Automation White Paper

White Paper for InfoVista

Optimisation automation:

Immediate gains for today, SON enabler for the future

May 2013

Dr Mark H Mortensen, Patrick Kelly and Anil Rao

.

Analysys Mason Limited 2013 May 2013

Contents

1 Executive summary 1

2 State of the network planning and optimisation domains 1

3 Reducing CAPEX with integrated NPM and NP&O 2

4 Up-to-date network intelligence for Automated Network Optimization and Planning 3

5 Optimization automation is the right step towards realizing SON 5

6 The market is already moving forward 6

7 Recommendations: modernise, integrate, automate 7

About the authors 8

List of figures

Figure 3.1: Manual NP&O processes using out-of-date data lead to inaccurate resource allocation ............... 3

Figure 4.1: Optimisation automation by integrating NP&O and near real-time NPM systems ........................ 4

Figure 4.2: Capex savings ................................................................................................................................. 4

Figure 5.1: Benefits of SON ............................................................................................................................. 5

Figure 5.2: SON-enabled NP&O processes ...................................................................................................... 6

Optimisation automation: Immediate gains for today, SON enabler for the future | 1


1 Executive summary

Mobile communications service providers (CSPs) are under tremendous pressure to increase network capacity to

support the ever increasing mobile data consumption rates. It is therefore imperative that they take steps to

efficiently utilise the limited network resources. CSPs have traditionally used network planning software to add the

right capacity at the right place at the right time, in order to provide the best customer experience, without expensive

overbuilds. Doing this optimally requires high-quality, current data. In addition, there is also a goal of optimisation

of available resources modifying the existing network configuration, without adding resources, in order to optimise

the use of current network resources while providing the latest services at the highest possible quality levels.

Network planning is a complex exercise with a typical planning cycle often taking months. With new mobile

access technologies coming into use such as small-cell, HSPA/HSPA+ and Wi-Fi data offload, the planning

process is becoming much slower and time consuming, and without streamlining the existing planning processes,

CSPs will increasingly struggle to find the optimal solutions. Compounding this problem further is the use of in-

house tools and manual processes that use outdated network performance data for planning. This leads to poor

quality network plans, inaccurate allocation of network resources and stranded capex. Analysys Mason estimates

that mobile CSPs have at least 5% of their network capacity stranded because of this, plus inaccurate forecasting.

Innovations in network planning and optimisation (NP&O) software systems will address this problem to some

extent. However, integrating a network performance management (NPM) system with a modern, automated

NP&O system enables the CSP to use latest network performance data for network planning improving the

overall accuracy and quality of network plans and paves the way for optimisation automation. Models indicate

that optimisation automation can recover as much as 20%40% of the stranded capacity, providing improved

capital expenditure (capex) efficiency and, through the automation of manual processes, additional operational

expenditure (opex) savings.

Furthermore, optimisation automation is the best current step towards realising the potential of self-

optimising/organising networks (SON).

2 State of the network planning and optimisation domains

Two major recent advances in NP&O technologies have recently been introduced, although many CSPs have

not yet updated their operations, and software systems, to take advantage of them. These CSPs are suffering

higher than needed opex costs.

First is the introduction of true planning systems, rather than mere planning tools. These modern systems

provide much more than the tools by centralising the data, synchronising the interdependent, layered plans, and

ensuring consistency amongst the various technology and geographic plans. These systems can also radically

reduce the planning cycle times from four to six months to a matter of weeks.

Second is the availability of advanced performance information from the network equipment itself. With the

right performance management system, a mobile CSP can determine the accurate utilisation and actual

performance that customers perceive and plan and tune their networks accordingly. This is eliminating

expensive drive tests and improving the quality of the data as measured at the handset, which are, more often

than not, inside buildings.

So what can be gained by combining these two advances? That is the subject of the rest of this white paper.



3 Reducing CAPEX with integrated NPM and NP&O

Beyond planning the right location for capacity augmentations, CSPs now use advanced NP&O software tools

to optimise their networks. The aim of such optimisation is to modify the existing network configuration

parameters, without adding resources, in order to optimise the use of network resources while providing the

current services at the highest possible quality levels. Driven by such CSP requirements as well as innovation

through R&D, the vendors of NP&O software have developed features that tackle the increase in technology

complexity and optimise the planning exercise. Below are three such examples:

Advanced antenna modelling: with heterogeneous networks, it is important to have good antenna format

for all cells (macros, micros, etc.). Most radio planning tools have separate antenna files for different

electrical tilts, electrical azimuths, different frequency bands, etc. This can mean a huge number of antenna

files. This is not practical at all from a users perspective. In the case of antennas being shared by different

technologies or frequency bands, you will have multiple sectors that share the same antenna, it is critical

to have a single antenna file, to indicate that the physical parameters of the antenna are shared by all the

sectors that use that antenna, while electrical tilts can potentially be different for the sectors that share that

antenna.

Support for LTE-Advanced: innovative CSPs, especially in North America and in developed AsiaPacific

countries are either already in the midst of strategic planning for LTE-A or will soon start thinking about it.

LTE-A offers capabilities that are dedicated to HetNet, and that are meant to increase network capacity,

which will be critical to remain competitive and protect margins.

Efficient hotspot identification for planning and optimisation: some innovative capabilities allow

engineering and optimisation teams to focus on the planning and re-planning exercises that would provide

the best return on investments. For example this can be the ability to leverage social media information

(such as Twitter) as one of the data feed (crowdsourcing). The ability to leverage polygon files (including

building heights and building types) as well as the ability to define indoor-to-outdoor traffic ratios are also

important innovations.

On its own, advancements in the NP&O technology will continue to benefit the CSPs, enabling them to optimise

deployment costs. However, there is a significant opportunity to go one step further and achieve higher network

capex efficiency through additional innovations such as using up-to-date network performance data in the

NP&O processes and realising the benefits from the synergies achieved between NP&O and NPM.

Since many CSPs use traditional planning tools, the NP&O process takes many months to complete a planning

cycle since many geographies and technologies must be planned together and in addition, the planners use

different tools for each technology (3G, LTE, etc.) in some cases, in different departments (engineering,

optimisation, CTO office, etc.). Typically, in a mobile NP&O scenario, two inputs are needed to create the

traffic matrices needed to plan the RF, backhaul and core network capacity current network usage and

configuration, and new traffic forecast due to growth. The long planning cycle times, together with out-of-date

network and forecast information lead to suboptimal placement of resources by the planning process. This leads

to networks with as much as 5% of their capacity stranded and unused. Of course, growth of the network will

eventually use up the incorrectly placed capacity but meanwhile, it is unused. And other areas that received

insufficient resources perform poorly until augmented, leading to poor quality of service and customer churn.



The situation is particularly unfortunate because many modern NPM systems are picking up near real-time data

from the network. But the long planning processes render this data obsolete by the time it is used. This is shown

in Figure 3.1 below, where NP&O processes are entirely manual, use poor quality historical performance

management data, and take months of planning before the network modifications are planned and implemented.

Figure 3.1: Manual

NP&O processes using

out-of-date data lead to

inaccurate resource

allocation [Source:

Analysys Mason, 2013]

4 Up-to-date network intelligence for Automated Network

Optimization and Planning Building highly performing

cost-efficient networks

Services deployed over an LTE network will require consistent uniform performance management across the

access and backhaul networks. The challenge in todays mobile networks is matching broadband demand with

available network capacity. Technologies such as LTE enable mobile operators to meet these demands via

greater spectral efficiency and targeting an LTE overlay strategy in areas where demand exceeds available

capacity.

Mobile operators can benefit from performance management systems because data can be used in near real-time

to make informed decisions on how to tune available network resources including such techniques as traffic

steering and optimisation of the radio access technology (RAT).

Collecting near real-time network performance data enables mobile CSPs to defer capital spending in parts of

the network where it is not yet needed and it improves the network planning and optimisation process. A good

quality plan puts the right resources at the right place at the right time, decreasing congestion, efficiently using

capital, and increasing customer satisfaction (see Figure 4.1).

Problems

Stranded capacity and capex Use of old and out-of-date

network performance data

Long planning cycle time Few what-if analyses

NP&O NPM

Up-to-date

network

performance

data

Mobile network(macro-cell, backhaul, IP-core)

Manual

optimisation

Data quality

GreatGood

Poor

TODAY: networks with stranded

capacity and capex

Network

modifications

take months

Jan

March

Feb

Manual feeds

of historical

data

Manual

congestion

control



Figure 4.1: Optimisation

automation by

integrating NP&O and

near real-time NPM

systems [Source:


Near real-time network performance management combined with network planning systems enables accurate

reporting for service coverage maps. The planning process can then do a just-in-time resource allocation in the

order of days for the RF, backhaul, and core networks. By automating the process of retrieving the information

from performance management systems and feeding it into NP&O systems, CSPs can achieve significant

benefits in the form of optimisation automation. This leads to accurate network resource allocation by pin-

pointing exact locations with network performance degradation based on existing traffic patterns, and provides a

basis for predicting the locations where future performance degradation is likely to occur. In addition, CSPs can

reduce human error by automating the feeds from NPM systems into NP&O systems.

Proactive coverage maps, automatically produced, can be used to tune the network plan to ensure continued

quality of service to key corporate and other high-value customers, as the traffic increases. This will be

particularly important as LTE high-speed data is introduced and its use grows with rising numbers of LTE-

enabled mobile devices and the ensuing increase in bandwidth usage. As integrated NPM and NP&O systems

are implemented with more, faster automated optimisation processes, benefits will increase as the systems are

able to optimise the network during anticipated diurnal variations in network traffic conditions. Analysys Mason

estimates that mobile CSPs can recoup 20% to 40% of the 5% stranded capex by implementing optimisation

automation processes (see Figure 4.2).

Figure 4.2: Capex

savings [Source:


Benefits

Current up-to-date networkperformance data

Reduce stranded capacity

Reduce stranded capex Up-to-date coverage maps Network optimisation based

on high-value customers

NP&O NPM

Up-to-date

network

performance data

Mobile network(macro-cell, backhaul, IP-core)

Manual

optimisation

Data quality

GreatGood

Poor

TOMORROW: integrated NP&O

and NPM

Network

modifications in

days/weeks

M T W T F

Capex

(30%

of total

mobile

CSP

cost)

Up-to-

date

n/w perf.

data

Accurate

forecasts

Efficient

n/w

planning

5% stranded

capex

1%2% savings on

capex



5 Optimization automation is the right step towards

realizing SON

Mobile CSPs worldwide are in different stages of deploying LTE access technology. CSPs are also pursuing

strategies to enhance coverage using the least possible capex such as deploying 3G/4G small cells, femtocells

and Wi-Fi offloading capabilities. This will result in a heterogeneous network (HetNet) that will be significantly

more complex. Consequently, the HetNets will place significantly high demands on the network planning and

optimisation teams, systems and processes. Manual planning cycles will take even longer with a higher

probability of human error leading to inaccurate and misallocation of network resources. If the CSPs are not

careful, inefficient network planning and optimisation can result in increased costs and potentially, defeat the

whole purpose of a HetNet strategy.

Mobile CSPs and vendors have tried to tackle this problem in the past. In 2007, when the long-term evolution of

3GPP (LTE) was being tabled, all parties, including mobile CSPs and vendors, agreed the need to operate the

system at a significantly lower cost compared to UMTS. This requirement gave rise to features for networks to

self-organise and self-optimise (see Figure 5.1). The SON standards were defined with three architectural

options based on where the SON algorithms are deployed in the base station/controller (centralised), in a

central server connected to northbound SON interfaces (distributed) or in a two-stage control architecture with a

centralised SON algorithm controlling distributed algorithms over a dedicated SON interface (hybrid).

Figure 5.1: Benefits of

SON [Source: Analysys

Mason, 2013]

Equipment manufacturers began back-porting SON features to 3G technology in earnest in 2010, as CSPs began

to understand that to meet the rising demand for data, it could be more cost-effective for them to expand HSPA

and HSPA+ high-speed data capacity on the existing 3G infrastructure in many locations.

However, to realise the full potential of SON will require network-level functions in a hybrid architecture,

requiring that NPM and NP&O functions be integrated, automated and, eventually, put in control of the network

in a closed-loop cycle. CSPs will also require the tools and mechanisms to validate vendor-driven SON

implementations to gain full confidence in the optimisation process.



Analysys Mason believes that true SON capabilities, while still eight to ten years away from being a full reality,

will be incrementally implemented. One such incremental step towards realising SON is the optimisation

automation. With more small cells in the network, a richer network performance data will be available that can

make the planning and optimisation process even more efficient. Eventually, as SON features roll out in the

equipment, the NP&O system, using up-to-date performance network intelligence, will be able to optimise

further the network, backhaul, and core IP networks. In the short term, these will be implemented both as open-

loop systems, providing recommendations to the network engineers, who control the network configuration, or

closed-loop systems, where the NP&O system itself optimises the network in near real-time (see Figure 5.2).

Figure 5.2: SON-

enabled NP&O

processes [Source:


6 The market is already moving forward

Over the last several years, vendors have been strongly positioning themselves to offer the centralised software

module of a hybrid SON. In line with this strategy, vendors are integrating their network performance

management capabilities with network planning and optimisation capabilities to provide mechanised, and

eventually automated, network optimisation for 3G/4G networks and future HetNets. To this end, a number of

traditional NPM independent software vendors and network equipment manufacturers have acquired NP&O

companies. TEOCO, a provider of fault and network performance management software, bought Schema for its

backhaul and automated cell planning capabilities. AIRCOM International, a provider of RF planning software,

built a network performance management solution and acquired configuration management through its

acquisition of Symena. Similarly, Ericsson bought Optimi, a network optimisation and management specialist;

Nokia Siemens Networks acquired IRIS Telecom; and Cisco bought Intucell, a SON software supplier.

In a move similar to these acquisitions, InfoVista acquired Mentum, a leading provider of network planning

systems, in November 2012. InfoVista has deployed its NPM solutions at a number of tier-1/tier-2 mobile CSPs

to normalize massive amount of network KPIs/KQIs, via its mobile packs. InfoVistas Mobile Knowledge Pack

is a product that monitors the mobile infrastructure of leading suppliers including Ericsson, Cisco, NSN, Alcatel

and Huawei to generate up-to-date reports on network performance and network quality of service in a multi-

vendor network. Incorporating the latest network performance data and forecast network intelligence into the RAN

and IP transport planning processes will enable InfoVista to automate network optimisation processes and offer the

accuracy and efficiency essential for optimised and just-in-time RAN and backhaul investments.

Benefits

Fast forward optimisation Opex benefit opportunity with

energy savings

Network performance improvement in real time

Automated what-if analysis features

NP&O NPM

SON Closed-loop optimisation

Real-time network

performance data

HetNet(macro-cell, micro-cell,

Wi-Fi, backhaul, IP-core)

SON Open-loop

optimisation

Network

modifications in

hours/minutes

Data quality

GreatGood

Poor

FUTURE: SON



7 Recommendations: modernise, integrate, automate

Mobile CSPs must consider migrating to a modern planning and optimisation system: CSPs are

approaching the transition to LTE by looking at it not as the single solution to the increasing data usage of

their subscribers, but as just one of the ways of providing increased high-speed data capacity. A modern

mobile planning and optimisation system should be able to handle heterogeneous network expansion of not

only 2G, 3G, HSPA, HSPA+ and LTE, but also alternative small-cell solutions (micro-, pico- and

femtocells) and Wi-Fi offload. A strong what-if capability is a must as the engineers seek the optimal mix,

but beyond that, the ability of the system to recommend the optimal mix will become increasingly

important.

Mobile CSPs should integrate their NP&O system with an NPM system. This will enable CSPs to not only

use the latest network performance data as input into the network planning processes but will also enable

optimisation automation. CSPs can benefit from improved allocation of network resources, deferred capex

investments and recouping of stranded capacity.

Mobile CSPs should consider investing in a solution that enables automation of the planning process and

more specifically the capability to simulate coverage and capacity on demand so other departments can

achieve efficiency gains.

CSPs should consider sourcing a pre-integrated NP&O and NPM solution from a single vendor. A pre-

integrated solution provides out-of-the-box functionality required to automate the optimisation process,

meaning the CSPs can benefit from efficient network planning processes from day 1.

CSPs should consider a solution with multi-vendor support. Todays CSP mobile network environment

includes equipment from at least three or more network vendors with their EMS/NMS for network

configuration and performance monitoring. CSPs should therefore consider the integrated multi-vendor

NP&O and NPM capabilities of a third-party independent software vendor to avoid siloed solution

deployment.

CSPs should consider implementing hybrid-SON capabilities in their mobile network. This will enable

them to oversee networks from multiple vendors, gluing together the edges of the two networks and

reconciling the probable two different distributed SON vendor optimisation algorithm sets.



About the authors

Dr Mark H. Mortensen (Principal Analyst) is the lead analyst for Analysys Masons

Customer Care and Service Fulfilment research programmes, which are part of the Telecoms

Software research stream. His recent interest areas include customer self-care, automation of

fulfilment processes, and data and software architecture for agile, real-time systems. The first

20 years of Marks career were spent at Bell Laboratories, where he distinguished himself by

starting software products for new markets and network technologies and architecting the

interaction of BSS/OSSs with the underlying network hardware. Mark was Chief Scientist of Management

Systems at Bell Labs, and has also been president of his own OSS strategy consulting company, CMO at the

inventory specialist Granite Systems, VP of Product Strategy at Telcordia Technologies, and SVP of Marketing

at a network planning software vendor. Mark holds an MPhil and a PhD in physics from Yale University and

has received two AT&T Architecture awards for innovative software solutions. He is also an adjunct professor

at UMass Lowell in the Manning School of Management, specialising in business strategy.

Patrick Kelly (Research Director) leads Analysys Masons Telecoms Software research

stream, which focuses on identifying the rapidly growing segments in the telecoms software

market and providing forecast and market share data on each of the 29 segments by region and

service type. He has produced research on IP next-generation service assurance, the 3G mobile

software market and customer experience management. Patrick is a frequent speaker at

industry conferences. He holds a BSc from the University of Vermont, and an MBA from

Plymouth College.

Anil Rao (Analyst) is a member of Analysys Masons Telecoms Software research team. He

has over 10 years experience in the telecoms industry, working in system integration and

service delivery with major Tier 1 mobile and fixed line operators, focusing on order

management, service fulfilment and service assurance. Anil holds a BEng in Computer Science

from the University of Mysore, and an MBA from Lancaster University Management School.

This paper was commissioned by InfoVista. Thanks to Cyril Doussau de Bazignan, Director of Product

Marketing and Juan Prieto, Product Marketing Manager Mobile Solutions at InfoVista for their briefings and

contributions to this white paper.1

1

Published by Analysys Mason Limited Bush House North West Wing Aldwych London WC2B 4PJ UK

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Analysys Mason Limited 2013

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