wireless

News Feature Report.

[14] Nokia Siemens Networks, “Improving 4G coverage and capacity indoors and at hotspots

with LTE femtocells”, White paper, 2011, [Online]. Available:

www.nokiasiemensnetworks.com

[15] David Onslow, “Two-way radio success. How to choose two-way radios and other wire-

less communication devices for your business”, 2012, 3rd Edition v3.1, pp. 7-11, [Online].

Available: http://www.intercomsonline.com/v/vspfiles/downloadables/Free-Two-Way-

Radio-Book.pdf

[16] Seybold, John S, “Introduction to RF propagation.” John Wiley and Sons Ltd., ISBN 0-

471-65596-1, 2005

[17] “Path Loss, Link Budget & System Operating Margins”, [Online]. Available:

http://www.4gon.co.uk/solutions/technical_path_loss_link_budget_som.php

[18] Steve Rackley, “Wireless networking technology : from principles to successful imple-

mentation”, Oxford : Newnes, ISBN-13: 978-0-7506-6788-3, 2007

[19] Savo G. Glisic, “Advanced Wireless Networks: 4G Technologies”, University of Oulu,

Finland, John Wiley & Sons Ltd., ISBN-13 978-0-470-01593-3, 2006, pp. 70-77

[20] Jim Geier, “How to: Define Minimum SNR Values for Signal Coverage”, [Online]. Avail-

able: http://www.wireless-nets.com/resources/tutorials/define_SNR_values.html

[21] Richard Wolff, “Noise, S/Nand Eb/No”, lectures notes for the course EE447, Fall 2011,

[Online]. Available: http://www.coe.montana.edu/ee/andyo/EE447/EB%20and%20NO.pdf

48

[22] Ashraf Awadelakrim Widaa, Jan Markendahl and Amirhossein Ghanbari, “Toward capac-

ity-efficient, cost-efficient and power-efficient deployment strategy for indoor mobile

broadband”, Wireless@KTH, KTH Royal Institute of Technology, paper submitted to the

24th european regional conference of THE INTERNATIONAL TELECOMMUNICA-

TIONS SOCIETY, Florence, Italy, 20 - 23 OCTOBER 2013.

[23] Gurther Auer, Vito Giannini and Claude Desset, “How much energy is needed to run a

wireless network”

[24] Cisco official website, Products&Services, Switches, Service Provider – Aggregation

Switches [Online]. Available: cisco.com

[25] Lectures notes for the course IK2510 Wireless Networks, KTH Royal Institute of Technol-

ogy, autumn 2012, unpublished

[26] Europe’s energy portal, “Electricity. Industry” [Online]. Available: www.energy.eu [Ac-

cessed: 12-May-2013]

49