Introduction to UMTS Optimization

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(1)Introduction to UMTS Optimization Course Code: SC2804. Duration: 2 days. Technical Level: 3. Radio Principles and Planning courses include: . Radio Principles. . Principles of Radio Site Engineering. . Digital Radio and Microwave Link Planning. . Cell Planning for GSM Networks. . 2G/3G Indoor Coverage Planning. . 3G Indoor Coverage Planning. . Introduction to GSM Optimization. . Drive-Test Data Capture and Analysis. . Cell Planning for UMTS Networks. . Introduction to UMTS Optimization. Specially prepared for Safaricom Limited. www.wraycastle.com.

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(3) Introduction to UMTS Optimization. INTRODUCTION TO UMTS OPTIMIZATION. First published 2004 Last updated October 2008 WRAY CASTLE LIMITED BRIDGE MILLS STRAMONGATE KENDAL LA9 4UB UK. Yours to have and to hold but not to copy The manual you are reading is protected by copyright law. This means that Wray Castle Limited could take you and your employer to court and claim heavy legal damages. Apart from fair dealing for the purposes of research or private study, as permitted under the Copyright, Designs and Patents Act 1988, this manual may only be reproduced or transmitted in any form or by any means with the prior permission in writing of Wray Castle Limited. © Wray Castle Limited.

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(5) Introduction to UMTS Optimization. INTRODUCTION TO UMTS OPTIMIZATION. CONTENTS Section 1 Section 2 Section 3 Section 4 Section 5 Section 6 Section 7. Introduction and Overview Optimization Software Tools Optimizing Coverage and Capacity RAN Configurations and Dimensioning Idle Mode and System Access Connected Mode and Radio Link Control UMTS Features and Techniques. © Wray Castle Limited. iii.

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(7) Introduction to UMTS Optimization. SECTION 1. INTRODUCTION AND OVERVIEW. © Wray Castle Limited. v.

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(9) Introduction to UMTS Optimization. CONTENTS 1. Optimization or Planning? 1.1 What is Optimization? 1.2 Typical Planning/Optimization Distinction 1.3 Differences for UMTS. 1.1 1.1 1.3 1.5. 2. The Optimization Process 2.1 Identifying Optimization Opportunities 2.2 Key Statistics and Analysis 2.3 Drive Tests and Signalling Analysis 2.4 Change Implementation 2.5 Monitoring 2.6 Database Update. 1.7 1.7 1.7 1.7 1.9 1.11 1.11. 3. Exercise 1 – Discussion about Optimization Options and Priorities. 1.13. 4. Drivers for Optimization 4.1 Overall Quality of Service (QoS) 4.2 Set-up Failure 4.3 Dropped Calls. 1.15 1.15 1.17 1.19. 5. The Coverage–Capacity–Quality Relationship 5.1 Interference Sources 5.2 The Coverage Loop. 1.21 1.21 1.23. 6. Summary of Optimization Strategies. 1.25. © Wray Castle Limited. vii.

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(11) Introduction to UMTS Optimization. OBJECTIVES At the end of this section you will be able to: • • • •. explain the close relationship between planning and optimization in a Wideband CDMA (WCDMA) radio network describe the overall optimization process as distinct from purely planning functions list typical key metrics relating to optimization outline, in general terms, how the air interface may be optimized through the use of cell parameters, activation of features and other techniques. © Wray Castle Limited. ix.

(12) Introduction to UMTS Optimization. 1. OPTIMIZATION OR PLANNING? 1.1. What is Optimization?. The term optimization is used in connection with almost any engineering design task. It is usually taken to mean fine tuning for optimum performance. This general understanding of the term can be applied comfortably in the context of a UMTS network, but its precise interpretation can vary a great deal in practice. Ideally, the optimization of a Universal Mobile Telecommunications System (UMTS) network would take place in the assumption that the network is not under performing because of some fault condition or configuration error. In practice, however, the output of the optimization process will often be the identification of a fault or incorrectly-set parameter value. The optimization process may also stray from its purest interpretation into the area of future planning. The nature of UMTS network design is such that it benefits from giving consideration to future direction even when planning for current needs. The optimization team is in a good position to estimate the likely future behaviour of the network and may provide a valuable input into future planning needs.. 1.1. © Wray Castle Limited. SC2804/S1/v1.1.

(13) Introduction to UMTS Optimization. Optimization – Theoretical fine tuning for optimum performance. Optimization – Practical fine tuning for optimum performance fault/configuration error detection identification of network development requirements setting planning goals. Figure 1 Optimization Definition SC2804/S1/v1.1. © Wray Castle Limited. 1.2.

(14) Introduction to UMTS Optimization. 1.2. Typical Planning/Optimization Distinction. Most people distinguish between the planning and optimization processes. This is true whatever the technology because it would be impossible to perform any kind of optimization on a network that had not yet been planned. Therefore, planning can be considered as a process that is carried out and completed before optimization commences. Furthermore, the optimization process will need a goal, for example a certain minimum level of dropped calls. Therefore it also makes sense to consider that until a network’s performance can be observed and judged, it cannot be optimized. This idea emphasizes a division in time between planning and optimization. Much of this is true of the Global System for Mobile communications (GSM). The GSM planning process is generally one of ensuring sufficient radio coverage based on assumptions made in formulating link budgets. The process of coverage planning can be independent of capacity planning. This means that the initial planning process can be performed without optimization involvement.. 1.3. © Wray Castle Limited. SC2804/S1/v1.1.

(15) Introduction to UMTS Optimization. Set targets for radio coverage and capacity. Perform link budget calculations and planning for radio coverage. Dimension for capacity requirements Build the network. Gather performance statistics. Optimize radio network design and configuration. Plan for continued network development. Figure 2 Planning and Optimization Relationship in GSM SC2804/S1/v1.1. © Wray Castle Limited. 1.4.

(16) Introduction to UMTS Optimization. 1.3. Differences for UMTS. For UMTS, coverage and capacity planning must be linked. This is because the mutual interference between calls has a direct impact on radio performance, hence on coverage. This means that even at the earliest stage a proposed radio network design should be tested, evaluated and optimized in traffic-loaded conditions. The only way to do this at the design stage is by simulation. A realistic and detailed simulation will be beneficial. Similarly, the earlier the optimization process can be carried out the better. This can be thought of as ‘optimization in advance’. However, no simulation is perfect and traffic characteristics can only be guessed. This means that constant modification is required as the real network is rolled out and real traffic characteristics become apparent. In UMTS, planning and optimization are ongoing processes that will always remain closely linked.. 1.5. © Wray Castle Limited. SC2804/S1/v1.1.

(17) Introduction to UMTS Optimization. Set targets for radio coverage and capacity Perform link budgets and traffic analysis to determine cell characteristics and configuration. Optimize through simulation. Plan radio network including expected expansion after rollout. Optimize through simulation. Build the network Optimize radio network design and configuration. Gather performance statistics Plan for continued network development. Figure 3 Planning and Optimization Relationship in UMTS SC2804/S1/v1.1. © Wray Castle Limited. 1.6.

(18) Introduction to UMTS Optimization. 2. THE OPTIMIZATION PROCESS 2.1. Identifying Optimization Opportunities. The first step is to distinguish between optimization problems and faults and configuration problems. Information is therefore required from a number of sources, for example: • key performance statistics • problem reports from customers • radio planning information • recent configuration changes • completed and ongoing work • existing data on problem areas Analyzing this data and correlating the information will enable true optimization opportunities to be identified. 2.2. Key Statistics and Analysis. The next step is statistical analysis of all the sites with an optimization problem. Radio planning will give information about anticipated problems such as interference and coverage. Historical data on previous problems may indicate a new issue has arisen, perhaps due to expansion or an increase in load factor on one or more cells. There may now be enough information to suggest a solution. If not, further information may be obtained by drive testing. 2.3. Drive Tests and Signalling Analysis. Performing a drive test in the area where the problem exists may result in further data. Failing that, detailed analysis of the signalling information passed between the Node Bs and Radio Network Controllers (RNC) may uncover the problem. To make the drive test, call trace and signalling measurements valid they should be performed under the same conditions as those prevailing when the original problem occurred. For example, at the same time of day, in the same traffic conditions, on the same route and in the same place.. 1.7. © Wray Castle Limited. SC2804/S1/v1.1.

(19) Introduction to UMTS Optimization. Inputs: Identifying an QoS targets, problem reports, optimization opportunity planning information, ongoing work Statistical analysis of all sites of interest. Sufficient information. Inputs: radio planning, historical data No. Perform drive test. Yes Identify an appropriate change Implement change. Monitor results No. Success. Reverse change. Yes Update database. Figure 4 The Optimization Process SC2804/S1/v1.1. © Wray Castle Limited. 1.8.

(20) Introduction to UMTS Optimization. 2.4. Change Implementation. When the problem has been identified, an appropriate change should be recommended. However, before considering a change, the impact on the rest of the network needs to be assessed. This is critical in UMTS because of the interaction between User Equipment (UE), and also between Node Bs, in terms of interference effects. Parameters that may be considered for optimization on a cell basis include: • physical channel elements • Power Amplifier (PA) maximum transmit power • power control parameters • selection and reselection parameters • handover parameters • neighbour lists • common channel configuration • dedicated channel configuration • antenna orientation • antenna tilt • antenna type (beam width, beamforming, adaptive) • antenna height It may be desirable to implement network features such as: • transmit diversity • site selection diversity transmit • hierarchical cell structures • multi-user detection • secondary scrambling codes. 1.9. © Wray Castle Limited. SC2804/S1/v1.1.

(21) Introduction to UMTS Optimization. Inputs: Identifying an QoS targets, problem reports, optimization opportunity planning information, ongoing work Statistical analysis of all sites of interest. Sufficient information. Inputs: radio planning, historical data No. Perform drive test. Yes Identify an appropriate change Implement change. Monitor results. Success. No. Reverse change. Yes Update database. Figure 4 The Optimization Process (repeated) SC2804/S1/v1.1. © Wray Castle Limited. 1.10.

(22) Introduction to UMTS Optimization. 2.5. Monitoring. Having made the change it is important to perform post-implementation monitoring to ensure it has the desired effect. This can be done by monitoring the statistics or, better still, by using the same method as was used to identify the problem initially. Statistical analysis should also be carried out to assess the impact, if any, on the rest of the network. In UMTS this monitoring must include observation of surrounding cells. 2.6. Database Update. If the changes have been successful (or not), the databases in the network management systems need to be updated. This way the history of the problem, and hopefully its solution, can be logged and used by others.. 1.11. © Wray Castle Limited. SC2804/S1/v1.1.

(23) Introduction to UMTS Optimization. Inputs: Identifying an QoS targets, problem reports, optimization opportunity planning information, ongoing work Statistical analysis of all sites of interest. Sufficient information. Inputs: radio planning, historical data No. Perform drive test. Yes Identify an appropriate change Implement change. Monitor results. Success. No. Reverse change. Yes Update database. Figure 4 The Optimization Process (repeated) SC2804/S1/v1.1. © Wray Castle Limited. 1.12.

(24) Introduction to UMTS Optimization. 3. EXERCISE 1 – DISCUSSION ABOUT OPTIMIZATION OPTIONS AND PRIORITIES Working in groups of two or three, complete the following exercise and summarize your group’s answers in the work space on the opposite page. Allow about 10 minutes, after which all groups will compare answers. 1. List techniques, features or solutions that reduce interference either directly or indirectly (e.g. antenna downtilt).. 2. List techniques, features or solutions that increase capacity either directly or indirectly (e.g. secondary scrambling codes).. 3. List techniques, features or solutions that improve radio coverage or produce better utilization of existing coverage (e.g. cell repeater).. 4. List techniques, features or solutions that combat slow fading and fast fading and their effects, either directly or indirectly (e.g. transmit diversity).. 5. List techniques, features or solutions that improve link quality either directly or indirectly (e.g. multi-user detection).. 1.13. © Wray Castle Limited. SC2804/S1/v1.1.

(25) Introduction to UMTS Optimization. Exercise 1 Work Space and Summary of Results SC2804/S1/v1.1. © Wray Castle Limited. 1.14.

(26) Introduction to UMTS Optimization. 4. DRIVERS FOR OPTIMIZATION 4.1. Overall Quality of Service (QoS). For a network to be successful in the highly competitive mobile phone market, it must be customer driven. This should be reflected in the setting of appropriate Quality of Service (QoS) targets against which network performance can be measured on a regular basis. The QoS targets must be reviewed regularly as part of a policy of constant improvement. The UMTS standards associate a specific technical meaning to the term QoS in describing the expected performance characteristics of a channel. These are valid in this context, but the term is also being used in a wider sense. Here it includes a customer’s personal feeling about the success and usability of a service. Thus it includes what may be termed ‘human factors’. Measurement of the QoS may be carried out either by the network operator or by an independent agency or a combination of the two. In terms of air interface performance for real-time services such as voice, customers are usually concerned primarily with call success rate and secondarily with call quality. For non-real-time services such as messaging or data exchange, this prioritization may be reversed. Call success rate could be defined in a number of ways, but a simple definition classifies calls as successful when they set up without a problem, do not suffer handover failure and clear normally, i.e. the call is not cleared abnormally or dropped. Given the slight differences in processes, it is wise to measure call success rate independently for mobile-terminated calls and for mobileoriginated calls. Call quality may be measured in a number of ways depending on the type of call. Voice or video may be judged subjectively, but for optimization purposes an objective target in terms of bit error rate or frame erasure rate is preferable. Data and messaging services can also be considered in terms of bit error rate and frame error rate, but a retransmission factor should also be considered. Data services will also have delay requirements in terms of latency and delay variation. Finally, the quality of the radio channel may be a good indicator of overall quality and this may be monitored in terms of radio signal strength and signal-to-noise ratio.. 1.15. © Wray Castle Limited. SC2804/S1/v1.1.

(27) Introduction to UMTS Optimization. Quality of Service (QoS) Call Success Rate. Set-up failure. Dropped calls. Mobile originated. Mobile terminated. Link Quality Signal-tonoise ratio. Bit error rate Frame error rate. Radio signal strength. Retransmission rate. Figure 5 Quality of Service (QoS) SC2804/S1/v1.1. © Wray Castle Limited. 1.16.

(28) Introduction to UMTS Optimization. 4.2. Set-up Failure. Call set-up failure is attributable to a variety of causes. There may be a hardware and/or software failure in the network or in the mobile equipment; alternatively, the UMTS Subscriber Identity Module (USIM) may be invalid or faulty. In relation to the air interface, congestion may be the cause, possibly within the Random Access Channel (RACH) or Paging Control Channel (PCCH). Generally this type of congestion only affects mobile-terminated calls, but PCCH congestion may also affect some types of ongoing data calls. The congestion of traffic-carrying channels will be a significant concern for optimizers. When the cell’s noise rise limit is reached, Radio Resource Control (RRC) will not allow new calls to be established. This situation in UMTS is complicated by the simultaneous provision of different service types with different QoS requirements. For example, a real-time voice call or higher-bit-rate video call may be blocked because of the noise rise limit. Yet, at the same time, a low-bit-rate non-real-time call may be allowed to go ahead. Additionally, the noise rise in a cell to be partly a factor of traffic load in neighbour cells, so it is possible for congestion in one cell is caused by overloading in a neighbour cell. Care must be taken to ensure that the cause is the focus of optimization, not the symptom. Calls may also fail at setup because of poor radio coverage, fading, or interference causing failure in access channels. Coverage can never be perfect. Interference is always present and can become too strong. Fading effects are also inevitable in a cluttered, multipath environment. The most obvious sources of interference are other users and other intra-frequency cells. However, interference contributions will also be present from inter-frequency cells, some of which could belong to other operators. This may be an important consideration in some optimization scenarios. The multimedia nature of Third-Generation (3G) services means that not all networks will support all services in all locations. Therefore it is possible that calls may fail simply because the network does not support the requested service or channel configuration. Incorrect cell parameter settings could also cause set-up failure, for example by causing mobiles to select an inappropriate server in idle mode or use inappropriate transmit power for access. UMTS presents particular challenges for the optimizer in this respect because there are so many parameters and because of the interdependency between cells.. 1.17. © Wray Castle Limited. SC2804/S1/v1.1.

(29) Introduction to UMTS Optimization. Set-up Failure. Hardware limits Soft capacity Service type and QoS variation Air interface channel types. congestion poor radio coverage. Intra-frequency Inter-frequency Inter-operator Pilot pollution External Noise. interference fading service not supported. incorrect or suboptimal cell parameter settings. Many parameters Interdependency. hardware/software problem in the network, mobile equipment or USIM. Figure 6 Set-up Failure SC2804/S1/v1.1. © Wray Castle Limited. 1.18.

(30) Introduction to UMTS Optimization. 4.3. Dropped Calls. Many of the reasons why calls drop are closely related to those that cause set-up failure. For example, calls may drop because of a hardware or a software problem in the network or mobile equipment, or because of problems in the radio channel. The potential causes of problems with the radio channel in terms of signal strength or interference are the same as those for set-up failure. One additional problem when considering dedicated channels could be the inappropriate setting of parameters that relate to closed loop power control. Calls requiring dedicated channels will also need handover functions. These may be a mixture of soft and hard handovers. In most UMTS networks there is also a requirement for inter Radio Access Technology (RAT) handovers. There are many parameters that relate to measurements and subsequent handover decisions. Incorrect or inappropriate setting of these parameters could result in handover failure. Problems with coverage or interference could also result in handover failure. In extreme cases call drops may be forced on a priority basis at times of congestion. If pre-emptive channel allocation is adopted for emergency (112) calls, then a routine non-emergency call may be dropped to provide emergency capacity. Key metrics relating to dropped calls include poor signal level, high interference level and handover success/failure rate.. 1.19. © Wray Castle Limited. SC2804/S1/v1.1.

(31) Introduction to UMTS Optimization. Dropped Calls. Intra-frequency Inter-frequency Inter-operator Pilot pollution External noise. interference fading poor radio coverage. Different bit rates Different QoS. handover/reselection failure. Soft (intra-frequency) Hard (inter-frequency) Hard (inter-RAT). fast power control. Capacity Quality. incorrect or suboptimal cell parameter settings. Measurements Power control Handover. pre-emption for emergency call channel allocation. Figure 7 Dropped Calls SC2804/S1/v1.1. © Wray Castle Limited. 1.20.

(32) Introduction to UMTS Optimization. 5. THE COVERAGE–CAPACITY–QUALITY RELATIONSHIP 5.1. Interference Sources. The capacity available in a UMTS system is ultimately limited by the amount of interference present. Downlink capacity may be thought of as limited by the total amount of transmit power available from the Node B. Nonetheless, downlink transmit power is only a factor because the inability to raise power beyond a limited point restricts the ability to overcome interference. The amount of interference tolerated by a given system is variable. It can be considered a factor of three key considerations: • services offered • features supported • local environment Different services have different QoS requirements and can therefore tolerate different amounts of interference. Optional features such as Multi-User Detection (MUD) can be used to increase tolerance to interference. The local environment determines a channel’s exposure to potential interference sources. An uplink channel is separated from other channels by uplink scrambling codes. An individual channel will experience interference predominantly from other in-cell and neighbour-cell intra-frequency channels. However, there will also be some adjacent channel interference, which may be most problematic if the interference source belongs to another operator. A downlink channel is separated from other channels on the same cell by the Orthogonal Variable Spreading Factor (OVSF) codes. These are highly orthogonal, but where different-length codes are used simultaneously in a multipath environment there will be a significant interference contribution. Downlink channels in neighbour cells are separated by scrambling codes, but this will also present an interference source. Additionally, as for uplink channels, adjacent radio channels will contribute some interference.. 1.21. © Wray Castle Limited. SC2804/S1/v1.1.

(33) Introduction to UMTS Optimization. Other UEs in neighbour cells. UL Int. DL Int.. UL Int.. DL. UL Int.. Intra-frequency neighbour. DL Int.. UL DL Int. Inter-frequency neighbour Other UEs in the serving cell. Serving Node B UE. Other UEs in neighbour cells. Figure 8 Interference Sources SC2804/S1/v1.1. © Wray Castle Limited. 1.22.

(34) Introduction to UMTS Optimization. 5.2. The Coverage Loop. Conventional planning practices deal with capacity and coverage as fundamental but independent processes. This approach is not applicable for a Code Division Multiple Access (CDMA)-based system. UMTS is both CDMA based and it provides multimedia support, hence capacity and coverage calculations cannot be separated. Any tool used to simulate network performance for planning or optimization of a UMTS system must link these calculations. The link budget is a normal starting point for any coverage estimate. However, in a CDMA-based system the link budget must account for interference levels. The interference level for a cell can be calculated if the load on a cell and its neighbours is known. If traffic distribution and traffic types are known, then cell load can be calculated for a given coverage area. In order to calculate cell coverage it is necessary to calculate a link budget. To establish an initial entry point to this loop, an assumed load is used, allowing an iterative process to begin. This will ultimately converge on a solution. The result of this convergence will be used for planning a network in the rollout stage. Once the network is operating and carrying live traffic these calculations may need to be revisited. Discrepancies between the assumptions made at the planning stage and real traffic characteristics could lead to coverage or interference problems. It is an optimization function to verify load, capacity and coverage assumptions as part of the analysis of optimization tasks.. 1.23. © Wray Castle Limited. SC2804/S1/v1.1.

(35) Introduction to UMTS Optimization. Coverage. Link Budget. Capacity. Figure 9 The Coverage Loop SC2804/S1/v1.1. © Wray Castle Limited. 1.24.

(36) Introduction to UMTS Optimization. 6. SUMMARY OF OPTIMIZATION STRATEGIES Most optimization solutions involve the use of network features, adjustment of one or more cell parameters, adjustment of antenna orientation, tilt, height or type, and redimensioning of traffic or control channels. More serious issues may require the addition of macro or micro sites, provision of in-building coverage, or cell splitting. In all cases, optimization activity must be carefully prioritized, keeping QoS and the customer in mind. There is little point in trying to optimize a cell working at 90% of potential capacity if one of its neighbours is suffering a 50 percent handover failure rate, for example. The optimizing engineer must always look for a practical solution that acknowledges the real constraints. For example, in a site suffering very high blocking, it may not be possible to install a second radio carrier (existing cabinets full, lack of space for more, perhaps) and another solution must be found (maybe a new micro cell and use of a Hierarchical Cell Structure (HCS) perhaps). It is also important to look for the simplest solutions first. For example, downtilting an antenna to modify coverage before considering a complete change of antenna type or complicated and risky parameter changes. Another complicative factor can be the use of Radio Network Subsystem (RNS) equipment from a number of different vendors within a single network. This can cause compatibility problems as not all vendors offer the same features and facilities. Adjustment of cell parameters is not a precise science. Some trial and error is often required. It is important to adjust only the minimum number of parameters simultaneously (one at a time if possible) in order to determine the parameter producing the changes (desirable or otherwise). Parameter changes can be implemented locally or from the Operations and Maintenance Centre (OMC). In all optimization activity, it is important to consider possible knock-on effects before taking action. Reorienting an antenna could solve coverage problems but cause serious interference problems elsewhere. It is important to consult others, discuss the issues, and perhaps consider alternatives before selecting the final solution. Equally, the appropriate company procedures must be followed when implementing changes. Finally, timing is important. Busy hour is not the best time for potentially serviceaffecting changes of parameters, features, etc. It is necessary to choose the time carefully and ensure all procedures are followed.. 1.25. © Wray Castle Limited. SC2804/S1/v1.1.

(37) Introduction to UMTS Optimization. Key Optimization Options antenna adjustment omni to sector transmit parameter tuning new cells additional radio carriers channel types/configurations deployment of features. Prioritize Activity customer quality of service. Select the Solution practical solutions within constraints simplest solution first knock-on effects consider alternatives multi-vendor issues company procedures timing. Implement the Solution monitor results customer quality of service reassess if required. Figure 10 Selecting and Implementing Optimization Solutions SC2804/S1/v1.1. © Wray Castle Limited. 1.26.

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(39) Introduction to UMTS Optimization. SECTION 2. OPTIMIZATION SOFTWARE TOOLS. © Wray Castle Limited. i.


(41) Introduction to UMTS Optimization. CONTENTS 1. Software Tools for Optimization 1.1 Introduction. 2.1 2.1. 2. Planning and Simulation Tools 2.1 Planning Tool Capabilities 2.2 The Graphical Display 2.3 Monte Carlo Simulation 2.4 Dynamic Simulations. 2.3 2.3 2.5 2.11 2.15. 3. Drive Test Tools 3.1 CW Testing 3.2 Live Network Drive Testing. 2.17 2.17 2.19. 4. Network Performance Data 4.1 Collection, Storage and Processing of Statistics 4.2 Key Statistics. 2.21 2.21 2.23. © Wray Castle Limited. iii.


(43) Introduction to UMTS Optimization. OBJECTIVES At the end of this section you will be able to: • • • • • • •. identify a range of different software tools that are applicable to the optimization process describe the desired capabilities of different tool types when used to optimize a WCDMA radio network describe how drive tests, ongoing radio coverage tests and traffic measurements relate to capacity and network optimization describe how simulations can be used to analyze optimization problems and identify potential solutions state the role of the NMC/OMC in providing statistical data of various types recognize the need for hardware and software tools in relation to testing and optimization recognize the limitations of tool and simulation capabilities. © Wray Castle Limited. v.

(44) Introduction to UMTS Optimization. 1. SOFTWARE TOOLS FOR OPTIMIZATION 1.1. Introduction. There is a wide range of tools available to the optimizer to assist with the optimization process. Some of these are the same as those used for the planning process, for example planning software or drive test tools. Others are specific to the optimization role. These include system databases, network statistics analysis tools, dynamic simulation software, protocol analyzers, network simulators and parameter tuning tools. Figure 1 provides a summary of some of the key software tool types that are utilized for optimization. These tools can be very complex when applied to UMTS and it is important that the optimizer is familiar with their operation and capabilities. The optimizer must be able to interpret fully and correctly output information from the tool. While these tools can be very powerful they also have limitations that must be appreciated and allowed for if the correct significance is to be applied to results.. 2.1. © Wray Castle Limited. SC2804/S2/v1.1.

(45) Introduction to UMTS Optimization. Radio planning tools Static simulation tools Dynamic simulation tools Parameter tuning tools. Protocol analyzers. Build and configuration databases. OMC/NMC KPIs. RNC Drive test tools Node B. Figure 1 Optimization Tools SC2804/S2/v1.1. © Wray Castle Limited. 2.2.

(46) Introduction to UMTS Optimization. 2. PLANNING AND SIMULATION TOOLS 2.1. Planning Tool Capabilities. Planning tools may be modified versions of Second-Generation (2G) planning tools or they may be dedicated 3G tools. Many operators have both 2G and 3G networks and it is beneficial if the same tool can show and process information about both systems simultaneously. Planning for GSM is usually a simple process of creating coverage predictions based on balanced uplink and downlink link budgets. However, for UMTS, radio signal strength predictions are not sufficient. Even if uplink and downlink link budgets have been performed that include allowance for system load, specific simulations are required to model the effects of traffic. Realistic mixed offered traffic must be simulated as accurately as possible. Therefore the tool needs to have a facility for modelling a variety of traffic and channel characteristics. These are most commonly brought together to form a service reliability prediction using a Monte Carlo simulation The optimizer may also be interested in a number of other radio characteristics. For example, prediction of soft handover areas, pilot pollution, Ec/Io values and active set sizes are very important when considering optimization solutions.. 2.3. © Wray Castle Limited. SC2804/S2/v1.1.

(47) Introduction to UMTS Optimization. Traffic Modelling. Radio signal strength prediction. mixed traffic channel characteristics demographics mobility user characteristics. CDMA Factors soft handover areas pilot pollution Ec/lo UE transmit power active set size. Monte Carlo Simulations used to produce service reliability maps. Figure 2 Planning Tool Capabilities SC2804/S2/v1.1. © Wray Castle Limited. 2.4.

(48) Introduction to UMTS Optimization. 2.2. The Graphical Display. The graphical display in any planning tool will contain both foreground and background data. Background data includes things like terrain contours, clutter data and vector data showing roads and railways. It may also be possible to overlay aerial photos or maps. The display shown in Figure 3a is typical and is taken from the Atoll planning tool produced by Forsk. The display is currently showing terrain data with clutter and vector data on top. Foreground data includes an indication of site positions, typically with graphical and text annotations giving an indication of site configuration. On top of this the tool will display the results of predictions and simulations. Figure 3b shows sites displayed with radio signal strength. Figure 3c shows a mixed traffic Monte Carlo simulation. Figure 3d shows predicted soft handover areas.. 2.5. © Wray Castle Limited. SC2804/S2/v1.1.

(49) Introduction to UMTS Optimization. Figure 3a Example Graphical Display. Figure 3b Sites and Radio Signal Strength SC2804/S2/v1.1. © Wray Castle Limited. 2.6.


(51) Introduction to UMTS Optimization. Figure 3c Mixed Traffic Monte Carlo Simulation. Figure 3d Soft Handover Prediction SC2804/S2/v1.1. © Wray Castle Limited. 2.8.

(52) Introduction to UMTS Optimization. 2.3. Monte Carlo Simulation. The Monte Carlo simulation is a critical process in the planning and optimization of UMTS networks. It is not an ideal simulation type in that it is static, but it is a good compromise that gives the optimizer a fairly quick and relatively realistic view of likely network operation. It is particularly useful for the optimizer to test the probable impact of a proposed optimization change. To simulate network operation it is necessary to account for the effects of interference between users in both the uplink and downlink directions. It is also necessary to model the effects of power control and mixed traffic. To do this, the Monte Carlo simulation creates a series of snapshots (or drops). For each of these snapshots users are randomly scattered over the ground area with weightings for expected traffic density. The tool then uses defined radio parameters to estimate transmitted power, soft handover requirements and, ultimately, call success rate. A number of snapshots can then be combined to produce a statistical analysis of the probability of coverage for various service types. 2.3.1. Monte Carlo Simulation Inputs. Figure 4 shows some of the most significant input parameters that are required before a Monte Carlo simulation can be performed. Tools vary in the way traffic profiles are entered, but typically traffic layers are built up by mapping services to user types and then user types to geographical areas. The result is a map showing the combined requirement for different services across the map area. Numerous radio parameters may be required. Many are related to site configuration and radio transceiver performance capabilities. However, some parameters may be adjusted through the optimization process.. 2.9. © Wray Castle Limited. SC2804/S2/v1.1.

(53) Introduction to UMTS Optimization. Bit rate Required Eb/No Activity factor PS/CS Channel type. Terminal type Service profile Service usage Mobility. User types User density. Service A. User type A. Area type A. Service B. User type B. Area type B. Service C. User type C. Area type C. Service n. User type n. Area type n. Monte Carlo Simulation. General Radio Parameters Site details (antenna height, gain, position, etc) Path loss Total transmit power Pilot power weighting Common channel power weightings Noise rise limit Ec/Io limit Soft handover thresholds Maximum active set size Power control step size Orthogonality factor. Figure 4 Monte Carlo Simulation Inputs SC2804/S2/v1.1. © Wray Castle Limited. 2.10.

(54) Introduction to UMTS Optimization. 2.3.2. Monte Carlo Simulation Output. The output of a snapshot produced through the Monte Carlo simulation will be an indication on the map of user distribution, requested services and connection success or failure. The example in Figure 5 shows a snapshot based on a simulated system supporting three different user types, each with access to the services listed in the displayed legend. The tool can provide specific data indicating the uplink and downlink channel performance for each user instance, as shown. Similar collective statistics can be produced for site performance. It is then possible to combine the outputs of a number of snapshots to produce a statistical map for each service type and user type combination.. 2.11. © Wray Castle Limited. SC2804/S2/v1.1.

(55) Introduction to UMTS Optimization. Figure 5 Monte Carlo Simulation Snapshot SC2804/S2/v1.1. © Wray Castle Limited. 2.12.

(56) Introduction to UMTS Optimization. 2.4. Dynamic Simulations. An advantage of static simulations is that they are quick to perform and the results are quite easy to interpret. Nevertheless, their accuracy is limited. When statically simulated, a call is either active or not, it is either in soft handover or not and power control is stabilized. In a real system there is a lag between measurements and control activity for power control and handover control. Similarly, open loop power control for Physical Random Access Channel (PRACH) establishment and signalling will precede all call attempts; even those that are unsuccessful. These can be allowed for to some extent in static simulations by including error variables, for example by adding a random error to required transmit power levels, but the most accurate results are produced with dynamic simulations. Dynamic simulations use specialized software that model user activity and movement over a continuous time frame. This enables much more detailed analysis of network behaviour with a specific set of parameter and configuration settings. This method is more time consuming but is of great value to the optimizer, especially in areas that are sensitive to small changes in settings. This method may also be used to generate correction factors that will improve the accuracy of results produced in static simulations. Care should be taken when setting up dynamic simulations to ensure that they have a clear objective goal. The results can be difficult to interpret if too many changes in settings are made.. 2.13. © Wray Castle Limited. SC2804/S2/v1.1.

(57) Introduction to UMTS Optimization. Trajectory of UEs is modelled following a map vector such as a road. DCH activity including closed loop power control. DCH activity including closed loop power control and soft handover. RACH activity including open loop power control UE inactive. DCH activity including closed loop power control. Figure 6 Dynamic Simulations SC2804/S2/v1.1. © Wray Castle Limited. 2.14.

(58) Introduction to UMTS Optimization. 3. DRIVE TEST TOOLS Drive testing often provides a primary source of information for optimizers investigating recognized performance problems. Drive testing can be used for a wide variety of network optimization functions including network performance assessment, fault analysis and model tuning. Two basic forms of drive testing are commonly performed, Carrier Wave (CW) testing and live network testing. 3.1. CW Testing. This involves the use of a calibrated receiver connected to a data storage device, typically a laptop or a Personal Digital Assitant (PDA). The receiver may be capable of measuring more than one frequency simultaneously. For UMTS it is useful if the receiver is capable of providing measurements of Receive Signal Code Power (RSCP) and Ec/Io for individual cells. However, basic CW testing measuring radio signal strength may be used on individual frequencies from a test transmitter for basic path loss estimation. CW testing is most commonly used for propagation model tuning and verification. The example in Figure 7 shows an overlay of CW test data on an empirically generated signal strength prediction. These differences can be analyzed to calculate a standard deviation for the cell. This can then be used to modify the ‘k’ values in the empirical model.. 2.15. © Wray Castle Limited. SC2804/S2/v1.1.

(59) Introduction to UMTS Optimization. Figure 7 CW Testing SC2804/S2/v1.1. © Wray Castle Limited. 2.16.

(60) Introduction to UMTS Optimization. 3.2. Live Network Drive Testing. This type of drive testing involves the connection of a test mobile (usually incorporating test software) to a logging device such as a laptop or PDA. A series of calls are made, either manually or automatically, and all events and signalling during the calls are recorded. It is particularly useful to record measurement data from the test mobile, both during calls and while in idle mode. UMTS offers the possibility to provide modified measurement commands to individual mobiles. This would mean that test mobiles could be asked to measure a larger neighbour set and provide more detailed measurements. The range of measurements that can be specified for UMTS is extensive. The recorded data captured during a drive test is then replayed using a drive test analysis tool. This may be a specialized tool, but many planning tools will also overlay some drive test data. Drive test analysis tools will typically use recorded positional information to provide a rolling map display for real-time or slow-time replay of drive test logs. Many analysis tools provide a protocol analysis function so that signalling can be decoded. This is particularly useful when analyzing the reasons for call failure. Figure 8 shows part of a drive test log overlaid on a graphical display in a planning tool.. 2.17. © Wray Castle Limited. SC2804/S2/v1.1.

(61) Introduction to UMTS Optimization. Figure 8 Live Network Drive Testing SC2804/S2/v1.1. © Wray Castle Limited. 2.18.

(62) Introduction to UMTS Optimization. 4. NETWORK PERFORMANCE DATA In a UMTS network, performance data is available in the form of raw statistics from all major network elements in the core network such as Mobile-services Switching Centres (MSC), messaging platforms, databases and other service platforms. Similarly, performance data can be gathered form all network elements in the UMTS Terrestrial Radio Access Network (UTRAN) such as RNCs, Node Bs, transmission nodes and Location Management Units (LMU). These statistics are essential for the day-to-day operation of the network, providing data for ongoing performance evaluation against targets. This information is also critical for the optimizer because it may be used for problem analysis and provides a means of assessing the success or otherwise of optimization solutions. 4.1. Collection, Storage and Processing of Statistics. All network elements, for example an RNC, collect and store statistical data locally. These raw statistics, of which there are many different types, are uploaded to the OMC/NMC at regular intervals. Usually they can also be read locally using a laptop. The uploads are carried out using Operations and Maintenance (O&M) data links, normally utilizing part of the transmission infrastructure. The upload interval could be as short as every five minutes, but is more likely to be every 15 or even every 30 minutes. It is possible for the most important statistics to be uploaded more frequently than other data in some systems. Raw statistics are sometimes called counters. The raw statistics can be viewed as tabular or graphical data, or further processed to provide key statistics, which are also known as metrics or Key Performance Indicators (KPI).. 2.19. © Wray Castle Limited. SC2804/S2/v1.1.

(63) Introduction to UMTS Optimization. Statistical reports (KPIs). Storage in relational database. Reporting tool. Tabular. Graphical. Data collection process. OMC/NMC. Local access to data. Figure 9 Gathering Network Performance Data SC2804/S2/v1.1. © Wray Castle Limited. 2.20.

(64) Introduction to UMTS Optimization. 4.2. Key Statistics. Key statistics are the KPIs that are used to judge whether the network is working to its design criteria. They are created through the processing of raw statistics. For example, raw statistics may be uploaded from each cell regarding the number of call requests, the number of successful attempts and the number of unsuccessful attempts. These would all be provided for a defined measurement period, perhaps every 15 minutes. If all these results are summed for all the cells on an RNC over a 24-hour period, then a KPI could be produced representing average call success rate for each day. Typically this would be divided into success rates for each definable call type, for example voice, video telephony, low-rate packet data and high-rate packet data. KPIs will be required for many different aspects of the operational network’s performance. Figure 10 provides some examples of things that may be included, but it is up to individual operators to determine the most appropriate KPIs. KPIs falling below an expected threshold may trigger optimization activity. These statistics in themselves may be useful for the optimizer, but more detailed analysis is often required to isolate a problem. For example, the call success rate mentioned above may be studied on an hourly basis in order to identify a time period when the problem occurs. More detailed analysis may also be set up when a new feature is introduced on a trial basis. Because of the potentially very large amount of data generated, it is beneficial if particular information about performance is targeted for detailed analysis in respect of the new feature. However, standard statistics should also be monitored in case the feature has an unexpected effect.. 2.21. © Wray Castle Limited. SC2804/S2/v1.1.

(65) Introduction to UMTS Optimization. Idle Mode Related success rate location update routing area update UTRAN registration area update total attempts location update routing area update UTRAN registration area update. Set-up Related paging success rate RACH success rate successful channel allocations successful PDP context activations average duration for call establishment average range from which call attempts are made. Connected Mode Related number of dropped calls number of soft handovers number of hard handovers handover success rate average percentage of calls in soft handover average transmit power (uplink and downlink) by call type cell throughput RNC throughput QoS statistics for packet data average call hold time average mobility of users per cell average range of users in a cell. Figure 10 Typical Key Statistics SC2804/S2/v1.1. © Wray Castle Limited. 2.22.


(67) Introduction to UMTS Optimization. SECTION 3. OPTIMIZING COVERAGE AND CAPACITY. © Wray Castle Limited. i.


(69) Introduction to UMTS Optimization. CONTENTS 1. Link Budgets 1.1 Load Factor 1.2 Load Factor and Noise Rise 1.3 Optimization Considerations for Load Factor 1.4 Mixed Traffic and Load Factor. 3.1 3.3 3.5 3.7 3.9. 2. Coverage and Capacity Optimization Issues 2.1 Coverage Solutions 2.2 Capacity Solutions 2.3 Adaptive Voice Channels 2.4 Secondary Scrambling Codes. 3.11 3.11 3.15 3.27 3.31. 3. Traffic Scenarios 3.1 Introduction 3.2 Uplink Limited Systems 3.3 Downlink Limited Systems. 3.33 3.33 3.33 3.33. 4. Evolving Radio Access Architecture 4.1 Rollout Architecture 4.2 Antenna Azimuths and Beamwidth 4.3 More Sectors or More Cells? 4.4 Use of Repeaters 4.5 Basic Considerations for Indoor Coverage. 3.35 3.35 3.37 3.39 3.41 3.51. 5. Exercise 1 – Urban Capacity and Coverage. 3.53. 6. Location Services (LCS) 6.1 Introduction 6.2 Quality of Service 6.3 Factors Affecting Accuracy of Location Information 6.4 Response Time 6.5 Cell ID Based Positioning Mechanism 6.6 Observed Time Difference Of Arrival (OTDOA) 6.7 Network-Assisted Global Positioning System (GPS). 3.57 3.57 3.59 3.61 3.63 3.65 3.69 3.79. 7. Propagation Modelling 7.1 Empirical Models 7.2 Deterministic Models 7.3 Comparing Models and Their Effects. 3.81 3.81 3.85 3.87. © Wray Castle Limited. iii.


(71) Introduction to UMTS Optimization. OBJECTIVES At the end of this section you will be able to: • • • • • • • • • •. perform link budget calculations to verify cell size and traffic load capabilities in mixed traffic scenarios describe the impact of coverage and capacity expected for a range of mixed traffic scenarios describe the conditions in which a cell may become uplink or downlink limited describe conditions in which a system may be coverage or interference limited describe how the rollout architecture for a UMTS network can be evolved to expand capacity and coverage discuss the merits of cell splitting and multicell sites discuss the merits of using repeaters to improve coverage describe how masthead amplifiers can be used to improve coverage and capacity in a UMTS system identify suitable propagation models and explain the need for accurate model tuning state the requirements for optimization of location capabilities in the radio access network. © Wray Castle Limited. v.

(72) Introduction to UMTS Optimization. 1. LINK BUDGETS A link budget must be performed in both the uplink and downlink directions. For GSM this only involves radio factors such as transmit power, receiver sensitivity, feeder losses and antenna gains. The aim is to find a maximum path loss that is acceptable in both the uplink and the downlink directions. For GSM, the result of this calculation is static since it is not altered by cell load. In UMTS the link budget is not static because it is affected by cell load. There are two related aspects to this: the fact that the technology is CDMA-based and also the need to support mixed traffic. In a link budget for a CDMA-based system, account must be taken of the interference present due to other users. This is a factor of serving cell load and also, to a lesser extent, of neighbour cell load. The resulting interference level is known as noise rise. It is necessary to allow a margin for noise rise when calculating the link budget. This margin is referred to as the interference margin. The noise rise is calculated from the load factor of a cell. The value of load factor is largely dependent on two factors: the channel processing gain and the required value of Eb/No at the receiver output. Both these factors will be different for different services with different QoS requirements. Thus a realistic value of load factor can only be achieved if realistic mixed traffic cases are considered. An important consideration for the optimizer will be the degree of correlation between the estimated traffic load used at the planning stage and the real traffic load when an optimization problem arises.. 3.1. © Wray Castle Limited. SC2804/S3/v1.1.

(73) Introduction to UMTS Optimization. Downlink link budget Uplink link budget. Maximum acceptable path loss Node B. UE. Radio Parameters. Interference Margin. Noise Rise. Load Factor. Mixed Traffic. Figure 1 Link Budget Inputs SC2804/S3/v1.1. © Wray Castle Limited. 3.2.

(74) Introduction to UMTS Optimization. 1.1. Load Factor. In practice the received signal power at a cell and at the UE contains both wanted channel data and unwanted interference. The theoretical maximum load on a cell would be when all the received power was wanted channel data. The load factor is the ratio of wanted power to unwanted power and is a measure of how close a cell is operating in relation to its theoretical maximum load. The calculation of uplink and downlink load factors differs slightly because of the relative positions of the transmitters and receivers. In the uplink direction the channels are transmitted from different locations, but are all received in the same location. This means that the effect of neighbour cells can be considered constant for all channels. In the downlink direction all channels are transmitted from the same location but received in different locations. The effect of neighbour cell interference varies as a result of the UE’s location and, ideally, this should be included in the load factor calculation. Additionally, a factor must be also allowed in the downlink to account for lack of orthogonality between variable-length codes in a multipath channel. Figure 2 provides expressions for uplink and downlink load factor calculation. Note that these expressions do not allow for a mixed traffic case as shown. However, this could be accounted for simply by summing the load factor estimate for each individual traffic type.. 3.3. © Wray Castle Limited. SC2804/S3/v1.1.

(75) Introduction to UMTS Optimization. η. =. + =. η. +. ν. η η. UL. = UL load factor. DL. = DL load factor. −α +. = =. +. ν. N = number of UEs in the cell N j = an individual UE W = chip rate Eb = energy per bit No = noise spectral density Rj = bit rate for UE j j. = activity factor for UE j. j. = orthogonality factor. j. = neighbour cell interference factor. Figure 2 Uplink and Downlink Load Factors SC2804/S3/v1.1. © Wray Castle Limited. 3.4.

(76) Introduction to UMTS Optimization. 1.2. Load Factor and Noise Rise. Noise rise is derived from both the uplink and the downlink load factors (η) in the following way: Noise rise =. 1 1–η. Noise rise is more usefully expressed in decibels for inclusion in the link budget as an interference margin; in which case the expression becomes: Noise rise (dB) =. –10log10(1 – η). Figure 3a shows the relationship between load factor and noise rise expressed in decibels. It can be seen that noise rise tends to infinity as load factor approaches 100%. It is not advisable to plan a system with very high load factors. The shape of the curve indicates that at high load factors small changes in load give rise to dramatic changes in noise rise. A system planned to carry such loads would require an impossibly high interference margin or it would suffer extreme cell breathing effects. This is perhaps most graphically illustrated when looking at a linear representation of the curve as shown in Figure 3b. If the maximum load factor is planned to be in the region of 60% to 80% then the curve is relatively flat. A system planned in this way requires a more manageable interference margin leading to achievable link budgets. In addition, it should show minimal cell breathing up to the intended cell capacity limits.. 3.5. © Wray Castle Limited. SC2804/S3/v1.1.

(77) Introduction to UMTS Optimization. 18 16 14 12 10 Noise Rise (dB) 8 6 4 2 0 0%. 20%. 40%. 60%. 80%. 100%. Load Factor ( ). Figure 3a Load Factor and Noise Rise (Logarithmic). 50. 40. 30. Noise Rise 20. 10. 0. 0%. 20%. 40%. 60%. 80%. 100%. Load Factor ( ). Figure 3b Load Factor and Noise Rise (Linear) SC2804/S3/v1.1. © Wray Castle Limited. 3.6.

(78) Introduction to UMTS Optimization. 1.3. Optimization Considerations for Load Factor. At rollout a UMTS network will have a relatively small number of subscribers, who are not likely to make full use of high-rate data services. The operator’s aim at this stage will be to maximize coverage. Capacity in the network is unlikely to be a problem. Therefore it makes sense to select a fairly low load factor as a basis for coverage planning with macro cells only. Consider Figure 4. A load factor of 50% gives rise to a 3 dB noise rise. Including this as the interference margin in the link budget places a small, but still significant, limitation of maximum acceptable path loss. For example, if the operator wished to provide contiguous coverage in an urban area offering at least 144 kbit/s to class 3 UEs, a typical link budget might suggest a maximum acceptable path loss of about 145 dB. This can be interpreted in terms of cell radius using, for example, the COST231-Hata model. When not considering the interference margin this gives a cell radius of about 1.2 km. When allowing for a 50% load factor it is necessary to add another 3 dB interference margin. This reduces cell radius to 1 km. The 50% load factor would be enforced by the Call Admission Control (CAC) policy in the RNC. As traffic levels rise in the network, the cell load factor limit will begin blocking calls with a resulting fall in grade of service. Simply increasing the permitted load factor to alleviate this is not a sensible solution. For example, if the CAC policy was modified to allow a load factor of 75%, then noise rise would be increased to 6 dB. When factored into the link budget as interference margin cell radius is reduced to approximately 800 m at busy times. This could leave coverage gaps in the network. This could be dealt with by the introduction of either in-fill cells or a hierarchical cellular architecture incorporating micro cells. Micro cells used simply to absorb traffic load rather than provide extended coverage could be planned on the assumption of high load factors. Typical load factor figures for macro cells would be in the range 50% to 60%. This gives a good compromise between maximizing coverage potential and maintaining a reasonable traffic load. Micro cells are added with less emphasis on cell radius and more emphasis on capacity. Typical load factors for micro cells could be in the region of 75% to 80%.. 3.7. © Wray Castle Limited. SC2804/S3/v1.1.

(79) Introduction to UMTS Optimization. Example: 144 kbit/s, urban area, class 3 UE Max. path loss 145 dB. Load factor = 0% Noise rise = 0 dB Cell radius 1.2 km. Using COST231-Hata. Load factor = 50% Noise rise = 3 dB Cell radius 1 km. Noise Rise (dB). 6 3 50%. 75%. 100%. Load Factor ( ). Load factor = 75% Noise rise = 6 dB Cell radius 800 m. Figure 4 Load Factor Illustration SC2804/S3/v1.1. © Wray Castle Limited. 3.8.

(80) Introduction to UMTS Optimization. 1.4. Mixed Traffic and Load Factor. It can be seen from the load factor equations that Eb/No requirements for a particular service contribute to determining the load factor. The output Eb/No requirement itself is dependent on the service type and the error protection being applied in the channel. For example, a typically allowed figure for a standard voice service would be 5.5 dB, whereas high-rate data is often taken to be much lower, perhaps as low as 1.5 dB or even 1 dB. The reason for this low Eb/No figure is the assumed use of more powerful error protection schemes such as Turbo coding and the relaxed delay constraints permitting retransmission. A lower Eb/No figure means that total cell throughput can be higher for a given load factor. The mobility and the geographical location of the UE may also influence Eb/No requirements because the prevailing channel conditions will have an impact on error characteristics. Another important factor is the level of neighbour-cell interference contribution. This is usually assumed to be higher in macro cells than in micro cells. This is because micro cells tend to be sheltered by street canyons and therefore suffer less from neighbour-cell interference. Again, a lower interference factor means more cell throughput for a given load factor. Finally, it can also be assumed that a higher load factor can be tolerated on micro cells than on macro cells because coverage and ultimate cell range is less of a concern. The UE is likely to be much closer to a micro cell and therefore a larger interference margin can be included in the link budget. Figures 5a and 5b show calculations of cell throughput in kbit/s for different cell types and service types. Calculations have been performed for the macro cell with 50% and 60% load factors, and for the micro cell with 75% and 80% load factors. This illustrates the extremes of variation that are to be expected in usable cell capacity for UMTS cells. These calculations assume that all users in each scenario will be using the same service type. In reality, a cell could be expected to deal with a dynamic mix of service types, in which case the throughput will be some amalgam of the values shown here.. 3.9. © Wray Castle Limited. SC2804/S3/v1.1.

(81) Introduction to UMTS Optimization. Service. Bit Rate (kbit/s). Activity Factor. Eb/No (dB). Load Factor. N-cell Number Total Cell Interference of Throughput Factor Channels (kbit/s). Voice. 12.2. 0.6. 5.5. 50%. 1.3. 57. 695.4. Low packet data Medium packet data High packet data. 64. 0.9. 2.5. 50%. 1.3. 14. 896. 144. 0.9. 1.5. 50%. 1.3. 8. 1152. 384. 0.9. 1. 50%. 1.3. 3.7. 1420.8. Voice. 12.2. 0.6. 5.5. 60%. 1.3. 68. 829.6. 64. 0.9. 2.5. 60%. 1.3. 18. 1088. 144. 0.9. 1.5. 60%. 1.3. 10. 1440. 384. 0.9. 1. 60%. 1.3. 4.5. 1728. Low packet data Medium packet data High packet data. Figure 5a Macro Cell – Mixed Traffic. Service. Bit Rate (kbit/s). Activity Factor. Eb/No (dB). Load Factor. N-cell Number Total Cell Interference of Throughput Factor Channels (kbit/s). Voice. 12.2. 0.6. 5.5. 75%. 1.1. 101. 1232.2. Low packet data Medium packet data High packet data. 64. 0.9. 2.5. 75%. 1.1. 27. 1664. 144. 0.9. 1.5. 75%. 1.1. 15. 2160. 384. 0.9. 1. 75%. 1.1. 6.7. 2572.8. Voice. 12.2. 0.6. 5.5. 80%. 1.1. 108. 1317.6. 64. 0.9. 2.5. 80%. 1.1. 28. 1792. 144. 0.9. 1.5. 80%. 1.1. 16. 2304. 384. 0.9. 1. 80%. 1.1. 7.1. 2726.4. Low packet data Medium packet data High packet data. Figure 5b Micro Cell – Mixed Traffic SC2804/S3/v1.1. © Wray Castle Limited. 3.10.

(82) Introduction to UMTS Optimization. 2. COVERAGE AND CAPACITY OPTIMIZATION ISSUES Coverage and capacity are closely linked in UMTS; nevertheless, it is possible to consider independent optimization strategies for each characteristic. In some cases benefits arising from successful optimization activity may result in improvements to both coverage and capacity, but even here it is possible to weight the effect to influence one or the other more noticeably. 2.1. Coverage Solutions. Coverage is likely to be of prime concern when a network is in the rollout phase. The main limiting factor will be the low transmit powers from a UE, most UEs being class 4 with a maximum output power of 21 dBm (0.125 W). This, coupled with an operating frequency in the region of 2 GHz, means a restricted uplink power budget. Well-established radio techniques and some CDMA-specific techniques can be used to improve coverage. These include: • antenna height • antenna gain/types • antenna alignments • low noise amplifiers • repeaters • soft handover gain 2.1.1. Antenna Solutions. Rollout Node Bs will be predominantly macro cells with antennas mounted relatively high compared to average building height. When such cells are used to maximize coverage they will probably be unbalanced such that the potential downlink radius is significantly greater than the uplink radius. This means that different antenna gains need to be used to balance the link. A common approach is to use omni transmit and sector receive over three sectors. Optimization attention will be focused on uplink antenna types, gains and alignments to maximize coverage and minimize interference. Close attention should be paid to simulation of performance effects caused by antenna installation errors that are within the tolerances set for site build and acceptance. It may also be worth considering higher gain antennas, perhaps with more than three sectors.. 3.11. © Wray Castle Limited. SC2804/S3/v1.1.

(83) Introduction to UMTS Optimization. Antenna Coverage Improvements antenna configuration (omni transmit) antenna type antenna gain antenna alignment build tolerances. Weak uplink link budget. Node B. Unbalanced downlink link budget. UE Typically class 4 21 dBm (0.125 W). Figure 6 Antenna Coverage Solutions SC2804/S3/v1.1. © Wray Castle Limited. 3.12.

(84) Introduction to UMTS Optimization. 2.1.2. Low Noise Amplifiers (LNA). The use of Low Noise Amplifiers (LNA) is a well established technique for boosting uplink power budget performance. These are sometimes referred to as Mast Head Amplifiers (MHA) or Tower Mounted Amplifiers (TMA). They reduce the noise figure at the input to the receiver, which helps to compensate for the low UE transmit power. The reduction in noise floor created by an LNA could also be used to increase capacity because it allows for more noise rise. 2.1.3. Repeaters. Repeaters may be used for coverage improvement in areas that are not likely to present high traffic loads. They should not be used where it is predicted that traffic load will increase significantly over time unless the site can be upgraded to a Node B with ease. If planned with care a repeater may also provide some increase in capacity. 2.1.4. Soft Handover Gain. While in soft handover the UE is benefiting from uplink and downlink spatial diversity in the link. This produces a gain usually referred to as soft handover gain. Soft handovers reduce overall capacity in a network because a call requires multiple channel resources. However, in areas where coverage is of prime concern it may be possible to reduce handover margins to increase the soft handover area.. 3.13. © Wray Castle Limited. SC2804/S3/v1.1.

(85) Introduction to UMTS Optimization. Low Noise Amplifiers (LNA) reduce receiver noise floor boost uplink link budget increase capacity. Repeaters low traffic or rural areas in-building coverage cheaper than new Node B could provide some capacity benefits. Weak uplink link budget. Node B. UE Typically class 4 21 dBm (0.125 W). Figure 7 Low Noise Amplifiers and Repeaters SC2804/S3/v1.1. © Wray Castle Limited. 3.14.

(86) Introduction to UMTS Optimization. 2.2. Capacity Solutions. As a network matures the customer base will increase, as will the range of services offered to subscribers. An early and very important function for optimization teams will be to evolve the radio access network from a coverage-oriented design towards a capacity-oriented design. This will involve a mixture of architectural changes and the introduction of new features as they become cost effective. This will include: • use of more frequencies • use of UMTS Time Division Duplex (TDD) mode • in-fill cells • Hierarchical Cell Structures (HCS) • indoor coverage solutions • more sophisticated 2G interworking • antenna configuration changes • antenna orientation/downtilt • adaptive voice channels • secondary scrambling codes • Multi-User Detection (MUD) • transmit diversity 2.2.1. More Spectrum. Most UMTS operators have licences for enough spectrum to operate more than one FDD carrier pair. Typically an operator may be able to implement two or three carrier pairs. These could be used in a variety of ways, but essentially an operator may choose to use then as independent cell layers or to provide more capacity within a cell layer. Overall the highest capacity will probably be achieved through the use of hierarchical cell structures partitioned by frequency. It is important for optimizers to bear in mind that different solutions may suit different locations and an operator can use different strategies in different geographical regions if appropriate. Even where UMTS operators have only one Frequency Division Duplex (FDD) carrier pair there may still be scope for spectrum sharing. This option would increase capacity and reduce infrastructure costs for the operators and is therefore worthy of consideration.. 3.15. © Wray Castle Limited. SC2804/S3/v1.1.

(87) Introduction to UMTS Optimization. Example UMTS Licence. TDD (x1). 5 MHz. FDD (x3 pairs). 5 MHz. 5 MHz. Used at rollout on macro cells. Progressively introduced as a micro cell or pico cell layer. 5 MHz. Progressively introduced as second carrier on macro cell sites or for a micro cell layer Progressively introduced as a micro cell or pico cell layer. Figure 8 Additional Radio Carriers SC2804/S3/v1.1. © Wray Castle Limited. 3.16.

(88) Introduction to UMTS Optimization. 2.2.2. UMTS TDD Mode. Many UMTS operators have licences that include spectrum for TDD mode radio carriers. Typically this will be a single carrier, but TDD mode is a very flexible technology solution. Although it is a UMTS technology the optimizer will need to treat it as a different radio access technology and integrate it as such. Potentially the cell sizes for a TDD mode cell and an FDD mode cell are the same; however, the TDD technology is more suited to non-symmetric data applications. This makes TDD mode a candidate technology for the implementation of pico cells and indoor coverage solutions. It may also be the preferable technology solution for special project cell where, for example, it may be desirable to stream high-quality video.. 3.17. © Wray Castle Limited. SC2804/S3/v1.1.

(89) Introduction to UMTS Optimization. Example UMTS Licence. TDD (x1). 5 MHz. FDD (x3 pairs). 5 MHz. 5 MHz. Used at rollout on macro cells. Progressively introduced as a micro cell or pico cell layer. 5 MHz. Progressively introduced as second carrier on macro cell sites or for a micro cell layer Progressively introduced as a micro cell or pico cell layer. Figure 8 (repeated) Additional Radio Carriers SC2804/S3/v1.1. © Wray Castle Limited. 3.18.

(90) Introduction to UMTS Optimization. 2.2.3. In-Fill Cells and HCS. Ultimately, the need for more capacity will always lead to a need for more cells. The first step in this process may be to in-fill new cells between the macro cells of a rollout architecture. This will need considerable attention from the optimization team to target new capacity appropriately and minimize the potential negative impact on existing cells. As a network develops the new cells may be implemented as overlays on existing coverage. In this case parameters and procedures required for the effective operation of HCS will need to be introduced. These should be monitored and tuned by the optimization team.. 3.19. © Wray Castle Limited. SC2804/S3/v1.1.

(91) Introduction to UMTS Optimization. Coverage areas of rollout cells reduced with downtilt and pilot power reductions. Optimization needed to ensure new in-fill is beneficial not detrimental to network performance.. Rollout Node B. New in-fill Node B Rollout Node B. Rollout Node B. Figure 9 In-Fill Cells and HCS SC2804/S3/v1.1. © Wray Castle Limited. 3.20.

(92) Introduction to UMTS Optimization. 2.2.4. Interworking with 2G. Most operators are overlaying a new UMTS network onto a mature and (usually) well-optimized GSM/General Packet Radio Service (GPRS) 2G network. UMTS offers capabilities above a 2G network, but many of the offered services can be carried adequately on a 2G network; for example, voice or messaging services. Therefore, balancing the traffic load in the most appropriate way between the 2G infrastructure and the 3G infrastructure is an important optimization task. The main mechanism for this will be effective and appropriate settings of triggers for inter-RAT handovers, but it may also impact on admission control.. 3.21. © Wray Castle Limited. SC2804/S3/v1.1.

(93) Introduction to UMTS Optimization. Split traffic according to QoS requirements. 3G. 2G. Optimize handovers and reselections to account for QoS requirements. Figure 10 Interworking with 2G SC2804/S3/v1.1. © Wray Castle Limited. 3.22.

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