The Effect of Path Loss on QoS at NPL
Dinesh Sharma R.K.Singh
Doctoral candidate Professor UTU, Dehradun KEC ,Dhawarahat [email protected] [email protected]
ABSTRACT--- Radio communication or radio propagation is important for growing technologies with proper design, development and management strategies for any wireless network. Radio propagation is specific about the site and varies extensively depending on terrains, frequency of operation, velocity of mobile terminal, interface sources and other parameters. exact description of radio channel through basic parameters and using the mathematical models are important to predict the signal coverage, attainable data rate explicit performance quality of substitute signaling and reception schemes. This paper shows the quality of service (QoS) parameters and its possible realization at network planning level on the basis of path loss. Here we analyze the QoS in terms of received signal strength. To achieve this purpose we have taken the field data and calculated the path loss at 900 and 1800 MHz frequency and compared graphically with existing path loss models. After observing the results we conclude the QoS in urban area decreases rapidly as we move away from the transmitter with compared to sub urban and rural areas.
Keywords— Quality of service (QoS), Path loss, Received signal strength, Network planning level (NPL), Key Performance Indicators (KPIs).
I. INTRODUCTION
Now a day’s most of traditional wired networks are replaced by the wireless networks. The main difference in between these two is the change from a fixed to mobile location, i.e. an address is no longer a physical location and an address will reach the wireless station. Wireless networks always provide flexibility, easy installation &quick maintenance, the wired networks suffers by bandwidth constraints and potential for more error rates compared to their wired counterparts. This reason is to justify the prospective additional wireless network QoS techniques. Quality of service, the name itself explains the excellence or performance of any responsible system.
Quality of Service (QoS) is the capacity to define the performance in any responsible system [1]. The term Quality of Service is used to assign a set of parameters which are proposed to signify assessable aspects of the subjective “perceived quality”. The criteria taken into account by the user to justify a service vary according to the nature of the considered service. In the field of wireless networks, quality of service was defined in the ITU standard X.902 as "A set of quality requirements on the collective behavior of one or more objects". It consists of all Requirements of a connection, such as service time response, frequency response, signal to noise ratio (SNR), path loss, cross-talk, interrupts, audio levels, etc. By using the following QoS
Parameters we can explain the requirement of QOS[2,4]: a. Throughput or bandwidth
b. Delay or latency
c. Delay variation (delay jitter) d. Loss or error rate
II. EFFECT OF PATH LOSS ON QoS
A. Path loss
antennas, especially their gain, height and general location. The path loss also affects other parameters such as necessary receiver sensitivity, the form of transmission used and many other factors. Due to this, it is essential to realize the reasons for radio path loss, and to be capable to determine the levels of the signal loss for a give radio path. The path loss is repeatedly mathematically and these calculations are repeatedly undertaken to prepare the coverage or system design activities Therefore, path loss calculations are used in many radio and wireless survey tools determine signal strength at different locations. This type of wireless survey tools are used to help determine the radio signal strengths before installing the equipment. The installation of macro cell base station is very high so before installation radio coverage surveys are important.
B. Causes of path loss
Signal path loss can be caused by many factors. In a global environment there are many factors that affect the actual RF path loss. When planning any radio or wireless system, it is necessary to have a broad understanding the elements that give rise to the path loss, and in this way design the system accordingly. The following are some of the major elements causing signal path loss for any radio wave system [5, 6].
Free space loss: This loss occurs as the signal travels from transmitter to receiver through space without any other effects attenuating the signal. The energy of any signal decreases when it travels a larger distance in the space according to the conservation of energy.
Absorption losses: These losses occur when the radio signal passes into a medium like large buildings and foliage which are not totally transparent to radio signals. This can be explained by the travelling of a light signal passing through a transparent glass. The terrain over which signals travel will have a major effect on the signal. The hills obstruct the path and considerably attenuate the signal, time and again making reception impossible. We can take an example on the Long Wave band; it found that signals travel better over more conductive terrain, e.g. sea paths. Dry sandy terrain gives higher levels of attenuation. Buildings and other obstructions including vegetation have a significant effect. the buildings reflect radio signals and they also absorb them. Trees and foliage can attenuate radio signals, particularly when wet.
Diffraction: This type of losses occurs when an obstruction unexpectedly appears in the path. The signal diffracts around the object, and losses occur. Radio signals tend to diffract more at sharp edges.
Multipath: In a real global environment, signals will be reflected and they will reach the receiver via a number of different paths. These signals may add or subtract from each other depending upon the relative phases of the signals. This entire process leads to a loss which is multipath loss. Mobile receivers (e.g. Mobile phones) are subject to this effect which is known as Rayleigh fading.
Atmosphere: The atmosphere also affects radio signal paths. It affects at lower frequencies, especially below 30 - 50MHz, the ionosphere has a major effect, reflecting them back to Earth. At frequencies above 50 MHz and more the troposphere has a major effect on the radio signal path. For UHF broadcast this can extend coverage to approximately a third beyond the horizon.
C. Predicting Path Loss
One of the main reason to understand the different elements affect the path loss is to be capable to forecast the loss for a particular path, or to forecast the coverage that may be achieved for a given base station and broadcast station. The prediction of the path loss is not easy for real life global applications, because for that purpose it has to consider many factors into account. In spite of this there are many wireless radio coverage prediction software programs and wireless survey tools that are available to predict radio path loss. Most path loss predictions are made using techniques outlined below [5]:
Statistical methods: These methods of predicting signal path loss rely on measured and averaged losses for distinctive types of radio links. Different models can be used for different applications. This type of approach is generally used for cellular network planning, for estimating the coverage of Private Mobile Radio (PMR) links and to plan for broadcast coverage.
Some of the path loss models are as follows [7]- a. Simplified Path Loss Model
b. Stanford University Interim (SUI) Model c. Okumura’s Model
d. Hata Model
e. COST231 Extension to Hata Model f. ECC-33 model
g. Walfisch- Bertoni Model h. Longley rice model i. Egli Propagation Model j. Bullington model k. Epstein-Peterson model
D. Effects on Qos and its possible solutions
Path loss plays vital role to decide the QoS for wireless communication at network planning level (NPL). Path loss causes poor signal strength at the receiver side. So that the receiver is not able to detect the original signal. All wireless communication operators use Key Performance Indicators (KPIs) to judge their network performance and they evaluate the Quality of Service (QoS) regarding end user perspective. All the events being occurred over air interface are triggering different counters in the Base Station Controller (BSC). The following are the KPIs of QoS at network planning level:
(a) Power of the transmitter
Transmitter power affects the QoS. The power of the transmitter decides the area of coverage. By this we can say that in a definite area by increasing the power of the transmitter we can improve the QoS. But increasing transmitter power leads to two disadvantages. The first disadvantage is increased design complexity and high cost. The second disadvantage is increased exposure to electromagnetic fields generated during communication (lead to health problems).If any body part is exposed to an electromagnetic field; some of the electromagnetic energy is absorbed by that part of the body and converted into heat. The same principle is used in microwave oven to heat food or liquids. Excessive heat generated in the body will cause many health problems. So we conclude that power of the transmitter can not be increased beyond a limit.
(b) Receiver sensitivity
Receiver sensitivity is important at any radio receiver whether it is used for broadcast reception within a mobile or a fixed radio communication networking system [8]. We can explain about the entire system by seeing it. The capability or capacity of the entire radio receiver to pick up the required level of radio signals will allow it to operate more efficiently within its application of broadcast reception or within a radio communication network system. The two basic requirements of a radio receiver is selectivity of signals to separate one station from another and amplification of signals so that they can bring to a sufficient level to hear. By optimizing the RF amplifier performance at the receiver, the parameters for the whole of the receiver can be improved. In this way the specifications for signal to noise ratio, noise figure can be brought to the required level. Internal noise is dominated by thermal noise generated within the receiver and is formulated through introduction of noise factor (linear) or noise figure (dB).
(c) Antenna height
The antenna height also affects the QOS. If we double the antenna height results in a 6dB gain according to plane earth model [9]. The plane earth model assumes the receive signal is made up of two paths; one is direct path and the second is ground reflected path. Depending on the distance the difference in path lengths campaigns two rays to add differently in the propagation. As the distance gradually increases, the summation passes through a number of peaks and nulls until the path difference is less than half a wavelength.
region below 6 km. To understand the effect of antenna height on cellular coverage under micro cellular conditions path loss models were examined [10].
(d) Antenna gain
Antenna gain relates the intensity of an antenna in a given direction to the intensity that would be produced by a hypothetical ideal antenna that radiates equally in all directions (isotropic ally) and has no losses. Since the radiation intensity from a lossless isotropic antenna equals the power into the antenna divided by a solid angle of 4π steradians, we can write the following equation:
Although the gain of an antenna is directly related to its directivity, the antenna gain is a measure that takes into account the efficiency of the antenna as well as its directional capabilities. Gain is also dependent on the number of parameters and the tuning of those parameters. Antennas can be tuned to be resonant over a wider spread of frequencies. To estimate the gain, we are taking the following explanation: The radio channel is possessing a number discrete paths, each resistant according to the gain of the antenna patterns determined by the direction that it impinges on the antennas. If the antenna patterns and the characteristics of each path were known, then it would be possible to determine the effect of any antenna on the particular channel. Due to the difficulty of the problem, some simplifying assumptions were made. The antenna in the mobile was a ¾ λ whip antenna which has an omni directional pattern in the horizontal plane. Assuming that all the paths arrive at the antenna close to the horizontal plane, the paths will receive the same gain. At the cell site highly directional dipole array antennas were used. Since the cell site antenna is free and clear of all near by obstacles, it can be assumed that all the significant energy that traverses the channel between the two antennas would arrive in roughly the same direction at the base station. Even if there are a number of reflectors near by the mobile, the paths leaving the cell site would essentially possess the same departure angle. This implies that all the paths would be subjected to the same antenna (LOS) gain at the cell site. The above hypothesis was first tested on the Blackfoot data. Three different angles of antenna down tilt were investigated for the high site; 40 , 70, and 100 . for each down tilt setup, 50 measurements were recorded and
received signal strengths averaged and then converted into one average path loss value. the average path loss values for down tilt angles before removing the LOS gains were 94.8 dB, 96.4 dB, and 107.7 dB, respectively. After removing the LOS gains they were 109.8 dB, 108.4 dB, and 108.7 dB, respectively. The difference between the highest average path loss value and the lowest is henceforth referred to as spreading. By removing the LOS gains, the spreading changed from 12.9 dB to 1.4 dB, which indicates the validity of the assumption that the LOS gain is equal to the gain that the antenna has on the channel [10].
(e) Location of antenna
The location of antenna also plays very important role in the path loss. The location of antenna includes the tilting of the antenna. In the above two parameters it showed that the tilting of the antenna can increase or decrease the value of the path loss in a particular areas [10].
III. RESULTS WITH PRACTICAL FIELD DATA
Fig.1 Measured path loss and ECC-33 path loss model in Urban Area Fig.2 Measured path loss and COST-231model in Suburban Area
IV. CONCLUSION
In this paper we discussed the parameters those effect the QoS and its possible solutions on the basis of path loss at network planning level. To understand the effect of path loss on QoS we have taken the field data (Received signal strength) with the help of spectrum analyzer. With the help of this study we analyses the QoS (in terms of received signal strength) decreases rapidly in urban areas as compared with the sub urban and rural areas. In other words we can say that as the path loss increases the QoS decreases and vice-versa In this paper we also
Fig.5 The variation of the QOS in terms of received signal strength and path loss
discussed different path loss models like ECC-33 , Cost-231 and Egli’s models. By comparing the different path loss models in different environments, we concluded that ECC-33 models are giving the best results in urban area as shown in figure 1. COST-231 models are showing better results in sub urban area as shown in figure 2. Egli’s path loss models show better results in rural areas as shown in fig 3. The variation of QoS with path loss and distance are shown in fig. 4 & 5.
REFERENCES
[1] W.C. Hardy, QoS: Measurement and Evaluation of Telecommunications Quality of Service, John Wiley & Sons, 2001.
[2] Technical, Commercial and Regulatory Challenges of QoS: An Internet Service Model Perspective by Xipeng Xiao (Morgan Kaufmann,
2008, ISBN 0-12-373693-5).
[3] public domain material from the General Services Administration document "Federal Standard 1037C" (in support of MIL-STD-188).
[4]http://www.cisco.com/en/US/docs/ios/solutions_docs/qos_solutions/QoSVoIP/QoSVoIP.html [5] http://www.radio-electronics.com/info/propagation/path-loss/rf-signal-loss-tutorial.php. [6] T.S. Rappaport, Wireless Communications - Principles and Practice, 2nd
Edition, Prentice Hall , 2001.
[7] Dinesh Sharma, Purnima K. Sharma, Vishal Gupta, R.K.Singh, “A Survey on Path Loss Models used in Wireless Communication System Design” in IJRTE Vol. 3, No. 2 in 2010.
[8] http://www.radio-electronics.com/info/receivers/sensitivity/sensitivity.php [9] W. C. Y. Lee, Mobile Communication Engineering, McGraw-Hill 1982.
[10] Edward Benner and Abu B. Sesay, “ Effects of Antenna” IEEE TRANSACTION ON VEHICULAR TECHNOLOGY, VOL.-45 NO.-2 in 1996
Mr Dinesh Sharma was born on 5th Dec 1982 in Narnaul District Mohindergarh of Haryana (India).He received
his M.Tech. degree in Communication Engineering from SHOBHIT University, Meerut, India. He is a Associate Member of the IETE. He has published several Research papers in national and international journals/conferences. He is presently research scholar in UTTARAKHAND TECHANICAL UNIVERSITY, Dehradun (INDIA). His present research interest is in Signal Processing and Wireless Communication.
