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.
  1. 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.
  2. 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.