Dr.Wael AlBayaydh has a PhD degree in computer engineering. He has been working in information technology for several years, concentrating on areas such as operating system, networking, network security, electronic commerce, Internet services, LDAP and Web servers. AlBayaydh has authored a number of articles for trade publications, and he presents his own papers at industry conferences. He can be reached at wr_y@hotmail.com
Teletraffic engineering is the application of traffic engineering theory to telecommunications. Teletraffic engineers use their basic knowledge of statistics including; Queueing theory, the nature of traffic, their practical models, their measurements and simulations to make predictions and to plan telecommunication networks at minimum total cost.
These tools and basic knowledge help provide reliable service at lower cost. Because the approach is so different to different networks, the networks are handled separately here: the PSTN, broadband networks, mobile networks, and networks where the possibility of traffic being heavy is more frequent than anticipated.
Introduction
Traffic engineering uses statistical techniques such as queuing theory to predict and engineer the behavior of telecommunications networks such as telephone networks or the Internet.
These tools and basic knowledge help provide reliable service at lower cost. Because the approach is so different to different networks, the networks are handled separately here: the PSTN, broadband networks, mobile networks, and networks where the possibility of traffic being heavy is more frequent than anticipated.
The field was created by the work of A. K. Erlang in whose honor the unit of telecommunications traffic intensity, the Erlang, is named. The derived unit of traffic volume also incorporates his name. His Erlang distributions are still in common use in telephone traffic engineering.
The crucial observation in traffic engineering is that in large systems the law of large numbers can be used to make the aggregate properties of a system over a long period of time much more predictable than the behavior of individual parts of the system.
The queueing theory originally developed for circuit-switched networks is applicable to packet-switched networks.
The most notable difference between these sub-fields is that packet-switched data traffic is self-similar. This is a consequence of the calls being between computers, and not people.
Mobile traffic
This article discusses the mobile cellular network aspect of teletraffic measurements . Mobile radio networks have traffic issues that do not arise in connection with the fixed line PSTN. Important aspects of cellular traffic include: quality of service targets, traffic capacity and cell size, spectral efficiency and sectorization, traffic capacity versus coverage, and channel holding time analysis.
Teletraffic engineering is a necessary field in telecommunications network planning to ensure that network costs are minimised without compromising the quality of service delivered to the user of the network. This field of engineering is based on probability theory and can be used to analyse mobile radio networks, as well as other telecommunications networks.
A mobile handset which is moving in a cell will record a signal strength that varies. Signal strength is subject to slow fading, fast fading and interference from other signals, resulting in degradation of the carrier-to-interference (C/I) ratio. A high C/I ratio yields quality communication. A good C/I ratio is achieved in cellular systems by using optimum power levels through the power control of most links. When carrier power is too high, excessive interference is created, degrading the C/I ratio for other traffic and reducing the traffic capacity of the radio subsystem. When carrier power is too low, C/I is too low and QoS targets are not met.
Quality of Service targets
At the time that the cells of a radio subsystem are designed, Quality of Service (QoS) targets are set, for: traffic congestion and blocking, dominant coverage area, C/I, dropped call rate, handover failure rate, overall call success rate.
The more traffic generated, the more base stations will be needed to service the customers. The number of base stations for a simple cellular network is equal to the number of cells. The traffic engineer can achieve the goal of satisfying the increasing population of customers by increasing the number of cells in the area concerned, so this will also increases the number of base stations. This method is called cell splitting (and combined with sectorization) is the only way of providing services to a burgeoning population. This simply works by dividing the cells already present into smaller sizes hence increasing the traffic capacity. Reduction of the cell radius enables the cell to accommodate extra traffic. The cost of equipment can also be cut down by reducing the number of base stations through setting up three neighbouring cells, with the cells serving three 120° sectors with different channel groups.
Spectral efficiency and sectorization
Mobile radio networks are operated with finite, limited resources (the spectrum of frequencies available). These resources have to be used effectively to ensure that all users receive service, that is, the quality of service is consistently maintained. This need to carefully use the limited spectrum, brought about the development of cells in mobile networks, enabling frequency re-use by successive clusters of cells. Systems that efficiently use the available spectrum have been developed - the GSM system-. Walke defines spectral efficiency as the traffic capacity unit divided by the product of bandwidth and surface area element, and is dependent on the number of radio channels per cell and the cluster size (number of cells in a group of cells):
efficiency = Nc / BW.Ac
where N c is the number of channels per cell, BW is the system bandwidth, and A c is Area of cell.
Sectorization is briefly described in traffic load and cell size as a way to cut down equipment costs in a cellular network. When applied to clusters of cells sectorization also reduces co-channel interference, according to Walke. This is because the power radiated backward from a directional base station antenna is minimal and interfering with adjacent cells is reduced. (The number of channels is directly proportional to the number of cells.) The maximum traffic capacity of sectored antennas (directional) is greater than that of omnidirectional antennas by a factor which is the number of sectors per cell (or cell cluster).
Traffic capacity versus coverage
Cellular systems use one or more of four different techniques of access (TDMA, FDMA, CDMA, SDMA). See Cellular concepts. Let a case of Code Division Multiple Access be considered for the relationship between traffic capacity and coverage (area covered by cells). CDMA cellular systems can allow an increase in traffic capacity at the expense of the quality of service.
In TDMA/FDMA cellular radio systems, Fixed Channel Allocation (FCA) is used to allocate channels to customers. In FCA the number of channels in the cell remains constant irrespective of the number of customers in that cell. This results in traffic congestion and some calls being lost when traffic gets heavy.
A better way of channel allocation in cellular systems is Dynamic Channel Allocation (DCA) which is supported by the GSM, DCS and other systems. DCA is a better way not only for handling bursty cell traffic but also in efficiently utilising the cellular radio resources. DCA allows the number of channels in a cell to vary with the traffic load, hence increasing channel capacity with little costs. Since a cell is allocated a group of frequency carries (e.g. f1 -f7 ) for each user, this range of frequencies is the bandwidth of that cell, BW. If that cell covers an area A c , and each user has bandwidth B then the number of channels will be BW/B. The density of channels will be .This formula shows that as the coverage area A c is increased, the channel density decreases.
Important parameters like the carrier to interference (C/I) ratio, spectral efficiency and reuse distance determine the quality of service of a cellular network. Channel Holding Time is another parameter that can affect the quality of service in a cellular network, hence it is considered when planning the network. It must be mentioned that it is not an easy task to calculate the channel holding time. (This is the time a Mobile Station (MS) remains in the same cell during a call). Channel holding time is therefore less than call holding time if the MS travels more than one cell as handover will take place and the MS relinquishes the channel. Practically, it is not possible to determine exactly the channel holding time. As a result, different models exists for modelling the channel holding time distribution. In industry, a good approximation of the channel holding time is usually sufficient to determine the network traffic capability. One of the papers in Key and Smith defines channel holding time as being equal to the average holding time divided by the average number of handovers per call plus one. Usually an exponential model is preferred to calculate the channel holding time for simplicity in simulations. This model gives the distribution function of channel holding time and it is an approximation that can be used to obtain estimates channel holding time. The exponential model may not be correctly modelling the channel holding time distribution as other papers may try to prove, but it gives an approximation. Channel holding time is not easily determined explicitly, call holding time and user's movements have to be determined in order to implicitly give channel holding time.The mobility of the user and the cell shape and size cause the channel holding time to have a different distribution function to that of call duration (call holding time). This difference is large for highly mobile users and small cell sizes.Since the channel holding time and call duration relationships are affected by mobility and cell size, for a stationary MS and large cell sizes, channel holding time and call duration are the same.
Quality of Service
(QoS) are mechanisms for controlling the performance, reliability and usability of a telecommunications service. Mobile cellular service providers may offer mobile QoS to customers just as the fixed line PSTN services providers and Internet Service Provides (ISP) may offer QoS. QoS mechanisms are always provided for circuit switched services, and are essential for non-elastic services, for example streaming multimedia. It is also essential in networks dominated by such services, which is the case in today's mobile communication networks, but not necessarily tomorrow.
Mobility adds complication to the QoS mechanisms, for several reasons:
- A phone call or other session may be interrupted after a handover, if the new base station is overloaded. Unpredictable handovers make it impossible to give an absolute QoS guarantee during a session initiation phase.
- The pricing structure is often based on per-minute or per-megabyte fee rather than flat rate, and may be different for different content services.
- A crucial part of QoS in mobile communications is grade of service, involving outage probability (the probability that the mobile station is outside the service coverage area, or affected by co-channel interference, i.e. crosstalk) blocking probability (the probability that the required level of QoS can not be offered) and scheduling starvation. These performance measures are affected mechanisms such as mobility management, radio resource management, admission control, fair scheduling etc. The
Factors affecting QoS
Many factors affect the quality of service of a mobile network. It is correct to look at QoS mainly from the customer's point of view, that is, QoS as judged by the user. There are standard metrics of QoS to the user that can be measured to rate the QoS. These metrics are: the coverage , accessibility (includes GOS), and the audio quality .In coverage the strength of the signal is measured using test equipment and this can be used to estimate the size of the cell. Accessibility is about determining the ability of the network to handle successful calls from mobile-to-fixed networks and from mobile-to-mobile networks. The audio quality considers monitoring a successful call for a period of time for the clarity of the communication channel. All these indicators are used by the telecommunications industry to rate the quality of service of a network.
The QoS in industry is also measured from the perspective of an expert (e.g. teletraffic engineer). This involves assessing the network to see if it delivers the quality that the network planner has been required to target. Certain tools and methods (protocol analysers, drive tests and Operation and Maintenance measurements), are used for this QoS measurement:
- Protocol analysers are connected to BTSs, BSCs, and MSCs for a period of time to check for problems in the cellular network. When a problem is discovered the staff can record it and it can be analysed.
- Drive tests allow the mobile network to be tested through the use of a team of people who take the role of users and take the QoS measures discussed above to rate the QoS of the network. This test does not apply to the entire network, so it is always a statistical sample.
- In the Operation and Maintenance Centres (OMCs), counters are used in the system for various events which provide the network operator with information on the state and quality of the network.
- Finally, customer complaints are a vital source of feedback on the QoS, and must not be ignored.
In general, GOS (grade of service) is measured by looking at traffic carried, traffic offered and calculating the traffic blocked and lost. The proportion of lost calls is the measure of GOS. For cellular circuit groups an acceptable GOS is 0.02. This means that two users of the circuit group out of a hundred will encounter a call refusal during the busy hour at the end of the planning period. The grade of service standard is thus the acceptable level of traffic that the network can lose. GOS is calculated from the Erlang-B formula, as a function of the number of channels required for the offered traffic intensity.
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