LTE Self-Organising Networks (SON): Network Management Automation for Operational Efficiency

Covering the key functional areas of LTE Self-Organising Networks (SON), this book introduces the topic at an advanced level before examining the state-of-the-art concepts. The required background on LTE network scenarios, technologies and general SON concepts is first given to allow readers with basic knowledge of mobile networks to understand the detailed discussion of key SON functional areas (self-configuration, -optimisation, -healing). Later, the book provides details and references for advanced readers familiar with LTE and SON, including the latest status of 3GPP standardisation.

Based on the defined next generation mobile networks (NGMN) and 3GPP SON use cases, the book elaborates to give the full picture of a SON-enabled system including its enabling technologies, architecture and operation. ”Heterogeneous networks” including different cell hierarchy levels and multiple radio access technologies as a new driver for SON are also discussed.

• Introduces the functional areas of LTE SON (self-optimisation, -configuration and –healing) and its standardisation, also giving NGMN and 3GPP use cases
• Explains the drivers, requirements, challenges, enabling technologies and architectures for a SON-enabled system
• Covers multi-technology (2G/3G) aspects as well as core network and end-to-end operational aspects
• Written by experts who have been contributing to the development and standardisation of the LTE self-organising networks concept since its inception
• Examines the impact of new network architectures (“Heterogeneous Networks”) to network operation, for example multiple cell layers and radio access technologies

• Language: English
• Publisher: Wiley
• Release date: Dec 28, 2011
• ISBN: 9781119963028

Book preview

To Leevi, Lina-Maria and Terja

In memory of Dr.-Ing. Hugo Sanneck (1932-2011)

To Nikos and Marika

Foreword

When we designed the first generation of digital mobile networks, the concept of a self-organising network (SON) was not in focus. Now, with hindsight we can say that a lot of self-organising features already exist such as power control, handover between cells and efficient customer management based on central administration of SIM cards.

Why has the vision of self-organising networks gained importance in our industry? There are two obvious drivers: cost reduction and increasing complexity. Network operators urgently need much more automation in order to efficiently manage large networks consisting of tens of thousands of base stations with hundreds of settings each. Optimising several network layers providing a multitude of customer services with high service quality would be highly complex and labour intensive, and therefore would be very costly without the mechanisms and intelligence in our networks to ‘organise themselves’.

While it was common practice in the early years with much smaller mobile networks to execute many tasks manually on site, now network operators are able to handle all operational activities remotely from one or few central locations. This trend was enabled to a large extent by the significant progress in the IT industry.

In order to guide the industry in developing automation functionality that is relevant for operators Deutsche Telekom together with their partner in the NGMN Alliance (Next Generation Mobile Networks) have taken the initiative to drive ‘Self-Organising Networks’ (SON).

Within the vision of SON the operators have defined the most relevant use cases for the automation of operational tasks: typically, those tasks that require significant manual effort, or tasks that are highly complex in nature, and are therefore prone to error. NGMN presented these use cases to the vendor industry, and 3GPP standardisation bodies were requested to develop and standardise respective self-organising solutions.

There are some prominent examples of SON solutions which are already implemented today. For instance the ‘Plug-and-Play’ deployment of a base station requiring only the physical installation on sites, where all complex and specific configuration settings as well as software management are executed automatically. Similarly the ‘Automatic Neighbour Relationship Configuration’ (ANR) reduces effort but improves also the perceived network quality.

With LTE we have a great opportunity to bring the value of SON into our networks. But the potential and ambition clearly includes legacy networks such as UMTS and GSM also.

This book is an excellent introduction to the world of SON for technicians in research as well as developers in the industry providing solid knowledge and motivation to push SON solutions forward in the telecommunications sector.

Dr. Klaus-Jürgen Krath

Deutsche Telekom AG

Preface

Mobile network operators will meet many challenges in the coming years. It is expected that the number of people connected, wireline and wireless, will reach five billion by 2015. At the same time, people use more wireless services and they expect similar user experience to what they can now get from fixed networks. Because of that we will see a hundred-fold increase in network traffic in the near future. At the same time markets are saturating and the revenue per bit is dropping.

To meet the increase in demand for a wide range of content services with high bit rate requirements, the Third Generation Partnership Project (3GPP) is standardising the next generation of cellular networks called Long Term Evolution (LTE). When LTE is introduced by the operators, it leads to parallel operation of LTE together with existing 2G and 3G networks that are not phased out for a long time to come. LTE represents a major advance, designed to meet needs for high-speed data and media transport as well as high-capacity voice support for carriers. This includes support for new types of network elements, such as relay and femto nodes, and different cell layers. Due to that fact, a significantly increased number of base stations is required to assure coverage and capacity, all of which have to be managed properly. Also many complex radio network parameters have to be maintained and optimised.

Mobile Network Operators' vital interest is to minimise operational effort and cost. The concept of Self Organising Networks (SON), introduced by the Next Generation Mobile Networks (NGMN) alliance on 2007, is a key enabler for simplifying operation and maintenance in next generation mobile networks. SON aims at:

Reducing operating cost by reducing the degree of human intervention in network design, build and operate phases.

Reducing capital expenditure by optimising the usage of available resources.

Protecting revenue by reducing the amount of errors introduced by humans.

This is accomplished by simplifying operational tasks through automated mechanisms such as self-configuration, self-optimisation and self-healing. SON can be seen as an approach in which many functions which have earlier been done manually as a part of the (‘offline’) network planning and optimisation tool chain are now moved to be executed (‘online’) in the network elements and their OAM system.

While NGMN has set requirements for SON use cases, 3GPP has made technical specification and standardisation for them. However, not all SON functions require standardisation. In this book, both 3GPP-standardised SON use cases and functions, but also functionality not using standardised interfaces or signalling is discussed.

The book focuses on LTE as for this new technology SON features can be designed from the start and thus take full effect. Where applicable, however, similar concepts are described for 3G and 2G. As the main operational challenges are seen in the management of radio networks, the focus of the book is on radio access. The end to end view is touched by covering some of the core network and transport (backhaul) aspects. Core network aspects are treated in a separate chapter and related transport aspects are treated where relevant, however, self-organisation of the transport network as such is beyond the scope of the book.

The book is organised as follows. The network management challenges that demand automation and thus SON are discussed in Chapter 1. In addition, the motivation behind applying SON for LTE networks is discussed.

An overview of 3GPP as well as LTE requirements and specifications are given in Chapter 2. Also LTE radio access network scenarios and their evolution are covered.

In Chapter 3, a vision for SON addressing the foreseen challenges is discussed and NGMN and 3GPP SON use cases presented. Typically, when benefits of SON are discussed, the first benefit is seen in saving in operational expenses. However, this is not the only benefit SON offers; SON will also have impact on for example, capital expenses and network quality of service. Such SON business benefits for selected use cases are discussed in Chapter 3. In addition, Chapter 3 presents the foundations for SON, that is, technologies on which SON is based as well as previous research projects, architectural considerations for SON-enabled systems and the operational and technical challenges of SON.

The operational life-cycle of a mobile network consists of design, build and operation/maintain phases. The two latter phases can be automated by SON. The build phase can be automated and thus simplified through auto-connectivity, -commissioning, and dynamic radio configuration (Chapter 4). In the operational phase, self-optimisation and self-healing functions automatically change the network configuration based on the network performance and incidents in the network. Self-optimisation and self-healing are discussed in Chapters 5 and 6, respectively.

Minimisation of Drive Tests (MDT) functionality is planned for 3GPP Release 10. MDT supports autonomous collection of UE measurements and positioning of the UE. This information, together with information available in the radio access network can be used to visualise in detail the network performance and health. Thus MDT, described in Chapter 7, is an enabler for both self-optimisation and -healing of the network. NGMN use cases exist also for core networks. Here, SON concepts are also applicable and closely linked to SON in radio access (Chapter 8).

When many different SON functions are active in a system, interactions between them may occur. Therefore mechanisms to operate SON at a system level are needed. This includes mechanisms for preventive coordination between different SON functions to avoid conflicts on one hand but assure efficient operation (parallelisation) on the other hand. Additionally, it is crucial that human operators can interact with the SON-enabled system and stay in control. SON operation is discussed in Chapter 9.

Chapter 2 already introduced network scenarios relevant for SON. A particular scenario is a ‘Heterogeneous Networks’ scenario in which a network is made of several different cell types, technologies or layers. Such a network will impose stronger requirements for SON with regards to scalability, interoperability but also improved functionality. Therefore a separate chapter, Chapter 10, is dedicated to SON for heterogeneous networks.

Finally, Chapter 11 gives an outlook to future SON related topics, such as cognitive radio networks, and novel technological enablers for future SON.

Concepts to automate network operations have recently gained significant interest to improve an operator's cost position. The book addresses particularly the novel SON components in the network elements and the OAM system. While a number of research publications (in addition to NGMN requirements and 3GPP standards material) have appeared, no comprehensive single source on the LTE self-configuration and -optimisation topic has been available. While including the latest status in 3GPP, the book aims at providing a comprehensive picture of a SON-enabled system.

For more information, please visit the companion website, www.wiley.com/go/Hamalainen.

List of Contributors

Tobias Bandh

Gyula Bódog

Yves Bouwen

Christoph Frenzel

Jürgen Goerge

Seppo Hämäläinen

Anssi Juppi

Risto Kauppinen

Raimund Kausl

Ilkka Keskitalo

Krzysztof Kordybach

Jaroslaw Lachowski

Daniela Laselva

Andreas Lobinger

Henrik Martikainen

Szabolcs Nováczki

Klaus Pedersen

Johanna Pekonen

Miikka Poikselkä

Simone Redana

Dirk Rose

Henning Sanneck

Cinzia Sartori

Christoph Schmelz

Markus Stauffer

Paul Stephens

Clemens Suerbaum

Péter Szilágyi

Haitao Tang

Malgorzata Tomala

Eddy Troch

Ingo Viering

Achim Wacker

Richard Waldhauser

Bernhard Wegmann

Jeroen Wigard

Volker Wille

Osman Yilmaz

Acknowledgements

The editors would like to acknowledge all the colleagues who enthusiastically contributed to the writing of the book (cf. ‘list of contributors’ above) not only as authors but also reviewers. SON is a very diverse technical area requiring many different competences in the radio and distributed systems fields. Hence, we are very grateful that it has been possible to bring together such a great team of close to 40 contributors from Nokia Siemens Networks, partner companies and universities.

We would like to thank the following colleagues for their help to set up the book project and valuable comments during the book's review process: Kari Aaltonen, Guillaume Decarreau, Richard Fehlmann, Nadine Herold, Günther Horn, Matthias Kaetzke, Patrick Marsch, Peter Merz, Wolf-Dietrich Moeller, Olaf Pollakowski, Raphael Romeikat, Mikael Rutanen, Dariusz Tomecko, Ville Tsusoff and Marcin Wiczanowski.

We appreciate the fast and smooth editing process and all help provided during the process of writing the book by Wiley-Blackwell and in particular: Mariam Cheok, Richard Davies, Lynette James, Abhishan Sharma, Sophia Travis and Mark Hammond.

We are grateful to our families and contributors' families for their understanding and patience during the long evenings spent when writing and editing the contents of the book.

Our employer made it possible to write this book by providing support and encouragement during the process of writing and editing. Therefore special thanks are for Nokia Siemens Networks.

Finally we are grateful for the interactions with the SON research and 3GPP SON standardisation community comprising mobile network operators, vendors and academia. The industry-wide effort to make SON happen has been clearly the basis for this book.

We welcome any proposals and suggestions for improvements of the contents of the book in forthcoming editions as well as pointing us to any possible mistakes. The feedback is welcome to the editors' e-mail addresses: [e-mail], [e-mail] and [e-mail].

List of Abbreviations

Chapter 1

Introduction

Cinzia Sartori, Henning Sanneck, Jürgen Goerge, Seppo Hämäläinen and Achim Wacker

The number of mobile subscribers has impressively increased during the last decade; at the same time wireless data usage continues to accelerate at an unprecedented pace even when (for developed countries) subscriber numbers reach saturation.

With the adoption of the Global System for Mobile Communication (GSM), mobile phones have become indispensable devices for voice communication and, nowadays, mobile networks are available for 90% of the world population. However, GSM was mainly designed for carrying voice traffic and some data capability was only added subsequently. The ‘mobile data explosion’ is a quite recent phenomenon driven by the introduction of the ‘Third Generation’ (3G) mobile system with Wideband Code Division Multiple Access (WCDMA), High Speed Packet Access (HSPA) and its enhancements called High Speed Packet Access Plus (HSPA+). The introduction of HSPA has marked the beginning of the transformation from voice-dominated to packet data-dominated mobile networks. These 3G evolution technologies are crucial to allow upgrading the network at relatively low costs and hence those technologies will be still important for a long period of time to come. However, it is clear that only a new Radio Access Technology (RAT) comprising a new air interface together with a new network architecture can cope with the described data explosion in the longer term. Long-Term Evolution (LTE; Holma and Toskala, 2011) is this technology which at the time of writing had been rolled out and put into commercial use in several countries already. Chapter 2 introduces the key technical concepts and radio access network scenarios of LTE.

The exponential growth of mobile broadband traffic is certainly caused by both, the increasing demand for known and new data services, such as mobile Internet access, social networking, location-based services/personal navigation, and so on, and the data processing and storage capabilities of state-of-the-art terminals, such as smartphones and, most recently, tablets (Figure 1.1). Such ‘always-on’ devices used by humans as well as network usage by machines (Machine to Machine; M2M) also put strong requirements on the capabilities of the network control plane.

Figure 1.1 Data volume growth. Source: Nokia Siemens Networks.

As a next step, the use of tablets may increase the demand for wireless video applications to a large extent and put tremendous stress on the wireless network infrastructure. This is the case, because high resolution displays and powerful processors enable the transmission of high-definition video. This, in turn, produces a demand for high data rates required ‘everywhere’ to satisfy the expectation of the end customers. Such ‘data hungry’ applications ask for more capacity and higher quality of service, which can only be satisfied with the introduction of LTE and its evolution called ‘LTE-Advanced’ (LTE-A).

To cope with such a huge demand for data traffic transmission, the wireless network operators need to significantly upgrade their networks and use these resources most efficiently. Traditional methods like macro site ‘densification’, along with improved receivers and higher order sectorisation, will not be fully sufficient to provide the desired capacity for the predicted traffic growth. The deployment of small cells as an additional layer to the macro layer is definitely the most promising solution for building improved spectral efficiency (and thus capacity) per area. Thus, the migration from macro-only to Multi-Layer topology as part of a ‘Heterogeneous Network’ scenario are expected to further accelerate in the near future. Also, LTE will run for a long period of time in parallel with existing 2G and 3G networks (Multi-RAT).

The described requirements for wireless service providers to upgrade their networks, to deploy LTE and to integrate their existing RATs have the effect that the network infrastructure as a whole will be rather complex and heterogeneous. Thus, operators face significant operational challenges in terms of work effort and cost. Unfortunately, those costs will not be compensated by additional revenue due to the decreasing average revenue per user (caused by pricing schemes like e.g. flat rates, induced through fierce competition in the market). Hence, the cost position as a vital interest of operators, in particular the operational expenses (OPEX), has gained much more attention recently. Especially in the early deployment phase, the efforts to set up and optimise the network are significant and traditionally lead to substantial delays before an optimal and stable system setup can be reached. In order to minimise such delays and in general reduce the network operation expenses, the Self-Organising Networks (SON) concept is considered to be an integral part of LTE.

1.1 Self-Organising Networks (SON)

The concept of SON became frequently used after it was adopted by the Next Generation Mobile Networks (NGMN) alliance to address challenges foreseen due to management of several radio access technologies along with the LTE network introduction. Chapter 3 provides an introduction to the SON vision (Section 3.1), key SON concepts and benefits and their foundations.

One of the aims of operators is to keep their operational burden at the currently existing level, that is, manage the multi-RAT (including LTE), multi-layer infrastructure as described above with their existing operational staff and cost structure. Operators have to maximise their return on investment, they need to optimise the resource utilisation in order to minimise their huge, necessary investments hence, efficiency is essential in order to be able to manage the additional network without increased workforce.

Network operation today is based on a centralised Operation, Administration and Maintenance (OAM) architecture. Configuration and optimisation of network elements is performed centrally from an OAM system (also called the Operations and Maintenance Centre: OMC) with support of a set of planning and optimisation tools. Planning and optimisation tools are typically semi-automated and management tasks need to be tightly supervised by human operators. This manual effort is time-consuming, expensive, error-prone and requires a high degree of expertise (Laiho et al., 2006).

Increased automation of network operations is seen as a proper means to cope with the described rising complexity of the network infrastructure in order to utilise deployed network resources in an optimised way. At the same time automation aims at:

keeping the operational effort at an acceptable level;

protecting the network operation by reducing the probability of errors during the overall process of rolling out a network and the permanently ongoing process of managing the network;

speeding up operational processes.

Self-organisation is an advanced mechanism to enable such automations. It is crucial that automated features are properly integrated with the existing operator processes and embedded into the architecture of the overall OAM tool chain. Automation is achieved by adding (SON) features to network equipment which facilitates network operation processes and delivery of professional services related to the network. Hence SON is a contributor to the ‘operability’ and ‘serviceability’ characteristics of a network.

3GPP has created the actual SON standards upon NGMN long-term objectives for a ‘SON-enabled mobile broadband network’ by defining the necessary use cases, measurements, procedures and open interfaces to support better operability in a multi-vendor environment. SON standardisation is still an ongoing activity (Figure 1.2). SON standardisation has started with LTE in 3GPP Release 8 and continued in Release 9 and 10 (Release 10 was completed in June 2011). Release 11, which will contain additional SON features and enhancements to existing ones, is in definition phase at the time of writing this book.

Figure 1.2 Roadmap for SON standardisation in 3GPP.

SON Use Cases (NGMN, 2008), cf. Section 3.2, are categorised into functional areas along the key OAM areas of configuration, optimisation and troubleshooting (cf. Figure 1.3):

Figure 1.3 SON use case examples.

Self-Configuration (Chapter 4);

Self-Optimisation (Chapter 5) including traffic steering between different type of radio resources; and

Self-Healing (Chapter 6).

A common characteristic is that the degree of ‘human-in-the-loop’ for OAM use cases is reduced as much as possible reaching even fully ‘closed loop’ automation for some of the use cases.

‘Minimisation of Drive Tests’ (MDT) functionality has been specified in 3GPP Release 10 for LTE and Universal Terrestrial Radio Access Network (UTRAN). MDT addresses the issue that often drive tests have to be executed to monitor and assess mobile network performance. Such drive tests are very expensive since the actual testing needs significant human operator involvement. Key characteristics of MDT are measurements collected on User Equipments (UEs), which may contain location information, thereby allowing to have a much more fine-grain view of a cell's performance. Because such a view is useful not only for a human operator but also for the automated SON functions, MDT is considered to be an important enabler for SON. MDT is discussed in detail in Chapter 7.

SON research and standardisation is mainly focused on the radio access domain, due to its intrinsic complexity (high number of widely distributed network elements) and thus significant cost share of the overall network infrastructure and its operations. Nevertheless, SON for Core Networks (Chapter 8) is also relevant from the perspective of properly configuring and optimising the network end-to-end. Note that backhaul aspects contributing to the end-to-end view are treated where relevant in Chapters 4–6 which discuss the SON functional areas.

Figure 1.3 shows some examples for SON use cases. There exists a significant number of different SON use cases which have partially conflicting goals, overlapping input or output parameters. Examples for such SON function interactions as well as technical solutions to control the interactions are discussed as the main topic for SON Operation in Chapter 9.

Like mentioned above, on one hand LTE needs to be integrated with existing RATs; on the other hand even the resource capabilities of LTE macro cells will not be sufficient in the long term but need to be complemented by smaller cells for capacity. In Heterogeneous Networks (cf. Figure 1.4) operators will have to deal with handovers in inter-technology and macro/femto scenarios; interference management of macro/pico and macro/femto is definitely an outstanding issue. At the same time network capacity needs to be optimised via an efficient utilisation of all available resources (multi-RAT, multi-layer) while assuring desired end user experience with appropriate Quality of Service (QoS) and Quality of Experience (QoE). SON for Heterogeneous Networks and related challenges are described in Chapter 10.

Figure 1.4 Heterogeneous Networks.

While most of the concepts of the ‘classical’ SON use cases are now getting assessed and operators start their deployment, the SON concept keeps evolving by integrating new use cases and solutions based on existing and novel technologies. Chapter 11 describes that evolution which may lead to a true ‘Cognitive Network’.

1.2 The Transition from Conventional Network Operation to SON

While SON concepts are very appealing for network operators on the one hand, on the other hand they need to be carefully integrated into existing tool chains realising OAM processes. Hence, in the following, basics of ‘conventional’ network rollout and operation are introduced and the potential automation possibilities, which are the targets for SON, are discussed.

Business targets must be broken down to an optimal deployment of the network infrastructure and to an optimised setting of every individual parameter in each network element. Therefore, operators typically employ a layered set of tools as depicted in Figure 1.5. On the left hand side the classes of tools are depicted. The corresponding department in an operator's organisation, time scale of resulting plans, and class of algorithms and parameters are listed on the right hand side.

Figure 1.5 Model of a layered OAM tool chain.

Traffic forecast, capacity planning and site planning translate above business targets to a proper deployment of network elements. They take bordering conditions into account like available budget, sites/transmission links and their costs. The timescale for these plans is in the year range, but can go down to monthly intervals. Scope of the plans is usually the entire network. Tools, algorithms and parameters do not depend on specific suppliers of the network elements, so these tools are generic and very stable over time.

Radio, transport and link planning and optimisation processes periodically try to optimise the different domains of the network. Tools evaluate performance data, run simulations and provide, for example, a set of optimised parameters, or a plan for optimised roll out sequence of the network as a result. Typically the plans have a time horizon of months down to days. Scope of the plans usually is the overall network, a large region of a network, or certain RATs. Planning and optimisation uses vendor independent, generic algorithms to simulate wave propagation for example. Those algorithms typically operate on standardised parameters. Since neither algorithms nor parameters depend on the vendor-specific implementation of the network elements, those algorithms and tools are stable as long as basic principles of call processing for a RAT do not change.

Many operators have a strict separation between planning departments and departments that operate the live network. The interface between planning departments with their vendor-agnostic tools for network or service management and the network operations department with mainly vendor-specific tools (Element Managers (EM), Domain Managers (DM)) is very often established by a kind of element abstraction layer.

On the one hand the element abstraction layer acts as central repository, which is used to collect, store and distribute all parameters in the network, that is, all standardised parameters and many or even all vendor specific parameters of the overall multi-technology, multi-vendor network. Usually, the element abstraction layer does not understand the semantics of vendor-specific parameters, so the element abstraction layer is not able to check the correctness of vendor-specific parameters, nor is this layer able to optimise them. However, this repository is needed to transfer network data in a coordinated way between planning department (or more generally: departments concerned with network management tasks) and network operations department. According to the OAM reference architecture as defined by 3GPP SA5 this repository function would be ‘counted’ to the Network Management (NM) layer.

On the other hand the element abstraction layer is used to map standardised parameters between the vendor-specific representation used by network elements and the generic information models used by NM functions. The mapping between vendor specific data and generic data has to be modified most probably with any new release of network elements. Also new features, for example, in planning tools, require mapping to additional parameters. Thus maintenance effort for those mappings is high.

In the context of SON NM tools that collect alarms and performance data in multi-vendor, multi-technology networks act as an element abstraction layer for Fault Management (FM) and Performance Management (PM). They collect the data from the vendor-specific DMs, and provide an abstracted view for the higher-level, generic tools.

According to the 3GPP OAM reference architecture the mapping is part of the DMs where the so-called ‘northbound interfaces’ (Itf-N) of the DM act as facade to hide this mapping from the NM layer. Tools of the element abstraction layer often use standardised interfaces (like those from 3GPP or TMF) to exchange data with the vendor-specific network or Domain Management Systems (DMS). Besides automated collection of alarm and performance data, already these interfaces allow automated exchange of Configuration Management (CM) data and remote control of the DMs and network elements by the tools of the element abstraction layer to a certain extent. However, in reality this mapping of CM data often is not performed by the DMs but by a dedicated tool that combines mapping and repository. Communication towards the DM and EM is then performed by proprietary interfaces.

In context of the introduction of SON it is worth emphasising that this element abstraction layer not only transforms information models. It often currently defines a strict boundary between departments and between different time scales of operation. Thus, introduction of SON is not only a technical challenge, but also might influence on the overall organisational and operational processes, as SON cycles could go beyond these two strictly separated departments.

Vendor-specific Element Management System (EMS) and DMS are able to handle most vendor-specific parameters, check their correctness and optimise them to a certain extent. The time scale of usage varies from days down to hours. Usually, the spatial scope of these tools is a vendor's radio network (or single radio technology) in a larger region. Definitely, those tools must be adapted with each new release of network elements.

Local craft/maintenance terminals, site managers, and so on are used on-site to commission and install network elements. They are able to manipulate the configuration of hardware and boards down to the lowest possible level. Those tools usually do not have a standardised interface to higher-level Network Management Systems (NMS). Although those tools are able to handle all data of a Network Element, they are usually not able to perform any kind of optimisation. Most of the time, these tools are specific to a certain type of Network Element, thus a field engineer has to cope with a multitude of such terminals. Local craft terminals typically connect to exactly one network element at a time.

Network elements are subject to management and in the past were not actively managing themselves at all. Even in the past, the network elements already implemented some kind of ‘low-level’ troubleshooting and optimisation. For example, the 3G UTRAN uses a hierarchy of layered optimisations: a radio network planning department provides quality values via a DM (e.g. for the block error rate, BLER) of an UTRAN cell to the Radio Network Controller (RNC), for example, once a month. Based on this input, the RNC uses proprietary algorithms to calculate optimised target values for the ‘signal to interference plus noise ratio’ (SINR) for each bearer connection under its control (outer loop power control, timeframe 10–100 ms) and sends this optimised SINR values to the WCDMA base stations (NodeBs). The NodeB in turn uses the given target SINR of outer loop power control as a bordering condition for its inner loop power control to adjust the actual transmit power for the individual connections every 666 ms. This example shows the degree of automation in Radio Resource Management (RRM) which should also be brought to the management of the network.

1.2.1 Automation of the Network Rollout

In order to maximise utilisation of invested capital, the number and location of base stations must be planned carefully. Coverage, capacity and quality must meet the business targets as well as regulatory obligations. Optimised deployment of the network is not only driven by the specifics of the air interface and utilisation of the available spectrum, but also depends on setting up a corresponding backhaul and aggregation network needed to route the traffic towards the core network. Also, long-term business processes like acquisition of base station sites (site lease) and site preparation with all the required construction and supplies such as electricity have to be taken into account. Further, the outcome of each step must be documented, for example, for proper payment of subcontractors and bookkeeping/inventory. Installation and commissioning of a base station as well as its registration for service are just small steps in this overall business process. A proper automation of this business process supports managing the overall project of rolling out a network.

Each individual step of the business process is a process (or ‘workflow’) of its own. Figure 1.6 shows the differentiation between the layer of the business process and the embedded workflows within the NM layer. This book focuses on the automation of the workflows in NM domain and element management and in the elements itself. Enterprise architecture and business process integration are not covered, except when northbound interfaces of domain management and NM are described.

Figure 1.6 Workflows for installation and commissioning a base station (BTS).

Bringing a base station on air means planning the corresponding parameters, installing the base station physically and configuring the software logically (commissioning). Installation and commissioning require field engineers with different skills, thus usually at least two site visits are necessary. Additionally, the commissioner needs to communicate with the planner in order to equip the base station with correct software and configuration data. Automation, which might include automated planning or planning on demand, may in most cases obsolete the site visit by the ‘commissioner’ resulting in bringing a base station on air faster, with fewer errors and with less workforce and thus significantly reduced costs. Chapter 4 discusses such ‘self-configuration’ concepts in detail.

1.2.2 Automation of Network Optimisation and Troubleshooting

Operators need to optimise revenue. This is the one, ultimate, business-level Key Performance Indicator (KPI). However, revenue not only depends on the network, but also on other instruments like marketing and sales, that is, attractive products at attractive prices, properly advertised with good customer relationship management. The best network does not help if the other instruments do not work. But also the opposite is true; even the best marketing and sales on their own will not generate satisfied customers.

Qualitatively, the overall performance of the network can be described by a ‘Super KPI’ like

(1.1)

equation

where the weights x, y, and z depend on the business targets of the operator as well as on specific area, maturity of the network layer, time of day, and so on. In the following, the different components of the overall performance indicator are introduced.

Coverage is required to allow customers to use mobile services on all relevant places. It also is important, for example, not to lose roaming subscribers to competitors. So coverage might be important even in areas where no significant traffic occurs.

Capacity is the ability of the network to carry traffic. It is important to note that only traffic translates into revenue, but not capacity as such. Providing capacity on areas without demand is waste of investment, while a shortage of capacity means losing traffic and thus revenue.

Good network quality is important to catch new customers and to reduce churn, although, quality does not immediately translate into revenue. Quality is similar in effect as marketing. Good quality in the long run will positively influence revenue, since customers are attracted. In contrast, bad quality will negatively influence revenue, which might be compensated by advertisement or lower tariffs.

Because expenses for equipment and operation are limited, already this initial, even very coarse analysis shows that conflicting targets exist. For example, from a traffic-only point of view, it might be better to invest in more capacity in the city instead of closing coverage holes in rural areas: better earning money in the city from 1000 roaming business travellers from abroad than to cover 1000 own subscribers who have flat-rates anyway. On the other hand, this strategy definitely would be perceived as ‘bad quality’ from the 1000 own subscribers' perspective and drive them to competitors. Also legal obligations to cover especially rural areas (e.g. with the high bandwidth capabilities of LTE) might be in conflict with this strategy.

Any optimisation and troubleshooting activity (manual or automated), central in the OAM system or decentral in network elements, must optimise for the overall performance of the network according to the business strategy of the operator. Optimisation refers here to the activity to bring the network performance from a performance operating point P1 to a point P2 (with P2 > P1) triggered by the demand to increase revenue from an existing investment. Chapter 5 introduces a range of use cases and their solutions in ‘self-optimisation’. Troubleshooting is in fact a similar activity, yet the trigger comes from addressing faults in the system. The system operates only at an inferior performance operating point P1 (again with P2 > P1) as opposed to a ‘normal’ operating point P2, which had been reached already before during fault-free network operation. Automated troubleshooting, also called ‘self-healing’, is introduced in Chapter 6.

If conflicting targets shall be optimised by different functions, those functions in the end must to be coordinated such way that overall performance is maximised. Not coordinating individual optimisation functions according to an overall strategy as, for example, given by a kind of ‘Super KPI’ might result in reaching local optima for individual functions, which might be far away from the global optimum. It also might result in ‘ping-pong’ and other unwanted effects of self-organisation. Chapter 9 will discuss several mechanisms of such coordination in detail.

1.2.3 SON Characteristics and Challenges

‘Self-organisation is a process where the organisation (constraint, redundancy) of a system spontaneously increases, that is, without this increase being controlled by the environment or an encompassing or otherwise external system’ (Heylighen, 2009). On the one hand, SON in LTE is based on the general definition like the one above used in philosophy, physics, biology, and so on. On the other hand, self-organising principles have already been applied to some extent in the IT (Autonomic Computing) and general networking domain (ad hoc networks). With regards to networking, the clear differentiator of SON in LTE is the application of self-organisation to an infrastructure network, which is desirable due to the inherent complexity of both, the network and its OAM system (Section 3.3).

Because SON functions are embedded into the OAM system and the network elements themselves, SON architecture is an important and often controversially debated topic. It is closely related to the general tradeoffs of distributed versus centralised system architecture in addition to the strong link to the 3GPP legacy OAM architecture (Section 3.4). The major driver for SON is the reduction of operational costs (rather than revenue increase, for example, by introduction of new services). Hence, it is crucial to understand the business value which can be generated by addressing a use case by SON (Section 3.5). Finally, the transition process towards SON described above brings technical challenges mainly caused by moving from an ‘offline’ planning and optimisation tool chain to embedding ‘online’ SON functions into the OAM system and the network elements. Furthermore, even if those challenges have been successfully addressed, SON functions need to be integrated with the corresponding, existing operator processes and the people implementing those processes (the human operator interacts with the system at a higher-level, setting policies and targets for SON functions, rather than directly changing configuration parameters, cf. Section 3.6).

References

Heylighen, F. (2009) Self-Organisation, Principia Cybernetica Web http://pespmc1.vub.ac.be/selforg.html. [accessed 30 June 2011].

Holma, H. and Toskala, A. (eds) (2011) LTE for UMTS: Evolution to LTE-Advanced, Revised Edition, John Wiley & Sons, Chichester, Chapter on SON.

Laiho, J., Wacker, A. and Novosad, T. (2006) Radio Network Planning and Optimisation for UMTS, 2nd edn, John Wiley & Sons, Inc., New York.

NGMN (2008) Use Cases related to Self-Organising Network, Overall Description, NGMN Technical Working Group, Self-Organising Networks, (ed. F. Lehser), December 2008.

Chapter 2

LTE Overview

Cinzia Sartori, Anssi Juppi, Henning Sanneck, Seppo Hämäläinen and Miikka Poikselkä

LTE encompasses a set of aggressive requirements that aim at improving the end-user throughput, the cell capacity and reducing the user plane latency. These requirements, together with full mobility, will bring substantial benefits to user experience.

LTE is designed to support all kind of IP data traffic and voice is supported as Voice over IP (VoIP) for better integration with multimedia services. LTE aggressive requirements lead to the definition of a new Network Architecture, the Evolved Packet System (EPS), which comprises the Enhanced RAN (E-UTRAN or LTE) and the Evolved Packet Core (EPC). Both data and voice services are supported over the same packet switched network. E-UTRAN and EPC have been defined in 3GPP Release 8 and enhanced in further 3GPP Releases.

LTE paved the way to a new standardisation approach. In Release 8 LTE network and OAM have been standardised at the same time, yielding tremendous opportunities to design an overall optimised