Evaluation of Femtocell Technology Challenges and Its Power

Control Methodologies for Green Heterogeneous Networks

Mazen Al Haddad and Magdy Bayoumi

Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA, U.S.A.

Keywords: Small Cells, Femtocell Technology, LTE, Hetnet.

Abstract: Femtocell technology brings extended low-power radio coverage directly in the indoor premises, where

propagation loss is typically highest. It also enriches both macrocell wide-area and in-building solutions in

terms of coverage & capacity. The integration of femtocells into heterogeneous cellular networks is foreseen

as a low-power and low-cost solution to cope with the exponential growth of required data traffic volumes,

offload the macro base stations and offer high performance mobile networks. However, the massive and

unplanned deployment of femtocells and their uncoordinated operations may result in harmful co-channel

interference and cause significant power waste in order to maintain an acceptable user performance. In this

work, we survey the technical challenges of femtocells deployment and the available energy control

techniques. Moreover, we look into adaptive mechanisms for femtocell technology to cover the way

towards green-oriented mobile networks. Our intention is to examine how femtocell deployment can share

the available radio resources efficiently in order to limit the average power consumption and mitigate co-

channel interference. Besides the introduction of the basic ideas for optimizing the spectral and energy

efficiency in femtocell networks, typical interference management techniques are discussed too, with a

special emphasis on power control methodologies.

1 INTRODUCTION

Recent analysis has shown that wireless networks,

not data centers, are the biggest energy drain in

cloud services. This is because more and more

people are accessing wireless networks with the

prospect of being connected anywhere and anytime.

Tablets, smartphones and laptops no longer need to

connect to wireless networks via cable. Instead,

WiFi or indoor/outdoor cellular solutions which are

inherently energy inefficient and a heavy contributor

to energy consumption are used (Bell Labs and

University of Melbourne, 2013).

As shown in Figure 1, a femtocell is a cellular

base station (BS) solution typically installed by the

end-user and transmits with minimal transmission

power to serve residential or small business

environments. It connects to the service provider’s

network via broadband such as Digital Subscriber

Lines (DSL) and typically supports only a few user

equipments (UEs). Femtocells can be deployed in a

variety of scenarios such as: Offices and residences

(from single-family homes to high-rise buildings),

public hotspots (shopping malls, airports,

train/subway stations, stadiums) or outdoor public

area sites.

Due to its advantages such as low cost and high

energy efficiency, femtocell technology has been

proposed and applied by the 3rd Generation

Partnership Project (3GPP) in its Universal Mobile

Telecommunications System (UMTS), Long-Term

Evolution (LTE) networks and its Advancement

(LTEA) (Knisely et al., 2009), (3GPP TR 36.814,

2010).

Figure 1: Basic Femtocell Network.

From the telecom provider’s viewpoint, a

significant amount of traffic can be moved from the

macrocell networks to femtocell networks. Thus it

reduces the number of macrocell BSs and

equipments for backhaul transmission from

macrocell BSs to their core network. This greatly

247

Al Haddad M. and Bayoumi M..

Evaluation of Femtocell Technology Challenges and Its Power Control Methodologies for Green Heterogeneous Networks.

DOI: 10.5220/0004933802470255

In Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems (SMARTGREENS-2014), pages 247-255

ISBN: 978-989-758-025-3

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

diminishes cost and power consumption. From the

customer’s viewpoint, the femtocells can be

conveniently deployed as desired, providing

sufficient radio signals to the UEs whilst consuming

less power in indoor environments. It may also not

be powered at all times for further energy savings.

The typical power consumption of a femtocell is

likely to be in the range of a few Watts, which is

obviously much less than that of macrocell BSs. One

other benefit of femtocells is that they help the

user’s battery last longer indoors where data rate

requirements are often highest. This is because less

power is required to transmit a signal over the short

distance to the femtocell rather than over the long

distance to a macrocell BS.

As femtocells are customer-deployed without

proper network planning, their interference

mitigation is more complicated than the traditional

macro-level networks. Thus, interference problems

in femtocell networks cannot be solved by existing

schemes typically used for macrocell deployments.

In (Kan et al., 2011), it’s shown that the interference

can be categorized in two types, the interference

between macrocell and femtocell (i.e., inter-tier

interference) occurs when femtocells utilize the

spectrum already allocated to the macrocell and the

interference between femtocells themselves (i.e.,

intra-tier interference).

Without proper interference management,

significant power is likely to be wasted in order to

maintain an acceptable user performance and quality

of service. For example, usually the high transmit

power is radiated by a macrocell BS to provide the

services for outdoor UEs. If no proper downlink

power control is applied at the macrocell BS,

interference is possibly generated to indoor UEs

connected to the femtocell BS in case the whole or a

part of the frequency band is shared between the

femtocell and macrocell. Therefore, the femtocell

BS has to increase its transmission power to

maintain the communication with its indoor UEs. In

this case, the overall energy consumption becomes

even worse after deploying the femtocells.

Interference management is therefore a key issue to

being able to capitalize on the potential energy

efficiency in femtocell networks.

In this paper, we analyze some power control

techniques related to femtocell technology to

mitigate the happening interference and keep energy

saved where possible.

2 WHY SMALL CELLS AND

FEMTO TECHNOLOGY?

Studies on wireless usage show that more than 50%

of all voice calls and more than 70% of data traffic

originates indoors

(ABI Research, Picochip, Airvana,

IP.access, Gartner, Telefonica Espana, 2007). For indoor

devices, propagation and penetration losses will

make high signal quality and hence high data rates

very difficult to achieve.

In this sense, femtocells are the ideal

complement to the macro network. A better, faster

user experience is delivered from a lower power and

a lower cost site. Customer-close sites can be

deployed and re-deployed as data demand ebbs and

flows in the network

(The Small Cell Forum, 2013).

Types of small cells include femtocells,

picocells, metrocells and microcells based on

increasing size from femtocells (the smallest) to

microcells (the largest). Any or all of these small

cells can be based on ‘femtocell technology’— i.e.,

the collection of standards, software, open

interfaces, chips and know-how that have powered

the growth of femtocells. Small cells are low-power

wireless access points that operate in licensed

spectrum and are feature edge-based intelligence.

Femtocells or Home Node Bs have been a hot topic

for quite some time since they offer benefits such as:

Improved Cellular Coverage and Capacity:

femtocells facilitate a new variety of mobile services

that exploit the technology’s ability to detect

presence, connect and interact with existing

networks. The enormous gains reaped from smaller

cell sizes arise from efficient spatial reuse of

spectrum. In addition to the full coverage and high

speed transmission at home, they increase the area

spectral efficiency (total number of active users per

Hertz per unit area) (Alouini and Goldsmith, 1999).

Better Link Quality, Significantly Lower

Transmit Power and Prolong Handset Battery

Life: because of their short transmit-receive

distance, femtocells can greatly lower transmit

power, prolong handset battery life, and achieve a

higher signal-to-interference-plus-noise ratio

(SINR). These translate into improved quality. The

lowered transit power will mitigate interference

from neighboring macrocell and femtocell users due

to outdoor propagation and penetration losses.

Improved Macrocell BSs Reliability: when a pre-

authorized MS enters the coverage of a home BS

(femtocell), it automatically switches affiliation

from the serving macrocell BS to the femtocell.

Hence, initiating as well as receiving calls and data

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transmissions is performed as usual but through the

femtocell network instead and over its IP backbone.

This will enable the macrocell BS to redirect its

resources towards providing better reception for

mobile users and improve the service reliability and

resource provisioning.

Offload Data Traffic from the Macrocell BSs:

instead of deploying a lot of outdoor macrocell BSs,

the heavy data traffic can be offloaded to femtocell

networks. Offloading a fraction of the traffic to the

femtocells will improve the macrocell BS capacity

since it will have to handle less traffic.

Higher Performance and Customer Experience:

weak in-building coverage causes customer

dissatisfaction, encouraging customers to either

switch operators or maintain a separate wired line

whenever indoors. The enhanced home coverage

provided by femtocells will improve customer

satisfaction.

Cost-related Benefits: femtocell deployments

reduce the operating and capital expenditure costs

for network operators. The deployment of femtocells

will reduce the need for adding macro BS towers. A

recent study (Analysys Research Limited, 2007)

shows that the operating expenses scale from $60K

per year per macrocell to just $200 per year per

femtocell. In addition, the end user will benefit too,

for instance with special home-zone services— e.g.,

free calls, superior indoor coverage, and quality

without changes in phones—and seamless services

across all environments without dual or new

hardware equipment.

3 FURTHER TECHNICAL FACTS

ABOUT FEMTOCELL

The capacity potential of femtocells can be verified

rapidly from Shannon's Channel Capacity law,

which relates the wireless link capacity (bits/second)

in a bandwidth to the Signal-to-Interference plus

Noise ratio (SINR):

C = W log2 1 +



(1)

[Where W is the bandwidth of the channel in Hz, S

is the signal power in watts and N is the total noise

power of the channel watts]. We could increase the

capacity by increasing the amount of spectrum, if

possible, or we could also increase the number of

antennas at the transmitter and receiver, as done with

MIMO (multiple input multiple output):

C  n*Wlog2 1







(2)

[Where n here is # of antennas]. Another way to

increase the capacity is to manipulate the SINR

ratio. The SINR is a function of the transmission

powers of the desired and interfering transmitters,

path losses, fading and shadowing during terrestrial

propagation. The transmitted signal is usually

decomposed by Path losses. The simplest form of

Path Loss is expressed in dB and can be calculated

using the formula:

L  10nlog10





C

(3)

[Where L is the path loss in decibels, n is the path

loss exponent, d is the distance between the

transmitter and the receiver, usually measured in

meters, and C is a constant which accounts for

system losses]. The key to increase capacity is to

enhance reception between intended transmitter-

receiver pairs by minimizing d and n.

Reducing distance to end-user and lowering

femtocell transmit power will improve the capacity

through increased strength and reduced interference.

In addition, deploying femtocells will enable more

efficient usage of precious power and frequency

resources. Of course, the assumption here is that the

wired broadband provides sufficient QoS over the

backhaul. Otherwise backhaul capacity limitations

could reduce the indoor capacity gains provided by

femtocells.

New telecommunication radio technology like

the Long-Term Evolution (LTE) network is reaching

the limits of Shannon's law, the spectrum available

for mobile data applications is limited, and the only

solution for increasing overall mobile network

capacity is to increase the carrier-to-interference

ratio while decreasing cell size and deploying small

cell technologies like femtocells.

Figure 2: AVG. Throughput between UEs with/without

femtocell deployment.

Example scenario - throughput as a function of

macrocell / femtocell setup by using the simulator

software in (Piro et al., 2011):

 Averaged Throughput, 1 macrocell deployment

10000000

20000000

1MacroNoFemtocells

(50UE)

1Macro+25Femtocells

(25MUE+25FUE)

AVGThroughtput(bps)

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249

without femtocell support, and 50 UEs (all of

them are served by the macrocell alone).

 Averaged Throughput, 1 macrocell deployment

with femtocell support, and 50 UEs (25 served by

the macrocell + 25 by femtocells).

As illustrated in Figure 2, we can see that the

throughput has dramatically improved after

introducing femtocell to support the macrocell

deployment.

Table 1: Simulation system parameters.

Parameter

Scenario Macro

only

Scenario Macro

and Femto

Apartment size 10m2

Nr of apartment on a

building

Nr of buildings 1

Building Type 5x5 grid

Nr of Macrocell 1

Nr of HeNB (Femtocell) 0

1 per apartment

(25 per Building)

eNB power transmission

43 dBm, equally distributed among

sub-channels

HeNB power transmission

20 dBm, equally distributed among

sub-channels

Radius of Macrocell 1km

Nr. of users/UEs 50

Speed of UE 3 km/h

Total bandwidth 20 MHz

Flow Duration 10 Second

Frequency reuse schema N.A. Reuse-1/4

Activity Factor 1

Scheduler Proportional Fair

Traffic (Best Effort Flows) Infinite Buffer

Access Policy Open Access

Frame Structure FDD

4 GREEN FEMTOCELL

TECHNOLOGY

It’s discussed in (Bell Labs and University of

Melbourne, 2013) that Mobile networks, and

especially their radio access parts (frontend to user),

are by far the dominant and most concerning drain

on energy in the entire clouding system. The energy

calculations show that by 2015 wireless cloud will

consume up to 43 TWh in comparison to only 9.2

TWh in 2012. That is an increase of 460% which is

in carbon footprint from 6 megatons of CO2 in 2012

up to 30 megatons of CO2 in 2015. Figure 3 shows

up to 90% of this consumption is attributable to

mobile and access networks (data centers account

for only 9%).

Therefore, the focus should be on making cloud

systems more energy-efficient by developing more

energy-efficient radio access network technologies

and specifically the upfront ones like small and

femtocells.

Figure 3: Estimate for annual energy consumption broken

down into the various components of the wireless cloud

ecosystem, 2012 and 2015 (Lo and Hi scenarios).

In (Al Haddad et al., 2012), a new indicator is

introduced which enables us to calculate the

consumed CO2 emission per kWh and enlighten the

green effect of any technology based saved energy

amount. The kWh is converted to kg of carbon

saved. For instance, the conversion factor for the

United States is 0.62747 kg CO2 saved for each

kWh produced from a carbon free source.

The factor is based on the carbon emissions

generated by the current United States' power

stations per kWh generated. This factor includes

other greenhouse gasses such as methane and nitrous

oxide which are converted to their carbon dioxide

equivalents so the value is really kg CO2 eq. per

kWh. The CO2 consumption can be calculated as

shown in the following equation:

CO2Power



Watt



∗ Conversionfactor

(4)

5 ANALYSIS OF FEMTOCELL

DEPLOYMENT IN CELLULAR

NETWORKS

In heterogeneous networks, where high data rates

are desired, more dense deployment of femtocells is

seen as an enabling solution. They are deployed with

the macrocells in an overlay, overlapping or

disjointed area in cellular networks. With such

hyper-dense networks, the problem of interference

comes between the macro cells and small cells as

well as among the small cells themselves. The

interference between macrocell and femtocell, i.e.,

inter-tier interference, arises from the fact that

femtocells may utilize the spectrum already

allocated to the macrocell. Without proper

interference management, significant power is likely

to be wasted in order to maintain an acceptable user

performance.

Main challenges with femtocell Technology are

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the Coordination between macrocells and ad-hoc

femtocells, Interference mitigation with macrocells

and femtocell deployment in a power-aware and

green way. Further challenges to be considered with

femto technology:

Tx Power Management: the RF environment is

constantly changing and each femtocell needs to

adapt its transmit power as other cells are being

added, relocated or removed to maintain a

continuous coverage and avoid interference.

Location Uncertainty: the location of femtocell is

randomness and unpredictable, and as the owner

likes.

Configuration Variation: some femtocells

configuration parameters might be adjusted by the

owners for operation and performance. The degree

of uncertainty in the deployment increases if the

femtocells configuration could be set differently for

each femtocell.

Access and Security Control: OSG (Open

Subscriber Group) or CSG (Closed Subscriber

Group). Different access control mechanisms for

femtocells may result in different interference

environments much more complicated to control

than that of the conventional wireless cellular

networks.

Resource and Interference Management:

femtocells can operate in their own dedicated

channel or share a channel (co-channel) with the

existing network cells. Femtocells deployed in co-

channel manner as macro cells need to coordinate

with macro cells to determine the optimal resource

partitioning and maximize traffic offloading to

femtocells.

Mobility Management: femtocells need to discover

neighbors autonomously to facilitate UE handover.

Backhaul Management: bandwidth of customer

backhaul cannot be guaranteed. When femtocells

experience limitation in backhaul bandwidth, they

should prioritize user classes or transferred packets.

All in all, Introducing femtocells should not

significantly degrade the performance of other/prior

deployed networks, therefore all the above listed

challenges should be considered and solved.

6 INTERFERENCE

MANAGEMENT TECHNIQUES

FROM POWER CONTROL

PROSPECTIVE

It is crucial to mitigate the interference which arises

when femtocells are deployed in macrocell networks

and ensure that the spectral efficiency is better than

that of the macrocell only networks. Several

interference management schemes for cellular

networks with femtocells are presented.

 Optimization of Resource Allocation in case of

coexisting femtocell and macrocell network

(cognitive radio) like analyzed in (Femto Forum

Working Group, 2009); (Boudec, 2012); (Luo

and Yu, 2006) or by utilizing new features like

“range expansion” that allows a User Equipment

(UE) to be served by a cell with weaker received

power (3GPP R4-092042, 2009) (RP – 111369,

2011).

 Radio resource coordination by allocating

different resources between neighboring eNBs in

the time or frequency domains as shown in

(3GPP R4-093349, 2009).

 System/Design improvement by adding more

resources like MIMO design as shown in (Cui et

al., 2004).

 Dynamic Resource Management where new

techniques like “opportunistic small cells” are

introduced (Qualcomm, 2013), which

dynamically turns the femtocell “ON” or “OFF”

based on the need for capacity for instance

proximity of users or traffic status e.g. idle status,

to not only reduce interference but also lower

energy consumption.

 Power Control (PC) which is necessary to

mitigate the interference by manipulating the

transmission power settings.

In this chapter we will go through the existing PC-

related solutions only. There are Downlink and

Uplink Power Control techniques for Interference

Mitigation and Power Setting Tuning. In this section

we try to summarize the most recent and important

ones.

6.1 Uplink Power Control

In the uplink (UL), the interference from the outdoor

Home UE to the macro eNB becomes a serious

problem when the Home UE is located close to the

macro eNB. In this case, the transmit power from

Home UE has to be reduced in order to mitigate

such interference. On the other hand, the indoor

Home UE, which is close to its serving Home eNB

and far from the macro eNB, can increase transmit

power with a bit or even no interference to macro

eNBs. Therefore, it is necessary to apply the uplink

power control in femtocell networks.

The uplink power control for LTE as currently

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251

defined in 3GPP standards (3GPP TS 36.213, 2013)

is composed of open and closed loop components.

The open loop power control (OLPC) is responsible

for a rough setting of UE transmit power. It

compensates slow changes of pathloss (including

shadowing) in order to achieve a certain mean

received signal power for all users. The closed loop

power control (CLPC) is used for user specific

adjustments of the power settings considering such

factors as Modulation and Coding Scheme (MCS),

measurement errors and rapid changes in radio

conditions. It can be also used for further

optimization of general network performance, as e.g.

described in (Boussif, 2008); (Boussif, 2010). The

equation defined in 3GPP for setting transmit power

of Physical Uplink Shared Channel (PUSCH) is as

follows (dB scale):

P 

min

PMax,10log







P0αPL 

deltaMCS 



deltai





(5)

[Where PMax is the maximum allowed UE transmit

power, M is the number of Physical Resource

Blocks (PRB) scheduled for the given user in a time

slot, P0 is parameter related to target mean received

power (user or cell specific), α is pathloss

compensation factor (cell specific), PL is the

downlink pathloss measured by the UE

(3GPP TS

25.814, 2006), deltaMCS is a parameter depending on

the used MCS (user specific), and f(deltai) is a user

specific CLPC correction]. In this case the cell

specific parameters of the OLPC are considered (P0,

α) as they have the main impact on the inter-cell

interference.

If this simple power control method is applied in

the uplink, a too strong signal transmitted from the

outdoor Home UE possibly can cause interference to

nearby macro eNB(s). In order to deal with this

problem, the PL between Home UE and its nearest

neighbor macro eNB has to be estimated for

additional actions. Some well-known methods

developed for uplink power control are:

 Power Cap Based PC: the maximum

transmission power density (i.e., power cap) of the

HUE is restricted in order to avoid heavy

interference to macro eNB(s). The power cap of the

HUE is calculated as a function of the estimated PL

between HUE and its nearest neighbor macro eNB.

Then, the HUE is power-controlled based on the PL

from the HUE to its serving Home eNB, up to the

level of the power cap (3GPP TS 36.104, 2007).

 PL Difference based PC: with the knowledge of

the difference between the PL from the Home

UE to its serving Home eNB and its nearest

neighbor macro eNB, the Home eNB calculates

the power offset as a non-decreasing function of

the PL difference. Then, this offset value is sent

to the Home UE via a radio resource control

message to further adjust the uplink transmission

power. Based on these facts, the Home UE

transmit power can be adjusted accordingly

(3GPP TS 36.104, 2007).

 Adaptive Target Mean received po>Wer

(Adaptive P0): the proposed solution in (Jacek,

Pedersen, Szufarska and Strzyz, 2010) is to

define the OLPC parameter P0 in equation (5) in

a way that would reflect the distribution of

interference levels within macrocell, e.g. as a

function of pathloss towards closest macro-eNB:

P0  round



APo  BPoPLLA





(6)

[Where P0 is the calculated OLPC parameter for a

local area node, PLLA_WA is the downlink pathloss

to the closest wide area node. APo and BPo are

parameters of the function that can be e.g. operator

or vendor specific]. The algorithm introduces two

additional parameters (APo, BPo are the same for all

Home eNBs) but it allows full individual

configuration too. To achieve similar effect with the

basic OLPC procedure, each local cell would have to

be configured with an individual set of parameters.

 Link Budget Analysis: a link budget analysis is

provided which enables simple and accurate

performance insights in heterogeneous networks.

(Chandrasekhar, Andrews, Muharemovic, Shen,

and Gatherer, 2009),

a distributed utility-based

SINR adaptation at femtocells is proposed in

order to alleviate cross-tier interference at the

macrocell from co-channel femtocells. The

Foschini-Miljanic (FM) algorithm is a special

case of the adaptation. Each femtocell maximizes

their individual utility consisting of a SINR

based reward less an incurred cost (interference

to the macrocell). The radio link quality for a

cellular user is determined, given a set of N

transmitting femtocells with different SINR

targets. Achieving higher SINR targets in one

tier fundamentally constricts the highest SINRs

obtainable in the other tier.

6.2 Downlink Power Control

Several interference mitigation schemes using

femtocell BS power level setting in DL have been

investigated:

 Basic fixed Power Approach: it is based on a

preconfigured value which is common for all

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femtocell BSs regardless of the surrounding RF

conditions. Advantages of this scheme are its

simplicity and ease of implementation.

Disadvantages are its difficulty to adapt to the

surrounding RF conditions and likeliness to

cause large interference. If the fixed power level

is too low, the femtocell BSs located close to the

macrocell BS have poor coverage because the

interference from the macrocell BS is high. On

the other hand, if the fixed power level is too

high, the femtocell BSs located at edge of the

macrocell provide a large interference to the near

macrocell MSs because the interference from the

femtocell BSs to the macro MSs becomes high.

 Self-configuration based on Macrocell BS

Signal: self-configuration of transmit power

level based on the measured received signal level

from the macrocell BS was developed by

Claussen et al., (2008).

 Self-optimization Approach based on SINR: a

self-optimization of coverage in accordance with

the information on mobility events of passing

and indoor users is used. Li et al., (2009) used

downlink power control to achieve SINR for

both macrocell and femtocell users.

Guidelines on how to control UMTS Home NodeB

(HNB) and LTE Home eNodeB (Home eNB)

interference by transmit power level setting are

given in

(3GPP TR 25.967, 2012) (3GPP TR 36.921,

2012). However, the previous techniques have not

adequately accounted for the interference with

neighboring macrocell users and surrounding

conditions.

 RSRP Approach: the largest Reference Signal

Received Power (RSRP) corresponding to the

nearest macro eNB is used as one of the

parameters for tuning downlink power control

(3GPP R4-093557, 2009). As the RSRP

decreases, which means that the Home eNB is

located close to the edge of the macro cell, the

transmit power should be small in order to

mitigate the downlink interference to the macro

UE. If a Home eNB is close to a macro UE,

lower transmit power should be set to mitigate its

interference to the macro UE. With the

knowledge of the largest RSRP and power offset,

the Home eNB selects the transmit power of the

reference signal as the median values of the sum

of the largest RSRP and power offset, the lower

and the upper limit values of transmit power.

 Adaptive power level setting approach: two

adaptive power level setting schemes are

possible here as shown in (3GPP TR 36.814,

2010):

a) Adaptation based on DL Reception Power

from MBS:

This technique is based on downlink co-channel

reception power of the reference signal of the

strongest macrocell BS. The femtocell BS measures

the reception power at the initial configuration phase

or in operational phase and adaptively set the

transmit power level accordingly. This scheme

corresponds to the measurement based self-

configuration scheme given in (Morita, Matsunaga,

and Hamabe, 2010). The femtocell BS sets the

transmit power of the reference signal as:





MEDIANP



P

















(7)

[Where the function MEDIAN() means the returned

value is the median of all arguments. P



[dBm] is the

reception power of the reference signal from the

nearest macrocell BS measured at the femtocell BS

and is dependent on the path loss between the

nearest macrocell BS and the femtocell BS which

includes the penetration loss at the building wall.



[dB] is the predetermined fixed power offset

compensating for the indoor loss. P

__

and

__

[dB] are the upper and the lower limit value

of the transmit power. P

__

is needed to limit the

interference from the femtocell BS to the macrocell

MS. P

__

is also needed to guarantee a certain

minimum performance for femtocell even if the

surrounding macrocell cannot be detected].

A disadvantage of the schema is that it is not

enough for only fixed power offset to compensate

for the indoor path loss. Each building has different

properties, such as the penetration loss at external

walls and P



should be tuned accordingly.

b) Adaptation based on DL Reception Power from

macrocell BS and UL Reception Power from

macrocell MS:

This technique is based on downlink (DL) co-

channel reception power of the reference signal of

the strongest macrocell BS and uplink (UL)

reception power from neighboring macrocell MSs.

The femtocell BS adaptively measures the DL and

UL reception power at self-configuration phase and

then optimizes the transmit power during the self-

optimization phase. The femtocell BS sets the

transmit power of the reference signal as follows:



MEDIANP



P







∗L













(8)

[Where P



, P

__

, and P

__

have the same

meaning as (7). P

__

[dB] is a predetermined

EvaluationofFemtocellTechnologyChallengesandItsPowerControlMethodologiesforGreenHeterogeneousNetworks

253

power offset value compensating for the indoor path

loss excluding the penetration loss.

is an

adjustable positive factor and can be determined by

the priority of the femtocell BS operation. L



[dB] is

the penetration loss which assumed to be ideally

estimated]. A macrocell MS is assumed to be located

in close proximity to a femtocell BS. This means the

distance from the macrocell BS to the macrocell MS

is nearly the same as that from the macrocell BS to

the femtocell BS. The penetration loss L



can be

calculated as follows:





∗P





P





L





(9)

[Where P

_



[dBm] is the UL transmit power

virtually calculated by the femtocell BS. P

_



[dBm]

is the UL reception power from the macrocell MS

measured at the femtocell BS. L



[dB] is open - air

propagation loss between the macrocell MS and the

femtocell BS excluding the penetration loss]. L



is a

predetermined value and is assumed in advance so

that the distance between the macrocell MS and the

femtocell BS can be minimized under the conditions

in which the interference from the macrocell MS to

the femtocell BS is tolerable. When the path loss

between the macrocell MS and the femtocell BS

excluding the penetration loss is within La, the

penetration loss in equation (9) is estimated to be

smaller than its real value and the transmit power is

suppressed. When the path loss is outside L



, the

penetration loss is estimated to larger than the real

value and the transmit power is released. This power

setting technique can resolve the problem of the last

power setting schema.

 Auto-tuning of DL Power of Femtocells

Adaptive to Various Interference Conditions:

the power offset in previous introduced

technique has not been adequately optimized for

various interference conditions. In (Kan et al.,

2011), the proposed scheme automatically tunes

the power offset so that the femtocell throughput

can increase while maintaining the macrocell

throughput based on macrocell mobile stations’

interference detection reports. In comparison to

the last technique where the 

__

is fixed,

various interference conditions such as size of

buildings where femtocell mobile stations exist

and distance to a street where macro MSs exist

are not sufficiently considered. The macrocell or

femtocell throughput may degrade if the initial

value is too large and too small compared with

the conditions.

Therefore, (Kan et al., 2011) introduces different

auto-tuning schemes using individual offset where

the P

__

is tuned individually per femto BS or

using common offset where the P

__

is tuned

commonly among femto BSs in a macrocell with

per-femtocell or per-macrocell measurement,

respectively. This approach uses a stepwise tuning

of P

__

based on Interference Detection Ratio

(IDR1) indicator, which is the ratio of the number of

interference detection reports to the number of

macro MSs that receive the measurement control

message from the serving macro BS.

7 CONCLUSIONS

With the steadily increasing demand for mobile

traffic, it is important that the telecom networks are

modernized with all the capacity, quality and

coverage extension technologies available and

especially the energy efficient ones such as

femtocell technology. In 3G networks, small cells

are viewed as an offload technique whereas from 4G

networks onwards, the principal of heterogeneous

networks is introduced where the network is based

on layers of small and large cells together. Whether

it’s a low indoor coverage, bad network performance

in rural areas, required capacity increase and high

data rates or qualified coverage guarantee in hard-to-

cover areas, a cost-efficient way to address these

issues is femtocell solutions.

There are no distinct standards to define the

physical power transmission of a femtocell but only

recommendations. This survey work provides an

overview of the power control and saving

methodologies with regard to femtocell technology.

It also discusses its challenges and different potential

ideas for improvements. The femtocell technology is

still young and fertile research is still required here.

In our future research work, we will be further

identifying the ability for femtocell technology to

help with the green initiatives. For instance, future

network releases need to support the coordination

among femtocells and not only between macro and

femto cells and take into account conditions of both

surrounding environment and networks. In addition,

other topics will be further investigated like

enhancing existing power control methodologies,

powering down small cells based on traffic situation,

improvements on cell phone battery life and

throttling small cell power down based on cell type

and usage.

Future innovations and further research are

strongly required to overcome the challenges

coming with this immature technology.

SMARTGREENS2014-3rdInternationalConferenceonSmartGridsandGreenITSystems

254

ACKNOWLEDGEMENTS

To my university advisor for his great efforts of

supervising and leading us, to accomplish this work.

To every person who gave us something to light our

pathway, we thank them for their support,

encouragement and believing in us.

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