To communicate wirelessly is the basic needs of the modern world owing
to the fact that the population of mobile users has increased rapidly.
In this situation, customers or end-users demand for good quality of
service (QOS) and coverage. The penetration loss caused by different
household construction materials, affect signal strength received by the
end users. The penetration loss is significant while considering the
overall losses in wireless communication .
The End-users usually experience network challenges whenever wireless
signals are affected by either extrinsic or intrinsic properties.
However, the intrinsic signal properties are caused by the hardware
malfunction and failure, hence this is insignificant for reliable
devices. Wireless signals usually suffer loss as a result of free space,
which is dependent on distance.
The survey metrics in this project introduce the various parameters to
be measured using optimum software and hardware device to detect and
measure the metrics that are used as judging criteria to evaluate the
Quality of Service (QOS) experience by the end user(s) for various
household construction materials as wireless signal propagate through
them.
It must be emphasized that, users experience on a particular network
service which could either be Wi-Fi (2.4GHz), 2G(900/1800MHz),
3G(2100MHz) and 4G(2600MHz), differs based on their environment and the
medium through which the wireless signal has travelled. The Radio
Frequency (RF) signals are being used as wireless signals for
propagation. The absorption rate of different household construction
materials through which wireless signals travel differs from one
another. However, additive sum of the effect of reflection and
absorption are the major effect when signal propagate through different
materials. This effect causes signal attenuation while other factors
include: diffraction and Scattering .
The building materials considered in this project are non-magnetic and
dielectric but behave like a lossy dielectric materials since they allow
signal to penetrate through them.
The metrics of focus in this project are: Received Signal Strength (RSS)
(dBm), downloadspeed(Mbps),
Upload Speed(Mbps), Penetration loss(dBm), Packet Loss and
Jitter(ms).Therefore, this report presents the techniques required to
evaluate the quality of service of wireless signal in different
household construction materials.
The need to communicate wirelessly in an effective way without any delay
in transmission and reception of data which is essential in today’s
global world. Wireless communication requires the sending and receiving
of signals without the use of any physical medium. As a result, wireless
signals are susceptible to various challenges by penetrating through
different materials before it gets to the user terminal. The unrealistic
propagation of the wireless signal when it passes through various medium
which is caused by multipath has made it penetrate through various
construction materials having different characteristics which account to
a significant penetration loss. The quality of service perceived by the
end user is a function of various materials characteristics through
which signals have travelled; hence performance on the network tends to
slide down, as a result of the penetration loss through various
construction materials. Evaluation of the losses encountered in various
construction materials is essential to circumvent for the total losses
in a building and also evaluate the quality of in-door signals.
- RELATED WORKThe work in , presented the method used to determine the Global System
for Mobile Communication (GSM)signal provided by 4 service provider-
MTN, Airtel, Globacom and Etisalat in Port Harcourt. Focus was made on
the penetration loss in 5 selected buildings, constructed with
different materials such as (Mud house with thatched roof, mud house
with rusted corrugated iron sheet, sandcrete building with rusted
corrugated iron sheet, sandcrete building with unrusted iron sheet and
building with alucoboard wall cladding. The measured data was obtained
using a Techno Tablet installed with Radio Frequency Signal Tracker
(RFST) software. The surveyed parameters were signal strength, and
distance, from which the penetration losses were obtained. The average
of the collected data was computed from which the measured data was
taken twice a day in a month, which has an occurrence of sixty (60)
values. The data were evaluated using Least Square Line Analysis to
obtain the line that best fit the curve. The result obtained showed
that the building with alucoboard wall cladding has the highest signal
penetration loss while the sandcrete building/unrusted corrugated iron
sheet roof has the lowest signal penetration loss.
The data obtained from the services provider were reliable and
correlative, since they were taken twice a day in one month. However,
the Signal to Noise Ratio (SNR) was not considered. This could be a
bottle neck for wireless signal in the environment where external
sources contribute majorly to signal distortion which could be
referred to as extrinsic factor.
The work in examined the penetration loss of doors and windows inside
residence using Integrated Service Digital Network
Broadcast-Terrestrial (ISDB-T) Television signal operating at 677MHz
frequency. It demonstrated the signal parameters such as received
power (Indoor and Outdoor), signal to noise ratio (SNR), field
strength (δ) with the aid of spectrum analyzer which was connected to
Ultrahigh frequency (UHF) antenna known as Rabbit Antenna, directly
placed at the doors and windows made of different materials. This
survey was conducted on sixteen (16) residences in an urban area in
Philippines, that was 7km away from the National Broadcasting Network
(NBN). The buildings were classified in accordance to their
construction materials into four (4) classes: A, B, C and D. The
indoor signal is measured and compared with the outdoor signal, the
discrepancies was used as the penetration loss, as a result of the
material characteristics which causes signal degradation. The result
obtained from the average penetration loss for each houses was
computed and compared using commutative distribution function(CDF) in
a probability distribution curve which shows that Class A has the
lowest APL(average penetration loss), while Class B and C have larger
APL as a result of thicker wall with reinforced materials, Class D is
of light materials. As a result, APL decreases from heavy to light
materials.
More concerned was made on interference by using a desk set spectrum
analyzer which aid visualization of operating signal in frequency and
time domain. However, as a result of low power level in the device, it
might not display accurate result of the surveyed data.
The work in analyzed and evaluated the performance of a radio signal
in 4 different large buildings so as to give more understanding of
what to expect from radio propagation environment in a worst case
scenario. The method used by the author was to provide large set of
data, which described attenuation variability of radio signals in
various building types in the public safety frequency band. This was
carried out in 4 different large building structures which are:
Conventional Centre, High-Rise office building, Apartment building and
Laboratory building. The operating frequency of the signal was 750MHz
band, in which the measurement was done with three 3 different types
of signal measuring devices. They include: Spectrum Analyzer Radio
Mapping, Narrow band communication Receiver Radio Mapping and
Broadband Synthetic-Pulse measurement; which was used to obtain the
received signal strength (RSSL), Centre frequency and Root Mean Square
(RMS) delay spread of signal power.
The result obtained showed that the present of short pulses in the
time-domain waveform was as a result of multipath in a given
environment. The RMS delay spread value was used to determine the time
it will take the multipath reflection to decay below the threshold
level. The median and standard deviation value were critically
observed in most of the measurement in both spectrum analyzer and the
receiving system. The result further illustrated that, the RMS delay
spread value for the measurement made in the large open floor building
were typically 2 to 5 times greater than the measurement obtained from
the building with narrows corridors.
The use of the three set of measuring devices makes the result correct
with little or no discrepancies. However, the RMS spread value was
affected greatly by the direction of the antenna and the penetration
loss. Therefore, radio signal analysis should not only be focus on the
signal but also on the environment and material characteristics which
could be classified as either lossy or lossless materials.
The authors in presented a model metrics in relation to evaluate the
Quality of Experience (QOE) and signal strength for future QOE
optimization using a wireless Local Area Network(LAN) recognized as
802.11b/g in the IEEE standard. The evaluation was done with the aid
of a software tool which comprises of QOE measurement so as to
evaluate the end user and monitor the QOS (quality of services)
parameter: Signal Strength. From the empirical study performed by the
authors, using a mobile web browsing application which was tested on a
Personal Digital Assistant (PDA), a result was obtained and evaluated
using both the linear and exponential regression. The metrics of
evaluation was focused on QOE parameters perceived by the user with
the aid of a questionnaire which was scaled using the standardized
Mean Opinion Score (MOS) such as, Excellent, Good, Fair, Poor and Bad.
While the QOS parameters considered was the Signal Strength. The
measurement was taken at 4 different location using wireless LAN in
the test environment. The strength of the signal was demonstrated on
histogram chart with their rating which indicated the MOS of for the
user experience. The result demonstrated that, at location 2, having
signal strength of -61dBm, has a higher MOS rating as compared to
location 4, with signal strength of -83dBm. It can be deduced from the
result that, the better the QOE, the better the QOS.
The author was able to give a correlative result between the QOS and
QOE, based on user perception. However, due to the variation in human
perception, more than one users experience should be perceived so as
to obtain more reliable result.
In addition, the environment where the users opinion is perceived
should be considered, so as to identify the possible bottle neck in
wireless network.
The work in examined the study of network neutrality principles which
illustrated how packet data were being lost on traffic congestion
causes by rapid increase of the additional users and high data rate
application which is as a result of two distinct issues:
discrimination and QOS. The approach used by the author was to
categorized users activities on the network based on data rate,
quality of service and economic value. The parameter of measurement
involves the scaling of the data rate and quality of sensitivity of
the activities on the network. The network activities were categorized
according to their sensitivity level which could either be low or high
and according to QOS parameters. From the result, it was shown that
increase in data rate lead to an increase in sensitivity. The economic
value for two different internet service provider (ISP) was compared,
such that they were both use for the same network activities, the ISP
with lowest sensitivity would have the lowest economic value and vice
versa.
The work in investigated on the Global Service for Mobile
Communication (GSM) signal loss in a multi-storey building. The
measurement was carried out in different building 0f 2,3,4 and 5
storey at Port Harcourt using the service obtained from 4 service
provider which are: MTN, Globacom, Airtel and Etisalat to determine
the signal strength with the aid of an RF Signal Tracker(RFST). The
measurement was conducted outside and inside each floor of the
building and the difference were computed using the standard deviation
and the mean. The measured parameters include: signal strength (dBm),
Local Area Code (LAC), Cell Identity (CID) and the distance from the
transmitter. The result obtained illustrated that, the loss varies
between 3.09 and 3.91, which was as a result of the effect caused by
floor partition. The average path loss and the floor attenuation
factor were determined as 3.53 and 21.22 respectively, while the
standard deviation varied from 3.46 and 6.27. It was concluded that,
the penetration losses were higher at the ground floor than the fifth
floor; however, the fifth floor has the maximum floor attenuation
factor.
The work in examined the impact that 2.4GHz and 5GHz Wi-Fi (wireless
Fidelity) has when subjected to different household construction
materials across several distances. A Router of model Xfinity XB3,
with a dual band 802.11ac Wi-Fi was used as the Radio Frequency (RF)
source. It was housed in an enclosed box constructed from single
material having dimension (10.5″X 3.3″ X 9.5″) .A software called
inSSIDer 4 was used to obtain the data from the Laptop, so as to
measure the signal strength received at both 2.4GHz and 5GHz while
varying the distance. The inSSIDer aid the tracking of the following
parameters: Signal Strength, Distance and Frequency Band, which was
used to determine the output result. The results obtained were
computed to plot two graphs (for 2.4GHz and 5GHz) of distance against
signal strength. This shows the impact on the household materials
which are: wooden -box, brick, sheet- metal, tile -ceramic, tile
-porcelain, glass- tempered, dry -wall and cement –pavers which was
indicated.
The author opined that signal strength of a particular material
displayed in the graph for 2.4GHz did not go below -50dBm,
irrespective of the far distance between the laptop and the enclosed
router, while the 5GHz drastically fall in signal strength as the
distance increases.
The work in investigated on the penetration loss using two GSM (Global
System for Mobile Communication) operator signals in Delta state,
Nigeria. The GSM operator signals were used to investigate the
measurement for a period of 6 month (January- June). The indoor and
outdoor signal measurement in (dBm) in both concrete and block
structures were obtained, using the Signal Tracker (Donut) installed
on a Samsung Galaxy mobile phone. The software was able to capture
signal strength, cell identity (CID), GPS parameter and distance. The
measured parameters were used to compute the average outdoor and
indoor signals; their differences were used to obtain the penetration
loss. The penetration loss values were obtained for concrete and block
building. The result showed that average loss of 10.62dbm and 4.25dBm
were obtained for the concrete and block building respectively.
The authors opined that the signal degradation increase with an
increase in penetration loss. In addition, the GSM signal is a
function of the building types; the loss through a concrete building
is higher than the loss through the block building.
The work in investigated the GSM(Global System for Mobile
Communication) signal strength level inside and outside the selected
building by considering the available network(MTN, GLO and Airtel) in
the location at Ogbomosho, Oyo State. The research area of focus was
based on three locations with distinctively different but modern
building material such as: Hollow Block, Solid Block and Precast
Asbestos Block categorized as B1, B2 and B3 respectively. The study
was carried out within 12 months, using the following equipment:
Samsung Galaxy S6 Android Phone, Network Signal Info Pro (Kabiit
Software), Network Operator SIM (subscriber Identity Module). The
Network Signal Info Pro software helps to determine the RSSI (Received
Signal Strength Indication), distance and associated location
parameters from appropriate BTS (Base Transceiver Station) for various
environments. The RSSI was obtained for both indoor and outdoor of the
3 buildings using the available network of 2400MHz band. The
penetration Loss for the 3 operators was computed for B1, B2 and B3
and the mean value for the buildings were obtained. Comparison was
made between the theoretical and measures pathloss for both indoor and
outdoor. The result showed that, the measured pathloss was in
agreement with the theoretical pathloss for the selected buildings,
the building B1 with hollow structure has the lowest penetration loss
while B3 has the highest penetration loss. The authors concluded that,
the construction materials affect GSM signal level inside building
which also depend on the reference point at which signal is measured.
The work in examined the effect on signal strength when being
obstructed by building materials such as: Glass, Wood and Brick. The
work was carried out with the aid of the following equipment: Acer
Laptop and Cisco Aironet 1130 Access Point. The signal strength was
obtained while the laptop distance was varied by 3 inches. The measure
data was computed in both MS- Excel and sheet and a Scatter plot was
computed from MATLAB. The signal strength and distance was obtained in
(dB) and (m) respectively. Comparison was made between the practical
result by plotting the signal strength against distance and the ITU-
loss model for indoor environment. The result showed that, the
increase in the glass thickens will yield an increase in loss, also
the glass has the lowest loss of 5dB, while the wood has a 6dB loss
and brick has a 17dB loss.
- METHODOLOGY
This work was carried out at Kwara State University (KWASU) Campus,
Malete and Ilorin region. The university campus consists of vegetation,
students and sparsely located buildings and trees, while Ilorin region
consist of condensed buildings with little vegetation. As a result the
Kwara State University may be classified as a suburban. The surveyed
data were obtained within these 2 site location as a result of
unavailability and unreliability of Network service provided by the
service provider. The services used for the field measurements of 2G
signal were MTN NG and Airtel NG due to downtime.
Description of Materials
The focus of this research was based on 5 selected construction
materials which are: 3 timber species, Concrete Slab, and a
Glass-Reflective. The materials were categorized as; Material A,
Material B, Material C, Material D and Material E. The description of
the materials is shown in table II.
Table II Material Description.