Study of Indoor Path Loss Computational Models for Femtocell Based Mobile Network

Abstract

Path loss minimization in next generation mobile network is a challenging research area. The signal transmitted by a base station degrades due to various obstacles in the environment. The received signal level at the mobile station is less than the transmitted signal level of the base station. This loss in the signal level is referred as path loss in mobile network. In this paper different path loss models are discussed for indoor environment covered by femtocell. It is assumed that the mobile users in that region exclusively access the services of femtocell. As only indoor area is considered, non-line of sight propagation is examined. Signal-to-interference-plus-noise-ratio for a femtocell base station is calculated. The performance of the path loss models are analyzed using vector signal generator and vector signal analyzer. A comparative analysis is carried out between the models. Based on the comparative analysis, a case study is performed to demonstrate how an appropriate path loss model will be selected depending on the frequency range, building type, walls and floors.

Full text

Study of Indoor Path Loss Computational Models
for Femtocell Based Mobile Network
Priti Deb
1
•Anwesha Mukherjee
1
•Debashis De
1
Springer Science+Business Media New York 2017
Abstract Path loss minimization in next generation mobile network is a challenging
research area. The signal transmitted by a base station degrades due to various obstacles in
the environment. The received signal level at the mobile station is less than the transmitted
signal level of the base station. This loss in the signal level is referred as path loss in mobile
network. In this paper different path loss models are discussed for indoor environment
covered by femtocell. It is assumed that the mobile users in that region exclusively access
the services of femtocell. As only indoor area is considered, non-line of sight propagation
is examined. Signal-to-interference-plus-noise-ratio for a femtocell base station is calcu-
lated. The performance of the path loss models are analyzed using vector signal generator
and vector signal analyzer. A comparative analysis is carried out between the models.
Based on the comparative analysis, a case study is performed to demonstrate how an
appropriate path loss model will be selected depending on the frequency range, building
type, walls and floors.
Keywords Femtocell Path loss Signal-to-interference-plus-noise-ratio Non-line of
sight propagation Mobile network
1 Introduction
The advancement of mobile network has explosively increased the number of mobile
subscribers. To meet the need of high speed communications and better signal strength at
indoor as well as outdoor region, Fourth Generation (4G) mobile network has been
developed [1–5]. The 4G mobile network is a totally IP-based system. It can provide a data
&Debashis De
dr.debashis.de@gmail.com
1
Department of Computer Science and Engineering, West Bengal University of Technology,
BF-142, Sector -I, Salt Lake City, Kolkata, West Bengal 700064, India
123
Wireless Pers Commun
DOI 10.1007/s11277-017-3983-z

rate of 1 Gbps and 100 Mbps respectively in indoor and outdoor locations. To offer 4G
services, Long Term Evolution-Advanced (LTE-A) network has come [6–10]. In LTE-A
network femtocell plays an important role [11–15]. Femtocell is a low power cellular base
station that has a coverage area of 10–20 m [16–20]. In LTE-A network macrocell base
stations are used along with femtocell base stations. To offer good signal level at indoor
area, femtocells are allocated inside the macrocell coverage area (1–20 km). LTE-A net-
work is most likely to be applicable for urban area where good quality of service (QoS) is
required [21]. Indoor cellular usage accounts for 50% of all voice calls and 70% of data
traffic [22–25]. But it mostly suffers from poor reception of signal due to low signal
penetration through walls and attenuation which may lead to total loss of the signal [1].
Macrocell base station (MBS) is unable to tackle the indoor coverage problem because of
its large coverage [26]. The distance between the transmitter and the receiver has to be kept
relatively close to enhance the quality link and data rate. As femtocell has small coverage
area, the distance between the femtocell BS and the mobile device is small. Femtocell not
only improves the coverage, but also balances the load of the macrocell [27–30]. Femtocell
base station (FBS) is usually installed in home or small office [31–35]. FBSs operate in
licensed spectrum with low power transmission [36–40].
The signal transmitted by a base station degrades due to the presence of obstacles like
walls, floors, etc. As a result, the power level of the signal received at the mobile station is
less than the power level of the signal transmitted by the base station. This loss is called
path loss which is mathematically expressed as,
PL ¼Ptrans Precv ð1Þ
where P
trans
and P
recv
are the power levels (in dBm) of the transmitted and received signal
respectively. Path loss models play an important role in studying the effects of deployment
of base stations in an area. Base stations should be allocated in such a way that proper
coverage can be given by reducing the path loss between the transmitter which is a base
station and the receiver which is a mobile device. By minimizing path loss better signaling
can be provided to the receiver. It helps in estimating the interference between the cells. In
a macro-femtocell network, the interference occurs between a femtocell and a macrocell as
well as between two femtocells [41–46].
In the present work only the indoor path loss models are studied and it is assumed that
indoor users exclusively use the services of the femtocell. Line of sight (LOS) and non-line
of sight (NLOS) both have been considered [47–50]. Here multiple floor penetration and
wall penetration are considered [36,51–54]. The path loss, received power and signal-to-
interference-plus-noise-ratio (SINR) [55–59] are determined to analyze the performance of
the path loss models.
In indoor region FBSs are used to improve the QoS and Quality of Experience (QoE) for
users. But to cover a whole building multiple FBSs are required. As a result interference is
increased. Moreover the quality of signal degrades due to floors and walls. Different
buildings have different constructions. Therefore a single path loss model is not suitable for
all the scenarios. A wrong selection of indoor path loss model affects the quality of signal
which in turn degrades the QoS and QoE. Our aim is to select an appropriate path loss
model for indoor region based on the environmental parameters. The contributions of this
paper are:
1. Four types of indoor path loss models are discussed and compared.
2. Performance of each path loss model is evaluated using experimental results.
3. The models are compared using simulation analysis.
P. Deb et al.
123

4. From the comparative analysis, a case study is performed to show how an appropriate
model can be selected for a particular building on the basis of frequency range,
building structure, floors and walls.
This paper is organized as: Sect. 2describes the related works, Sect. 3discusses on the
indoor path loss models, Sect. 4presents the received power and SINR calculation, Sect. 5
analyzes the performance of the path loss models with a comparative study, future chal-
lenges are discussed in Sect. 6, and finally Sect. 7concludes the paper.
2 Related Works
The use of FBS has benefited the user in terms of better signal strength, throughput and low
power. On the other hand operators are also benefited with increased network capacity and
spectral efficiency [60]. To get high data rates, FBSs together with macrocells are used
widely. The fundamental challenge for such a two-tier macro-femtocell network is inter-
ference mitigation. In [61] a six sector macrocell layout is considered and methods are
adopted for reducing the co-tier and cross-tier interference enhancing the system
throughput and outage probability. Interference can also be managed by allocating dif-
ferent frequency bands using time slots [62]. In such a system indoor attenuation is sep-
arated from outdoor environment using outdoor-indoor propagation models [63]. Very
little attention is given for indoor-outdoor propagation models in the frequency range of
1.96–2 GHz. In this paper different path loss models for indoor environment are studied
considering multiple floor and wall penetration losses.
3 Indoor Path Loss Models for Femtocell Network
Path loss models are broadly classified as:
•Empirical models
•Semi-empirical models
Empirical models are mainly based on the analysis of statistical measurements while semi-
empirical models are based on theory and real case data. It also introduces deterministic
parts which can be added to the model. For higher coverage inside the buildings, a more
complex multipath structure compared to outdoor propagation is to be developed with
small cells. This is due to the building structure, the room layout and the material used for
constructing the building. In this literature the following propagation models are studied:
COST 231, WINNER II, Multi-Wall-and-Floor (MWF) and ITU-R P Model.
3.1 COST 231 Model
In 1999, COST 231 model is introduced by European Co-operative for Scientific and
Technical research (EUROCOST). At first for 900 and 1800 MHz frequencies experiments
have been conducted. After that this model has been scaled to other frequencies. The path
loss in case of COST 231 model considering number of wall and floor is given as [64],
Study of Indoor Path Loss Computational Models for…
123

PLCOST ¼lFSL þlcþX
J
i¼1
kwilwi þk
kfþ2
kfþ1B
hi
flfð2Þ
where l
FSL
is the free space loss, l
c
is the constant loss determined from the measurements,
k
wi
and k
f
are the number of traversed walls and floors respectively, l
wi
and l
f
are the losses
of penetrated walls and floors respectively, Bis an empirical parameter, Jis the number of
wall types, for light wall l
wi
is 3.4 dB, and for heavy wall l
wi
is 6.9 dB. Although different
number and categories of walls are considered, different floor types are not considered in
this model, only the number of floor is considered in the equation. Hence this model is
suitable if the considered indoor scenario contains different number and types of walls and
different number and same type of floor.
3.2 WINNER II Model
The WINNER II (Wireless World Initiative New Radio phase II) channel model has been
proposed for different scenarios of radio propagation such as indoor propagation, indoor to
outdoor propagation, outdoor to indoor propagation and outdoor propagation scenarios by
European Union IST funded project in 2007 [65]. This model was firstly applied at 2 and
5 GHz. After that it is extended over a frequency range 2–6 GHz.
The path loss for this model in LOS scenario is given as,
PLWINNERII LOS ¼18:7 logðDÞþ46:8þ20 log Fc
=
5
 ð3Þ
The path loss for this model in NLOS scenario is given as,
PLWINNERII NLOS ¼20 logðDÞþ46:4þ20 log Fc
=
5

þxð4Þ
where x=5(N
w
-1) in case of light wall and x=12(N
w
-1) in case of heavy wall, F
c
is
the frequency in GHz, Dis the distance between the access point and the mobile device in
meter (m), and N
w
is the number of wall. The equation shows that the relation of penetrated
walls and path loss is constant and linear. Equation (4) shows that only number of wall is
considered in this case. Therefore this is suitable for the indoor scenario containing dif-
ferent number of walls of same type.
3.3 Multi-wall-and-Floor Model
This model has been proposed in 2007 based on ray tracing at 5.2 GHz and verified at
different frequencies [66]. The path loss for this model considering the number and cat-
egories of wall and floor is expressed as,
PLMWF ¼l0þ10nlogðDÞþX
J
i¼1X
kwi
j¼1
lwij þX
X
m¼1X
kfm
j¼1
lfmj ð5Þ
where l
wij
and l
fmj
denote the attenuation for iand jth wall traversed and the attenuation for
mand jth floor traversed respectively, k
wi
and k
fm
denote the number of traversed wall of
type iand floor of type mrespectively, Jand Xdenotes the number of wall and floor
P. Deb et al.
123

categories, for light wall l
wij
is 3 dB, for heavy wall l
wij
is 10 dB. In this model a nonlinear
relation is shown between the number of wall or floor and the penetration loss. This model
is suitable for the indoor scenario containing different number of wall of different type and
different number of floor of different type.
3.4 ITU-R P Model
The ITU-R P (Radio communication Sector of International Telecommunication Union, P
series) model has been proposed in 2012 for a wide range of frequencies, 900 MHz to
100 GHz [67]. The path loss for this model considering the number of floor is calculated
as,
PLITUR ¼20 logðFcÞþNlogðDÞþLfðnfÞ28 ð6Þ
where Nis the distance power loss coefficient and Dis the separation distance between the
access point and the mobile device in meters (D[1 m), n
f
denotes the number of floors
between the access point and the mobile device, F
c
signifies the frequency in MHz, L
f
is the
floor penetration loss factor in dB, for residential building Nis 28, L
f
=4n
f
, for office
building Nis 30, L
f
=15 ?4(n
f
-1). This model considers only the number of floor in
between. Therefore this model is suitable for the indoor scenario containing different
number of floors of same type.
Figure 1pictorially describes the evolution of the discussed path loss models along with
their features. It is observed from Fig. 1a that COST 231 and MWF models have been
developed from One-slope model [66]. The path loss in case of One-slope model is given
as,
PLoneslope ¼Lþ10nlogðDÞð7Þ
where Dis the distance between transmitter and receiver in meter and Lis the path loss at a
distance of 1 m. WINNER II has been developed from WINNER model. According to
WINNER model, the path loss is given as,
PLWINNER ¼alog10ðDÞþbþclog10 Fc
=
5

þxð8Þ
where Dis the distance between transmitter and receiver, F
c
is the frequency in GHz, ais
path loss exponent, cis the frequency dependence for the path loss and bdenotes the
intercept.
Figure 2shows four indoor scenarios. The applicable path loss models for these sce-
narios are pictorially illustrated in Fig. 2. The path loss for light wall, heavy wall, multi-
wall-and-floor and building are presented in Fig. 2a–d respectively.
4 Received Power and SINR in Femtocell Network
Poor coverage in indoor area can be overcome by using femtocell. The distance between
the transmitter and the receiver is reduced for better signal level.
The transmission power for a FBS is calculated as [38],
Study of Indoor Path Loss Computational Models for…
123

Pt¼Pr4p
ð3ffiffiffi
3
p=2ÞDrGFð9Þ
where P
r
is the received power by the mobile device under its coverage, D
r
is the nor-
malized radiation pattern and G
F
is the FBS antenna gain. In a network higher data rate can
Fig. 1 Evolution and features of different path loss models. aEvolution of different path loss models.
bFeatures of different path loss models
P. Deb et al.
123

be achieved by increasing the SINR. The SINR is a function of transmitted power from the
desired base station, transmitted power from the interfering base station, shadowing, fading
and path losses [52].
The SINR for a FBS is calculated as,
SINR ¼Pt
PfmPtþWð10Þ
where P
t
is the transmitted power of the FBS, f
m
is the number of adjacent FBSs of the
considered FBS and Wis the product of the white noise spectral density and the subcarrier
spacing.
Path loss in COST 231 Model:
2
1
1
kf
kf
JB
f
COST FSL c wi wi f
i
PL l l k l k l
+
⎡⎤
−
⎢⎥
+
⎣⎦
=
=++ +
∑
where lwi=3.4 dB.
Path loss in WINNER II NLOS Model:
_
20log( ) 46.4 20log( )
5
c
WINNERII NLOS
F
PL D x=++ +
where x=5(Nw-1), Nwis the number of walls.
Path loss in COST 231 Model:
2
1
1
kf
kf
JB
f
COST FSL c wi wi f
i
PL l l k l k l
+
⎡⎤
−
⎢⎥
+
⎣⎦
=
=++ +
∑
where lwi=6.9 dB.
Path loss in WINNER II NLOS Model:
20log( ) 46.4 20 log( )
5
c
WINNERII
F
PL D x=++ +
where x=12(Nw-1), Nwis the number of walls.
Path loss in MWF model:
0
11 11
10 log( )
fm
wi
k
k
JX
MWF wij fmj
ij mj
PL l n D l l
== ==
=+ + +
∑∑ ∑∑
For light wall: lwij=3 dB, For heavy wall: lwij=10 dB.
Path loss in ITU-R P model:
20log( ) log( ) ( ) 28
ITUR c f f
PL F N D L n=++−
For residential building: N=28, Lf=4nf,
For office building: N=30, Lf=15+4(nf-1),
where nfis the number of floors.
(a) (b)
(c) (d)
Fig. 2 Path loss in indoor region considering walls and floors. aPath loss for light wall. bPath loss for
heavy wall. cPath loss for multi-wall-and-floor. dPath loss for building
Study of Indoor Path Loss Computational Models for…
123

5 Comparison Between Path Loss Models
A comparative analysis between the path loss models in indoor region is performed with
centre frequency of 2 GHz. In our work it is considered that the indoor region is covered by
FBS, and signal from a FBS can penetrate maximum of 2 floors with a distance of 20 m.
Frequency Response and Frame Summary for COST 231 Model
Path loss for COST 231 model:
2
1
1
f
f
kB
Jk
COST FSL c wi wi f f
i
PL l l k l k l
⎡⎤
+−
⎢⎥
+
⎢⎥
⎣⎦
=
=++ +
∑
.
For light wall: lwi=3.4 dB, For heavy wall: lwi=6.9 dB.
COST 231 considers different number of walls of various types and different number of floors of same type.
Frequency Response of LTE-A signal for COST 231 model:
(a)
(b)
(c)
Fig. 4 a Frequency response of the transmitted LTE-A signal. As observed from (a), the signal level ranges
from -5 to 5 dB. The resolution bandwidth (Res BW) is 15 kHz. The time length is 1 Symbol. b,
cFrequency response of the received LTE-A signal for light wall and heavy wall after path loss respectively.
As observed from (b,c), the frequency response of the received signal has been deviated from that of the
transmitted signal due to the path loss
Fig. 3 LTE-A spectrum observed from VSA. aConstellation diagram of LTE-A spectrum. bLTE-A
spectrum
P. Deb et al.
123

Two types of walls are considered: (1) light wall made of glass, plastic etc., and (2) heavy
wall made of concrete, brick. The COST 231, MWF, WINNER II models are compared for
this scenario. The ITU-R P model does not explicitly consider wall penetration loss. This
model is compared on two types of building: residence and office, since the structure of a
residential building differs from an office building.
5.1 Experimental Analysis of Path Loss Models
Agilent EXG Vector Signal Generator (VSG) N5172B and EXA Vector Signal Analyzer
(VSA) 9010A have been used for experimental purpose. VSA 9010A analyses a signal
within the frequency range of 10 Hz to 13.6 GHz. VSG N5172B can produce a signal of
power level -144 to 19 dBm and frequency range of 9 kHz to 6 GHz. MATLABR2010b
has been used for simulation purpose.
Figure 3shows the LTE-A spectrum with constellation diagram. This spectrum is
analyzed using VSA in the Wireless laboratory of West Bengal University of Technology.
Constellation diagram shows a modulated signal in a complex plane as a two-dimen-
sional scatter diagram presenting the Cartesian coordinates. The constellation diagram and
spectrum of the LTE-A signal are shown in Fig. 3a, b respectively. As observed from
Fig. 3b, the center frequency is set to 2 GHz.
5.1.1 COST 231 Model
If COST 231 model is used, the path loss is determined using Eq. (2). The frequency
response of the transmitted LTE-A signal and the received LTE-A signal after path loss are
presented in Fig. 4. Frequency response measures the magnitude and phase of the output
Frequency Response and Frame Summary for COST 231 Model
Path loss for COST 231 model:
2
1
1
f
f
kB
Jk
COST FSL c wi wi f f
i
PL l l k l k l
⎡⎤
+−
⎢⎥
+
⎢⎥
⎣⎦
=
=++ +
∑
.
For light wall: lwi=3.4 dB, For heavy wall: lwi=6.9 dB.
COST 231 considers different number of walls of various types and different number of floors of same type.
Frame Summary of LTE-A signal for COST 231 model:
(a)
(b)
(c)
Fig. 5 a Frame summary of the transmitted LTE-A signal. In the frame summary the channels, Error
Vector Magnitude (EVM), power, modulation method and number of resource block (RB) are displayed. b,
cFrame summary of received LTE-A signal for light wall and heavy wall after path loss respectively. b,
cFrame summary of the received signal has been changed from the transmitted signal
Study of Indoor Path Loss Computational Models for…
123

with respect to the input. The frame summaries of the transmitted LTE-A signal and the
received LTE-A signal are shown in Fig. 5.
5.1.2 WINNER II Model
If WINNER II model is used, the path loss is determined using Eqs. (3) and (4). The
frequency response of the transmitted LTE-A signal and the received LTE-A signal after
path loss are presented in Figs. 6and 7. The frame summaries of the transmitted LTE-A
signal and the received LTE-A signal are shown in Figs. 8and 9.
5.1.3 MWF Model
If MWF model is used, the path loss is determined using Eq. (5). The frequency response
of the transmitted LTE-A signal and the received LTE-A signal after path loss are pre-
sented in Fig. 10. The frame summaries of the transmitted LTE-A signal and the received
LTE-A signal are shown in Fig. 11.
5.1.4 ITU-R P Model
If ITU-R P model is used, the path loss is determined using Eq. (6). The frequency
response of the transmitted LTE-A signal and the received LTE-A signal are presented in
Fig. 12. The frame summaries of the transmitted LTE-A signal and the received LTE-A
signal are shown in Fig. 13.
Frequency Response and Frame Summary for WINNER II Model
Path loss for WINNER II model:
LOS:
_18.7 log( ) 46.8 20 log( )
5
c
WINNERII LOS
F
PL D=++
.
NLOS:
_
20log( ) 46.4 20 log( )
5
c
WINNERII NLOS
F
PL D x=++ +
.
For light wall: x=5(Nw-1), For heavy wall: x=12(Nw-1), where Nwis the number of walls.
WINNER II NLOS considers different number of walls only.
Frequency Response of LTE-A signal for WINNER II LOS model:
(a)
(b)
Fig. 6 a Frequency response of the transmitted LTE-A signal. As observed from (a) the signal level ranges
from -5 to 5 dB. The Res BW is 15 kHz. The time length is 1 Symbol. bFrequency response of the
received LTE-A signal after path loss. It is observed from Fig. 7b that the frequency response of the
received signal has been deviated from that of the transmitted signal due to the path loss
P. Deb et al.
123

Frequency Response and Frame Summary for WINNER II Model
Path loss for WINNER II model:
LOS:
_18.7 log( ) 46.8 20 log( )
5
c
WINNERII LOS
F
PL D=++
.
NLOS:
_
20log( ) 46.4 20 log( )
5
c
WINNERII NLOS
F
PL D x=++ +
.
For light wall: x=5(Nw-1), For heavy wall: x=12(Nw-1), where Nwis the number of walls.
WINNER II NLOS considers different number of walls only.
Frequenc
y
Response of LTE-A si
g
nal for WINNER II NLOS model:
(a)
(b)
(c)
Fig. 7 a Frequency response of the transmitted LTE-A signal. As observed from (a) the signal level ranges
from -5 to 5 dB. The Res BW is 15 kHz. The time length is 1 Symbol. b,cFrequency response of the
received LTE-A signal for light wall and heavy wall after path loss respectively. As observed from (b) and
(c), the frequency response of the received signal has been deviated from that of the transmitted signal due to
the path loss
Frame Summary of LTE-A signal for WINNER II LOS model:
(a)
(b)
Fig. 8 a Frame summary of the transmitted LTE-A signal. In the frame summary the channels, EVM,
power, modulation method and number of RB are displayed. bFrame summary of the received LTE-A
signal after path loss. bDemonstrates that the frame summary of the received signal has been changed from
the transmitted signal
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Frame Summar
y
of LTE-A si
g
nal for WINNER II NLOS model:
(a)
(b)
(c)
Fig. 9 a Frame summary of THE transmitted LTE-A signal. In the frame summary the channels, EVM,
power, modulation method and number of RB are displayed. b,cFrame summary of the received LTE-A
signal for light wall and heavy wall after path loss respectively. b,cFrame summary of the received signal
has been changed from the transmitted signal
Frequency Response and Frame Summary for MWF Model
Path loss for MWF model:
0
11 11
10 log( )
fm
wi
k
k
JX
MWF wij fmj
ij mj
PL l n D l l
== ==
=+ + +
∑∑ ∑∑
.
For light wall: lwij=3 dB, For heavy wall: lwij=10 dB.
MWF considers different number of walls of different types and different number of floors of different types.
Frequency Response of LTE-A signal for MWF model:
(a)
(b)
(c)
Fig. 10 a Frequency response of the transmitted LTE-A signal. As observed from (a) the signal level
ranges from -5 to 5 dB. The Res BW is 15 kHz. The time length is 1 Symbol. b,cFrequency response of
the received LTE-A signal for light wall and heavy wall after path loss respectively. As observed from (b,c),
the frequency response of the received signal has been deviated from that of the transmitted signal due to the
path loss
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Frame Summary of LTE-A signal for MWF model:
Frequency Response and Frame Summary for MWF Model
Path loss for MWF model:
0
11 11
10 log( )
fm
wi
k
k
JX
MWF wij fmj
ij mj
PL l n D l l
== ==
=+ + +
∑∑ ∑∑
.
For light wall: lwij=3 dB, For heavy wall: lwij=10 dB.
MWF considers different number of walls of different types and different number of floors of different types.
(a)
(b)
(c)
Fig. 11 a Frame summary of the transmitted LTE-A signal. In the frame summary the channels, EVM,
power, modulation method and number of RB are displayed. b,cFrame summary of the received LTE-A
signal for light wall and heavy wall after path loss respectively. b,cFrame summary of the received signal
has been changed from the transmitted signal
Frequency Response and Frame Summary for ITU-R P Model
Path loss for ITU-R P model:
20log( ) log( ) ( ) 28
ITUR c f f
PL F N D L n=++−
.
For residential building: N=28, Lf=4nf,For office building: N=30, Lf=15+4(nf-1),
where nfis the number of floor.
This model considers different types of building: office and residence. This model considers different number of
floors. Wall loss is not explicitly considered in this case.
Frequency Response of LTE-A signal for ITU-R P model:
(a)
(b)
(c)
Fig. 12 a Frequency response of the transmitted LTE-A signal. As observed from (a) the signal level
ranges from -5 to 5 dB. The Res BW is 15 kHz. The time length is 1 Symbol. b,cFrequency response of
the received LTE-A signal for residential and official construction after path loss respectively. b,
cFrequency response of the received signal has been deviated from that of the transmitted signal due to the
path loss
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The experimental results demonstrate that the frequency response and frame summary
of the received signal have been deviated from the transmitted signal due to path loss.
5.2 Parameter Values
The values of the parameters assumed in simulation are presented in Table 1.
5.3 Comparative Analysis of Path Loss Models Based on Simulation
Figure 14 presents the path losses calculated for light walls and heavy walls using COST
231, MWF and WINNER II NLOS models. As different number of wall and floor are
considered, path loss in WINNER II NLOS model is only measured for comparison.
Figures 14 and 15 show that the MWF model estimates the highest path loss whereas the
WINNER II NLOS model offers lowest path loss. This is because the MWF model con-
siders different types of walls as well as floors for which the loss factor varies.
Figure 16 depicts the path loss for the ITU-R P model which does not consider the wall
loss explicitly. Hence the comparison is made on two different type of building: residential
and office. ITU-R P considers different number of floor.
As an office building contains more number of floors than a residential building, the
path loss is higher for official construction. ITU-R P model is mainly useful if the wall loss
is not considerable and the path loss is to be calculated based on the building structure and
the number of floor.
Frame Summary of LTE-A signal for ITU-R P model:
Frequency Response and Frame Summary for ITU-R P Model
Path loss for ITU-R P model:
20log( ) log( ) ( ) 28
ITUR c f f
PL F N D L n=++−
.
For residential building: N=28, Lf=4nf,For office building: N=30, Lf=15+4(nf-1),
where nfis the number of floor.
This model considers different types of building: office and residence. This model considers different number of
floors. Wall loss is not explicitly considered in this case.
(a)
(b)
(c)
Fig. 13 a Frame summary of the transmitted LTE-A signal. In the frame summary the channels, EVM,
power, modulation method and number of RB are displayed. b,cFrame summary of the received LTE-A
signal for residential and official construction after path loss respectively. b,cFrame summary of the
received signal has been changed from the transmitted signal
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5.4 SINR
Figure 17 shows the SINR for a femtocell calculated using Eq. (10). The received power
ranges from 0.35 to 1 mW, the normalized radiation pattern is considered within 0.5 and 1,
Table 1 Parameter values con-
sidered in the path loss models Path loss model Parameter Constants
Wall based path loss model
COST 231 [64]B0.46
l
c
37 dB
l
w1
(light wall) 3.4 dB
l
w2
(heavy wall) 6.9 dB
l
f
18.3 dB
l
FSL
20log
10
(d)?20log
10
(f
c
)
WINNER II [65]x
1
(Light Wall) 5(N
w
-1)
x
2
(Heavy wall) 12(N
w
-1)
F
c
2000 MHz
D2–15 m
MWF [66]n2.03–1.96
l
w1
(light wall) 3.0 dB
l
w2
(heavy wall) 10 dB
l
f1
19 dB
D2–15 m
Building type based path loss model
ITU-R P [67]N
o
(office) 30
N
r
(residence) 28
D2–15 m
L
fr
(residence) 4n
f
L
fo
(office) 15 ?(4n
f
-1)
F
c
2000 MHz
Fig. 14 Path loss for light wall
Study of Indoor Path Loss Computational Models for…
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the antenna gain is assumed as 2 dBi. We have considered the interference between
femtocells. If the number of adjacent femtocell increases, the probability of interference
also increases. As a result the SINR is reduced. This is pictorially illustrated in Fig. 17.
Figure 18 shows the average noise level of the signal transmitted by a FBS.
Fig. 15 Path loss for heavy Wall
Fig. 16 Path loss for home and
residence using ITU-R P model
Fig. 17 Number of adjacent
femtocell versus SINR of a FBS
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As observed from Fig. 18, the noise level of the signal is -137.47 dBm/Hz. The ref-
erence level of the signal is set to 0.25 dBm. The centre frequency is set to 2.00185 GHz.
The Res BW and video bandwidth (VBW) are set to 560 and 56 kHz respectively.
5.5 Comparison Between Path Loss Models
Table 2presents a comparative analysis between the path loss models COST 231, MWF,
WINNER II and ITU-R P. From Table 2it is observed MWF not only considers different
types of walls but also different categories and number of floors to calculate the path loss.
COST 231 considers different type and number of wall but different number of floor of
uniform type in calculating path loss. But in WINNER II the path loss is calculated based
on the number of wall. In WINNER II the type of wall and number of floor are not
considered to calculate the path loss. As observed from Table 2, the path loss is less in case
of the light wall than the heavy wall. In ITU-R P model the type of building is considered
which is not considered in the other models. ITU-R P calculates the path loss based on
building type and number of floor; number and type of wall is not considered in this case as
wall loss is not explicitly considered in ITU-R P. As demonstrated in Table 2, the path loss
is less in case of residential building than office. This is because the number of floor is
more in case of an office building. From the comparative analysis it is observed that, if
difference types of buildings exist with different number of floors and wall loss is not
considerable, then ITU-R P model is more applicable. If different number of walls and
Fig. 18 Noise level of the signal transmitted by a FBS
Study of Indoor Path Loss Computational Models for…
123

Table 2 Comparison Table between path loss models for femtocell
Path loss model Formula No. of wall considered No. of floor considered Path loss
COST 231
PLCOST ¼lFSL þlcþPJ
i¼1kwilwi þk
kfþ2
kfþ1B
hi
flf
5 2 Light wall Heavy wall
115.17 dB 136.61 dB
WINNER II NLOS PLWINNERII ¼20 logðDÞþ46:4þ20 log Fc
=
5

þx5 2 Light wall Heavy wall
94.50 dB 111.30 dB
MWF PLMWF ¼l0þ10nlogðDÞþPJ
i¼1Pkwi
j¼1lwij þPX
m¼1Pkfm
j¼1lfmj 5 2 Light wall Heavy wall
128.21 dB 148.77 dB
ITU-R P PLITUR ¼20 logðFcÞþNlogðDÞþLfðnfÞ28 5 2 Residence Office
65.40 dB 81.93 dB
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floors exists and the type of wall as well as floor differs, then MWF is more applicable.
Otherwise if the indoor area contains different number and type of walls and different
number of floors of same type, then COST 231 is suitable. Otherwise if the indoor area
contains different number of walls of same type, then WINNER II is applicable. From the
perspective of frequency range, WINNER II is applicable for 2–6 GHz of frequency but
ITU-R P works in 900 MHz–100 GHz frequency band. Thus ITU-R P is applicable for
wide range of frequencies. Therefore from the comparative analysis it is illustrated that
depending on the frequency range, type of building, type of walls and floors it is to be
decided which model can be used to measure the path loss.
Table 3 Selection of appropriate path loss model in considered cases
Case
no.
Case scenario Selected path loss
model using proposed
scheme
Path loss models
used in
comparison
Path loss value using
selected model
(approx.) (dB)
1 Residential building
A number of floors of
same type
Wall loss is not
considered explicitly
ITU-R P for residential
building
COST 231
MWF
WINNER II
NLOS
ITU-R P for
office building
60
2 Indoor region with a
number of floors of
different types
Light wall with varying
thickness
MWF light wall COST 231 light
wall
MWF heavy wall
WINNER II
NLOS
ITU-R P for
residential
building
115
3 Indoor region with a
number of floors of
same type
Heavy wall with varying
thickness
COST 231 heavy wall
model
COST 231 light
wall
MWF heavy wall
WINNER II
NLOS
ITU-R P for
residential
building
110
4 Office building
A number of floors of
same type
Wall loss is not
considered explicitly
ITU-R P for office
building
COST 231
MWF
WINNER II
NLOS
ITU-R P for
residential
building
80
5 Indoor region with a
number of floors of
different types
Heavy wall with varying
thickness
MWF heavy wall COST 231 heavy
wall
MWF light wall
WINNER II
NLOS
ITU-R P for
residential
building
145
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5.6 Case Study
Five cases are considered here. According to the building structure, floor type, wall type,
number of floor and wall, the appropriate path loss model for a particular case is selected
and compared with rest of the path loss models. The considered cases are described in
Table 3.
In Fig. 19 the path loss value obtained for each case using the selected model based on
circumstances is compared with the result if other models are used. Table 3shows how the
best suitable path loss model can be chosen based on the constructional scenario of the
building.
6 Future Challenges
6.1 Challenge 1: Path Loss in 5G Mobile Network
Massive demand of bandwidth and date rate has grown interest in research of fifth gen-
eration (5G) mobile network [68]. Requirement of huge bandwidth is motivating the use of
millimeter wave bands. Here a large number of accessible bandwidth offers multi gigabit
transmission throughputs to mobile devices for 5G cellular communication system [69].
Indoor cellular channels are recently worked over 2.5, 5 GHz frequency bands etc. To use
the vast range of available bandwidth of 6–60 GHz, there is a need of widespread 60 GHz
indoor path loss measurements for understanding channel features [70]. The channel
characteristics will help in designing the 5G cellular system to achieve multi gigabits
throughput per second. Yet, only a few channel measurements work has been performed to
understand this frequency band. To obtain consistent models for future millimeter wave 5G
cellular system, propagation models has to be built for measuring the signal power
[71–73]. As 5G cellular system will be based on heterogeneous network structure, different
and efficient propagation models are required [74].
Fig. 19 Path loss in different cases using proposed strategy
P. Deb et al.
123

6.2 Challenge 2: Path Loss in 5G Millimeter Wave Mobile Network
Data loss may occur due to natural causes in millimeter wave communication [72]. The
main reasons for attenuation in 5G millimeter wave are [75]:
•Atmospheric Gasses Attenuation
•Water Vapor Absorption
•Oxygen Absorption
•Precipitation Attenuation
•Rain
•Foliage Blockage Attenuation
•Scattering or Reflection Effect Attenuation
•Diffused
•Diffraction or Bending Attenuation
5G millimeter wave mobile network is very much noise prone. To deal with these issues
different type of propagation model has to be developed [76,77].
6.3 Challenge 3: Poor Extensibility to Varying Environments
As empirical models are based on channel measurement, on specific environments they
don’t consider varying environmental characteristics. Thus they give a generalized result.
These models lack the ability to predict those experimental values [78]. Dependency on
environment makes these models less accurate. To increase the extensibility of these
models new and efficient path loss models has to be developed.
6.4 Challenge 4: Supporting Smart Antennas
For outdoor environment where antennas are located on high rise building or tower,
frequent configuration changes would not cause any problem. For indoor environment, the
antenna height of femtocell is lower compared to walls and other obstacles present in the
room. Such circumstances create shadow regions in the room [79], thus smart antennas are
used recently. Here use of right path loss model is a big challenge.
6.5 Challenge 5: Path Loss in Sky Scrappers
In recent days sky touch buildings are constructed. At the upper level of these buildings
signal strength is very low. To increase the signal strength, femtocells can be used.
Consequently an efficient indoor path loss model is required.
7 Conclusion
This paper has discussed on the indoor path loss models for femtocell based mobile
network. The indoor region is covered by femtocell base station. From the discussions it is
observed that, if the indoor region contains different number of walls of different types and
Study of Indoor Path Loss Computational Models for…
123

different number of floors of uniform type, then COST 231 is suitable. Otherwise if the
indoor region contains multiple types of walls as well as multiple types of floors, then
MWF is most applicable. If the indoor region has different number of walls of same type,
then WINNER II model can be used. If the wall loss is not considerable and path loss is to
be measured depending on the building construction and number of floor, then ITU-R P
model is useful. Simulation and experimental analyses are carried out to compare the path
loss models. The analyses show that how the most suitable path loss model can be selected
for an indoor scenario depending on frequency range, building structure, wall types and
floor types.
Acknowledgements Authors are grateful to Department of Science and Technology (DST) for sanctioning
a research Project entitled ‘‘Dynamic Optimization of Green Mobile Networks: Algorithm, Architecture and
Applications’’ under Fast Track Young Scientist scheme Reference No.: SERB/F/5044/2012–2013, No.
DST/INSPIRE Fellowship/2013/327 and TEQIP II under which this paper has been completed.
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Miss Priti Deb has obtained M.Tech., degree from West Bengal
University of Technology. Currently she is doing research in Dept. of
Computer Science and Engineering, West Bengal University of
Technology under the supervision of Dr. Debashis De. Her research
area includes power management in 5G mobile network. She has
published an International conference paper available in IEEE Explore.
Study of Indoor Path Loss Computational Models for…
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Miss Anwesha Mukherjee is currently doing research in Dept. of
Computer Science and Engineering, West Bengal University of
Technology as a DST-INSPIRE Fellow provided by Department of
Science and Technology, Govt. of India. She has passed B.Tech in
Information Technology Department from Kalyani Govt. Engineering
College in 2009. Then she has completed her M.Tech in Information
Technology Department from West Bengal University of Technology
in 2011. She stood First Class First in M.Tech and has received Gold
Medal. She is currently pursuing Ph.D. in Computer Science and
Engineering Department under the supervision of Dr. Debashis De.
Her research area includes location, power and security management in
mobile network. She has presented and published 15 research publi-
cations in national, international conferences, journals and one book
chapter. She has received Young Scientist award both in 2014 at
Beijing, China by International Union of Radio Science, H. Q.,
Belgium.
Dr. Debashis De is currently an Associate Professor and Head of the
Dept. of Computer Science and Engineering and Information Tech-
nology, West Bengal University of Technology. He has received
M.Tech. degree in Radio Physics and Electronics in 2002. He obtained
his Ph.D. (Engineering) from Jadavpur University in 2005. He worked
as R & D Engineer of Telektronics. Presently he is an Associate
Professor in the Department of Computer Science and Engineering of
West Bengal University of Technology, India and Adjunct Research
Fellow of University of Western Australia, Australia. He was awarded
the prestigious Boyscast Fellowship by department of Science and
Technology, Govt. of India to work at Herriot-Watt University,
Scotland, UK. He is also awarded Endeavour Fellowship Award during
2008–2009 by DEST Australia to work in the University of Western
Australia. He has received Young Scientist award both in 2005 at New
Delhi and in 2011 at Istanbul by International Union of Radio Science,
H. Q., Belgium. His research area includes location, power and
security management in mobile network and mobile cloud computing. He has presented and published 130
research papers in various national, international conferences and journals, and eight books.
P. Deb et al.
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