son removing risk adding value
TRANSCRIPT
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Self-Optimizing Networks: Removing Risk and Adding Value
A Stratecast Executive Industry Positioning Paper
Tim McElligott Senior Consulting Analyst – Global OSS/BSS Strategy
February 2014
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Self-Optimizing Networks: Removing Risk and Adding Value
2 © 2014 Stratecast. All Rights Reserved.
EXECUTIVE SUMMARY
Getting lean, which communication service providers (CSPs) spent more than a decade doing, was a necessity
that brought the cost of doing business down to a level that allowed CSPs to compete and remain profitable. However, it has left them with few options for responding to the incredible growth of network traffic;
particularly, highly dynamic mobile data traffic.
Their best option is automation. No business could hope to respond to dynamic growth the way CSPs need to
respond, with manual processes and human labor. Lack of automation increases costs and prevents effective
responses to rapid changes in network load and customer experience. To whatever extent possible, CSPs must leverage technologies that support automation. This automation could include applications for any or all of these
categories: data collection and analysis, network device configuration, service assurance, traffic management, optimization, repair, and capacity management. One such technology available today is the self-organizing
network (SON); often called the self-optimizing network.
This whitepaper provides an overview of the current iteration of SON as defined by 3GPP and others. It also looks at work being done to extend the application of SON beyond 4G and beyond the radio access network
(RAN). While the concepts behind SON are applicable to any network type, this whitepaper focuses primarily on radio access networks (RAN).
The paper highlights current use cases for SON, and looks at what features may be added to make SON a more
comprehensive solution that goes beyond a focus on network performance. It also addresses some of the concerns CSPs have over automation in their network domain. These concerns are well founded; but in the
current business and competitive environment, these concerns must be addressed and overcome. This paper shows some of the ways that might be done.
Finally, the paper covers the challenges to managing heterogeneous networks (HetNets), which will likely become
prevalent in mobile networks over the coming years, provided technologies like SON can render these HetNets cost effective and manageable.
SON: THE IDEAL AND THE REAL
The concept of the Self-Organizing Network (SON) was first
described in Release 8 of the 3rd Generation Partnership Project (3GPP) technical specifications for UTRAN-based LTE systems, in
December 2008. The definition of SON by 3GPP was in response to
calls by CSPs to increase automation and avoid the operational issues in 2G and 3G networks. The basic concepts of this specification’s
early release still hold. However, the need to define an expanded scope for SON has steadily grown more urgent; and the breadth of
requirements and capabilities has grown in parallel. Before exploring
this expanded scope, this paper will review the current state of SON.
Whereas Release 8 of the 3GPP standard focused primarily on
specifications and use cases for automated inventory, software
$467.4 millionProjected Outdoor
Drive Test Equipment Market by 2019
WILL SON CURTAIL IT’S GROWTH?
Source: Frost & Sullivan
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downloads and physical Cell ID assignment, SON began to take on new dimensions in later releases, particularly
regarding optimization. Early optimization efforts focused on mobility, coverage, capacity, and load balancing. The goal of these use cases was to address problems in manual optimization processes; namely, inconsistency and lack
of responsiveness to dynamic changes in network conditions. SON also focused on reducing costs associated with manual drive testing, as well as energy costs within wireless networks—a significant contributor to overall
operational expenses. Energy savings management allows mobile operators to design networks that consume less
power by automatically and temporarily shutting down unused capacity when not needed.
These efforts stand on their own, but also support ongoing work for developing one of the more coveted, but
trepidation-inducing automations in networking: the self-healing network. A self-healing network mandates stricter data integrity and real-time visibility in a network that is changing dynamically. CSPs worry about a lack of
control over the troubleshooting process when they lose their frame of reference for the configuration at the time a particular event occurred. These concerns are being overcome and will be discussed later in this
whitepaper.
Thus, the features and capabilities described above can be segmented into three categories of the Self-Organizing Network: self-configuring, self-optimizing and self-healing.
▪ Self-configuring networks typically focus on pre-service, automated deployments of base station,
radios, small cells and other RAN elements. This category of SON leverages auto-discovery and ANR to
allow network elements to discover their place in the network, as well as the configurations of their
neighbor and adjacent cells. It also lets them adjust an element’s configuration and relationship to its neighbors. This will become increasingly important as small cells and heterogeneous networks
proliferate.
▪ Self-optimizing networks improve coverage by maximizing the utilization of network elements, and
conserving the power required to run them. It concentrates on automatically responding to a growing body of parameters that need to be set and reset in response to changing requirements in traffic, based
on factors such as time-of-day demand, emergency coverage, environmental conditions, and the health
of other network elements. However, these responses increasingly need to include parameter changes related to customer experience and end-user usage patterns.
▪ Self-healing networks respond to service degradation or system failures by automatically adjusting
parameters, configurations, power consumption or physical antenna tilt, across the RAN and between
neighboring nodes. This self-healing function will change the dynamics of troubleshooting networks, and
improve mean-time-to-repair and service quality. It could also reduce the severity and duration of
SON allows mobile operators to design networks that consume less power by
automatically and temporarily shutting down unused capacity when not needed. “ ”
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Self-Optimizing Networks: Removing Risk and Adding Value
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service-affecting outages. Ultimately, automated network configuration changes will react to customer-
based parameters.
SON can be implemented in any or all of three different configurations. Distributed, centralized or hybrid.
▪ Distributed SON: In this type of SON (D-SON), functions are distributed among the network
elements at the edge of the network—typically the ENodeB elements. This implies a certain degree of
localization of functionality, and is normally supplied by the network equipment vendor manufacturing
the radio cell.
▪ Centralized SON: In centralized SON (C-SON), functions are more typically concentrated closer to
higher-order network nodes or the network OSS, in order to allow a broader overview of more edge elements and coordination of, for example, load across a wide geographic area. C-SON systems provide
increased scope for the use of input data from beyond the network. C-SON systems are more typically
supplied by third parties, due to the need to inter-work with cells supplied by different equipment vendors.
▪ Hybrid SON: Hybrid SON is a mix of centralized and distributed SON, combining elements of each in
a hybrid solution.
USE CASES EVOLVE
Initial use cases for SON, defined by 3GPP, were LTE-centric and focused on three main functional areas:
configuration, optimization and healing. Understandably, none included data, actions or processes external to the network. SON configuration use cases looked at hardware installation and testing, at set-up parameters for
radios and transport technology performance, and at network authentication. Likewise, optimization use cases
were limited to using network data to adjust network parameters in radio and transport networks.
CSPs began to ask how the benefits they envisioned
for LTE SON could be applied to their existing 2G and 3G networks, thus increasing the breadth of
SON to new technologies. At the same time, other
groups seek to extend the depth of SON’s capabilities. In recent work— such as that from the
SEMAFOUR project, which is a consortium created to develop a unified self-management system—use
cases for future networks have been identified. These
include resource management for supporting dual connectivity, dynamic spectrum allocation and
interference management, automatic traffic steering, and reconfigurable antenna systems. Capabilities such
as traffic steering will become more important as heterogeneous networks that include small-cell and offload
technologies become more widespread and require better integration with core networks. Traffic steering can be impacted by another 3GPP enhancement known as dual connectivity, in which a user can be connected to
multiple base stations. This also cries out for better resource management.
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BEYOND DEFINITIONS AND THE FUTURE OF SON
The initial buzz around SON gave the industry a name and a validated approach for increasing automation in wireless networks. It also created pressures for SON to cover more.
Outside of the industry standards, SON should and does continue to evolve. Leaving SON purely to industry
specification groups results in slower progress towards increased automation. This delay stresses equipment providers’ ability to respond, both technically and commercially, to necessary change; and opens the door to
opportunity for independent third party software supplier to establish offerings that go beyond the standards definition of SON. As suppliers in the mobile industry identify their strengths and unique approaches to managing
RANs, they bring to light many areas beyond the network that impact or could be impacted by SON. These areas
include efforts to both extending SON capabilities and the long established processes within CSP organizations.
For example, self-configuring networks completely change the dynamics of network planning. Engineers will no
longer design cell sites based almost exclusively on coverage and capacity projections, but will design dynamic networks that include small cell technologies and support Wi-Fi handoffs. They must take neighbor relations to a
new level, and learn to master the real-time analytics of data from many additional sources. Network planners
must prepare for the domino effects of autonomous network elements reconfiguring themselves at will, albeit based on parameters and rules set by network engineers.
Engineers are also considering what role policy managers will play in the network, and how to incorporate the rule sets of policy managers into the automation process, as well as what parameters will be used to trigger
them.
Extending SON also means going beyond the network. Most of the triggers currently defined are based on
network performance parameters. Using only network data means decisions will be made based on the tweaking
of technology. This is very important, but it also flies in the face of proclamations by CSPs that they are customer focused and working to deliver the best customer experience. An algorithm created for automatically fine-tuning
the network to maximize the customer experience cannot achieve its goal without including data sets born of that experience.
That is why geo-location and customer experience analytics will play an important role in future iterations of SON; although there is no reason these technologies cannot be included in the process today. Not incorporating
these technologies is unnecessarily leaving valuable information and business-affecting capabilities on the table.
SUBSCRIBER GEO-LOCATION
Before there was 4G LTE; before 3G transformed both the network and customer usage by introducing high-speed mobile data; even before 2.5G—there was drive testing. Drive testing involves the costly practice of
An algorithm created for automatically fine-tuning the network to maximize the customer
experience cannot achieve its goal without including data sets born of that experience. “ ”
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Self-Optimizing Networks: Removing Risk and Adding Value
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loading a vehicle or vehicles with devices and test gear to travel through the coverage areas of a given network,
making connections and measuring performance. It was the best option available in the early days of mobile for evaluating coverage, and it has held that distinction to the present day. Part of the mission of SON is to eliminate
or significantly reduce the need for drive testing. More centralized test systems and smarter devices have helped lessen the need; but a more strategic use of geo-location technologies and analysis can help further reduce drive
testing.
Geo-location technologies, in conjunction with the proliferation of small cells, are allowing CSPs to get much more granular in identifying trouble spots in a network. When CSPs are ready to automatically shift resources in
reaction to poorly performing network segments, geo-location allows them to be much more efficient in the process by providing the data that allows a SON to apply only the necessary resources to solve a problem.
Geo-location also works hand-in-hand with customer experience data analytics to add a deeper dimension to self
-optimization. This deeper dimension is one that enables decisioning systems to incorporate precise data on which customers may be affected by a problem in the network. Coupled with input from O&M systems, it also
helps CSPs understand the value of those customers. CSPs can therefore make value-based, or revenue-based, business decisions regarding the re-allocation of resources.
UTILIZING THE CUSTOMER EXPERIENCE
The proof of a CSP’s commitment to customer centricity may lie in its willingness to move SON beyond its
current role as a network performance tool, to a tool that takes full advantage of customer experience data by
leveraging that data in its automation and optimization processes. The customer experience aspects of SON should include subscriber usage patterns, subscriber location, subscriber value, and actual customer experience.
The value portion of such a customer experience view would also require a tight integration with O&M.
A full SON that includes geo-location and customer data also changes the dynamic for the customer care
organization. Customer care representatives will be able to better characterize a service-effecting event when
interfacing with a customer, since it would be couched in service and/or business terms rather than technology terms. This type of SON would focus primarily on corporate business users. Much of the granularity allowed by
customer-centric SONs relies on the deployment of small-cell technology, which presents challenges of its own.
SON inherently delivers benefits in the way of improved network performance, capacity management and
network utilization. These improvements indirectly, but positively, affect the customer experience. However, for
a more direct impact on the customer experience, functionality and systems designed specifically for the
The proof of a CSP’s commitment to customer centricity may lie in its willingness to
move SON beyond its current role as a network performance tool, to one that takes full
advantage of SON by incorporating customer experience data into its automation and
optimization processes.
“
”
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customer experience could stand to be more tightly integrated, or even productized, as part of a CSP’s SON
solution. Customer-facing systems such as billing, CRM, order management, service delivery and service fulfillment could be part of a SON solution. And, along with SON’s core network function, could be used to:
▪ Proactively manage service level agreements
▪ Target optimization at the most valuable coverage areas
▪ Target optimization at the most valuable customers
▪ Base policies and parameters on what the customer wants and does, versus what the network thinks it
needs for optimal performance
▪ Provide access and context for SON to customer service departments
▪ Force the interworking of network and IT, which is beginning to happen in other parts of the business
LEVERAGING CUSTOM ALGORITHMS AS A SOURCE OF DIFFERENTIATION
All that has been said so far points to SON use cases; and the algorithms that support them can become an area
of differentiation. Take, for example, an algorithm or set of algorithms that drive hand-off optimization between cells. No two algorithms are created equal or are likely to generate different results regarding handoff success
rates. And, much like developments in the burgeoning Big Data market, solutions suppliers will be able to differentiate themselves based on who writes the best algorithms. The winners will be the algorithms that deliver
the fastest, most accurate and insightful conclusions, and lead to the best performing networks. They will also be
those algorithms that can incorporate unique CSP requirements.
As stated above, algorithms designed primarily for network
performance will fail to have the full effect on the customer experience and the business. So, CSPs should look for algorithms
with the broadest scope, which incorporate key data from
pertinent IT and operations and monetization (O&M, also known as OSS BSS) functions.
No two networks are exactly the same, nor are any two business models. So, it follows that algorithms cannot come from a cookie-
cutter design. SON suppliers must offer customization services, as
well as provide CSPs the option of customizing their own algorithms for SON.
THE CHALLENGE OF MANAGING HETNETS
The term HetNet indicates the use of multiple types of access nodes in a radio access network. HetNets refer to
the combination of macro cells (traditional cell towers) with small cells, working in conjunction to deliver increased coverage and capacity, compared with just the macro networks alone. These small cells can be any
combination of femtocells for indoor coverage and picocells for outdoor traffic hot spots.
The overall small cell market is forecasted by Frost & Sullivan to experience a 61 percent compound annual
$7.76 billionProjected Market Size
for Small Cell Technology in 2016
SON COULD ACCELERATE THIS
GROWTH
Source: Frost & Sullivan
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Self-Optimizing Networks: Removing Risk and Adding Value
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growth rate through 2016, and grow to approximately $7.76 billion.1 The drivers for deploying small cell
technology include: a potential lower total cost of ownership; increased coverage; improved data traffic management—despite the amount of data traffic growing to 6.3 Exabytes of data per month by 2015; and faster
new service introduction.
However, SON itself is seen by some as a short- to mid-term restraint on small cell deployment. This is because
SON is seen as a priority and a competitive advantage, and CSPs do not want to delay its introduction by
including difficult-to-manage heterogeneous networks in the rollout. Part of the reason SON is a priority is that it is estimated to achieve a 55 percent savings in capital and operational expenses when deployed.
Managing current multi-vendor, multi-technology RANs; and managing the associations between them, and the neighbor lists within them, is complex enough. Adding small-cell technologies to this already complex
environment magnifies the complexity. However, complexity can be managed; if network costs are not better
managed, little else matters.
While more than 60 percent of the small cell market share is divided among three leading companies, many new
suppliers of small cell technology are expected to enter the market, making centralized management increasingly difficult. Management will get even more difficult when open-source technologies become more prevalent in small
cell environments, which Frost & Sullivan analysts have said they must.2
Security and privacy are of concern on two fronts regarding small cells. Wireless is inherently more prone to eavesdropping and jamming, as well as device tracking. But also, small cell technology provides many more access
points—often less secure access points—to the network. From a cost perspective, CSPs cannot afford to deploy technologies that require return visits for maintenance or for eventual upgrades. Small cells must therefore meet
the requirements for being part of a SON, and allow for remote and automated configuration, self-optimization
and self-healing.
MULTIVENDOR SUPPORT MUST BE REAL AND COMPLETE
Although many equipment suppliers claim to be multi-vendor in their management support of like technologies, and some to a certain extent are, there will be little room for exceptions when it comes to managing SONs.
Automated configuration and self-healing in particular require a higher level of consistency in the parameters used to evaluate performance and commands that control changes in multiple vendors’ equipment. A truly
independent management layer also can aide in evaluating the efficacy of applied policies and changes on both a
real-time and long-term basis.
Not all networks will be LTE. Nor will all networks or even segments of networks be on the same generation of
technology. Extending the 3GPP concepts for SON to all generations and makes of equipment can be expedited by a platform that supports true multi-vendor capabilities.
ACKNOWLEDGING AND ADDRESSING CONCERNS ABOUT AUTOMATION IN NETWORKING
The concerns CSPs hold about automating critical aspects of their networks—such as planning and engineering, configuration, optimization and maintenance—are strongly held, and with good cause. They are all a part of the
overall concern, which is losing control over the management of their infrastructure. And, as mentioned above,
1 See Frost & Sullivan research report: Analysis of the Small Cell Market: Small is Big, December 2012.
2 See Frost & Sullivan Report: Small Cells: A Big Component in Future Mobile Networks, February 2013.
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multi-vendor integration is still a concern.
CSPs are uncomfortable allowing the automation of certain network functions and processes when they do not feel, still, that they have a reliable real-time view of the network. CSPs lack an accurate baseline from which to
begin troubleshooting problems when things go wrong. Data integrity is also a long-standing and ongoing concern.
This causes CSPs to seek granular control and supervision of their algorithms. Some CSPs are calling for options
within the automated flow that allow for manual confirmation of certain changes in configuration. Others call for
better back-out plans or ways to override the system, if necessary. CSPs also recognize that their network management processes were not designed for a fully autonomous system, and would require re-evaluation. All of
this points to a need for mature SON solutions, not just algorithms.
Without more automation and better self-optimization, the current CSP business model will begin to break down. CSPs cannot afford to continue manually supporting a network that will comprise hundreds of thousands
of HetNet devices. Nor can they support the kind of data volume growth the industry expects. CSPs also have to consider the unknown, which encompasses all the new applications, services and devices the market is likely to
see in the coming years. Most important, CSPs won’t be able to hold back the equally large and sophisticated
Internet companies that will grow impatient waiting for CSPs to build networks to support their innovative services. This combination of the need to move quickly, coupled with concerns over SONs’ impact on
manageability, will cause CSPs to seek out third parties that have a track record of supporting both their business and network objectives.
CSPs lack an accurate baseline from which to begin troubleshooting problems when
things go wrong. “ ”
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Self-Optimizing Networks: Removing Risk and Adding Value
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THE LAST WORD
From its emergence in 2008, SON has grown into one of the critical technologies that CSPs have at their disposal
to manage the on-going growth of highly dynamic mobile data traffic. Conceived as a network technology for optimizing performance, SON now represents a strategic shift that can positively impact not only network
performance, but also profitability and the customer experience. Therefore, as CSPs look beyond the limited use cases and network technologies of standards-based SON, they will begin to see SON increasingly as a business
solution.
A closer proximity of IT and network functions will drive the CSP transition to higher automation. Ideally, incorporating more IT functionality and resources into SON would entail true integration into a comprehensive
SON solution, and not treating IT and OSS as mere data feeds into a networking process. Geo-location, customer experience, customer value, business assurance, and, one day, Big Data, should all be part of a
comprehensive SON solution; and considered on par with network utilization, ANR, and programmable radios.
The small cell market is projected to be huge, by any standard. Frost & Sullivan expects a 61 percent CAGR through 2016. However, turning small cells into true HetNets, which can be managed cost-effectively and achieve
the expected boost in coverage and capacity, will take automation. And, transforming HetNets into a more broadly effective next-generation RAN will take more than automation. It will require a SON that incorporates
all the other business and customer aspects discussed in this paper.
Given the broad potential scope of SON, and the multi-vendor, multi-technology management and optimization capabilities that will ultimately be required, CSPs should give serious consideration to evaluating SON solutions
from an independent third-party supplier. CSPs also should consider finding a partner with the services experience to help transform management and optimization practices and procedures in tandem with new SON
technology introduction.
Tim McElligott
Senior Consulting Analyst – Global OSS/BSS Strategy
Stratecast | Frost & Sullivan
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