The process used by Mobile Operators to Design and Plan the Core part of the Mobile Network (base station to PSTN/Internet) has traditionally been based on ad-hoc, spreadsheet methods for calculating network capacity relative to Subscriber demand.

The process is typically fragmented and inefficient, kicking off with a Subscriber and Service Usage Forecast that is provided by the Marketing Group to RF and Core Network Planning Teams.

The RF Team calculates the number of Base Stations and Transceivers (TRX’s) that are required to provide adequate coverage and capacity. The Core Network Engineering team then calculates the number of BSC’s/RNC’s, switching and peripheral platforms that are required. This is often undertaken using “spreadsheet calculators”, which apply engineering rules for the capacity of each vendor’s equipment to the demand forecast, to determine the amount of equipment required. Following this, periodic checks are made to true-up the deviation between real world demand and the design assumptions that were used for planning purposes.

One of the many downsides of using “spreadsheet calculators” is that they do not take into account customer performance impacts resulting from poorly defined system boundaries and re-homes that are required to support ongoing network evolution.

To optimize performance, mobility events and re-homes need to be minimized on an ongoing basis and to improve the accuracy of the design process real-world demand data needs to be used in conjunction with marketing forecasts. Achieving all of this is a non-trivial task that requires mathematical modeling and algorithms to identify the best possible network evolution path.

Leveraging real world network data, algorithms can be embedded into software tools to maximize the correlation between capacity and demand. In conjunction with this they can be applied to minimize the number of borders that cut through areas of high mobility, thereby reducing signaling load and associated transaction processing that erodes system capacity and performance. Last but not least, they can be used to analyze every permutation and combination of network design over time, to identify the best possible network evolution path that minimizes re-homes and associated performance impacts.

In this way Mobile Operators can be assured that they are achieving the best possible performance, while keeping their network investments as lean as possible.

The core network planning process adopted by most Mobile Operators has traditionally been fairly straightforward, following the industry standard of calculating BSC/RNC and MSC/CS/MGW requirements using a top-down approach. This approach takes Marketing forecasts of demand by service, or minutes of use (MOU) as an input and maps this to a constraint model for each element in the network that is used to calculate how much equipment is required. By applying the relevant equipment costs to this forecast, Mobile Operators can then calculate their annual Capital Expenditure requirements.

To improve the efficiency and accuracy of this process the team at Cerion created a core network optimization & planning tool, which has the capability to provide both a top-down and bottom-up assessment of requirements. The bottom-up approach leverages real world Operational Measurements (OM’s) &/or Call Detail Records (CDR’s), to derive a far more granular and precise assessment of equipment requirements than is available using top-down methods. It also incorporates algorithms that optimize the configuration and efficiency of the network as it evolves over time, based on both geographic subscriber demand and mobility, rather than using a far lower resolution demand forecast.

By running the optimization engine embedded in the product, users are able to simultaneously minimize the number of 2G and 3G elements in the network and mobility related transactions that erode network capacity and performance. In conjunction with this the product links bottom-up design with top-down capital planning and provides a system of checks and balances for a comparative reconciliation of bottom-up and top-down results.

The benefits of this approach are that it enables integration of the top-down and bottom-up processes and achieve the best possible network design on an ongoing basis:

* Since the overall planning process can have significant impact on the financial bottom line it is prudent for Mobile Operators to operate a combined top-down and bottom-up approach to achieve maximum financial efficiency.

* When compared to traditional ad-hoc methods for BSC/RNC and MSC/CS/MGW planning, this approach typically yields at least 15% in annual CAPEX and OPEX savings.

* By leveraging a system of checks & balances between the two processes, Mobile Operators are enabled with a mechanism for delivering the leanest, most precise and best performing network possible.

The combination of these factors enables Mobile Operators to be more efficient,  thereby making them more competitive and able to realize greater success in the marketplace.

In today’s fiercely competitive mobile marketplace, Mobile Operators must do everything that they can to ensure that their operations are as lean as possible, while moving swiftly to invest in new technologies and stay ahead of the competition.

As mobile networks evolve from circuit switched to IP the rate of change in mobile technology has never been greater, with the consequence that new network investments have a shorter and shorter life cycle before they are superseded.

The combination of these two factors means that in order to be successful Mobile Operators must minimize incremental investment, maximize associated returns and simultaneously ensure that they deliver the best possible quality of service (QOS) for end users.

The greatest technology changes are presently occurring in the fixed part of the mobile network (as opposed to the radio part of the network) where traditional circuit switched infrastructure is being overlaid and will be replaced by wholly IP-based system elements.

Core network investments cost Mobile Operators billions of dollars a year and to minimize investment while maximizing the return, it is absolutely critical for these Operators to have the capability to precisely assess and optimize core requirements on an ongoing basis.

To achieve this it is necessary to understand in near real time, the demand and associated dynamics taking place in the network and plan accordingly.

The principal dynamics driving mobile network design include:

* Rapidly changing network technology that leads to additional network complexity.

* Hyper-competition that drives tariff, service and end-user device differentiation, all of which result in unpredictable demand for IP services.

* Increased transaction processing associated with subscriber mobility that consumes network resources eroding its capacity to support revenue earning services.

Understanding all of these dynamics is a non-trivial task, requiring a proactive approach to analyzing and interpreting a vast amount of network data, which enables optimal decisions to be made concerning the design and evolution of the network.

Cerion Optimization Services is the world leader in this field and has developed sophisticated software tools for optimizing mobile network profitability by keeping network investment as lean as possible while simultaneously maximizing end-user performance.

Transaction processing is an increasingly big headache for Mobile Operators because it reduces network capacity, erodes revenue potential and adversely affects overall operational profitability - So what is transaction processing and what can be done to minimize its’ impact?

As mobile networks evolve to deliver broadband IP services, the associated technology is becoming ever more complex, resulting in a dramatic increase in the communication that is required between the different elements making up the network. This communication takes the form of signalling messages that are passed between the different elements in the network to support voice, IP and other mobile services.

Although many of the services supported by this messaging are revenue generating, others do not generate any revenue at all and in fact incur a tax on the network that reduces revenue potential. To successfully deliver services to customers all of the messages, whether revenue generating or not must be processed by the different elements comprising the mobile network.

The different services being delivered incur different transactions on the associated central processors that have a varying impact on both element and overall system capacity. The non-revenue generating services with the biggest impact on transaction processing are those associated with subscriber mobility and so it is vitally important to keep these to a minimum.

Subscriber mobility incurs far greater signalling in 3G networks than its 2 or 2.5G predecessors due to the need to support hard, soft and softer hand-off. As a result the capacity tax on the core network elements and the network as a whole increases dramatically. This tax becomes considerably worse in networks that combine 2G and 3G because of the additional mobility-related signalling associated with the hand-off between technologies or I-RAT signalling.

In hybrid 2.5/3G networks this signalling can seriously reduce the ability of key system elements  to process revenue earning services, including the erosion of switch capacity by as much as 50%.

To maximize revenues, minimize network investment and increase ARPU, Mobile Operators must therefore move swiftly to address this issue. They must identify solutions for minimizing mobility related transaction processing while concurrently maximizing end-user performance. Helping them to increase network capacity, boost profits and gain a significant edge over the competition.

As mobile networks evolve to deliver a rich array of IP-based multimedia services and consumer demand for these services grows, the proactive management of mobility will be a critical aspect of the mobile network design and planning process.

Driven by enabling technologies such as Session Internet protocol (SIP) and IP Multimedia Subsystem (IMS), fixed-mobile convergence is already becoming a reality with multi-mode devices roaming between GSM/UMTS networks and Unlicensed Mobile Access (UMA) such as Wi-Fi and Wi-Max.

The ultimate goal of convergence however, is to deliver a seamless service experience for customers across multiple locations, devices and types of use. Customer mobility is an extremely important aspect of convergence, particularly in relation to mobile networks because the demand for services is influenced by factors such as location that can also determine the customer’s method of access. 

Subscriber mobility in conventional 2G mobile networks creates a limited number of hand-off types that occur at each level of the network. Future networks however, will be increasingly peer-to-peer in their architecture and allow for roaming between technologies.

As a result of this the permutation and combination possibilities for hand-off types and cross-domain hand-offs increases exponentially – This increases the risk of Capacity and Quality of Service (QOS) impacts for end users and makes Proactive Mobility Management an absolutely essential part of the Core Network Design & Planning process.

One possible solution for overcoming this challenge is to acquire a Network Design and Optimization Tool that incorporates a Proactive Mobility Management Feature – To achieve this, the product should leverage Operational Measurements (OM’s) to proactively minimize the mobility impacts for any present or future network scenario and have the capability to support multiple technologies and infrastructure vendors.

With the coming of age of new technologies to power the Mobile Internet, the Wireless Industry faces dual challenges of getting to grips with IP, while simultaneously delivering a portfolio of high quality IP services for customers who are always on the move. For Mobile Network Designers these requirements combine to make the task of accurate and cost effective equipment engineering far more complicated and difficult than it has been in the past. There are many reasons for this - Firstly the fact that customers are mobile creates varying geographic demand on the network that simply does not happen in fixed networks. Mobility imposes a significant tax on the network because significant network resources are consumed in managing this, when they could be used to support the delivery of revenue earning services. Secondly the rate of technology change is driving multiple technology overlays that are implemented in different ways by the infrastructure vendors, making network engineering far more difficult and complicated than it has been in the past. 

Last but not least, the delivery of IP services involves analyzing traffic that is highly sporadic in nature and which incurs considerably more signaling overhead than traditional voice services. With demand for these services expected to explode over coming years, engineers need to find reliable methods for modeling and predicting both IP traffic and associated mobility signalling.

To stay ahead of these challenging dynamics network engineers must adopt smarter ways of working - Success means leveraging cutting edge design tools that incorporate IP capacity and mobility modelling, with optimization capabilities to help to streamline  the efficiency and precision of the design process. In this way engineers can minimizel the time to market for new designs and help lower the overall cost of network ownership.

Smart Tools are revolutionizing traditional methods for designing and planning the Core of mobile networks.

Traditional methods are typically based on an assessment of future demand that is contained in a Marketing Plan. Typically both RF and Core Network Engineering Groups assume this data to be a valid and calculate the amount of equipment that will be required by dividing the projected demand by the constraints of the equipment involved. This process is somewhat crude and is more often than not conducted using ad-hoc methods that have evolved over a period of time into some form of spreadsheet tool.

Today however far more accurate techniques are available to arrive at better and far more accurate results. Leveraging a combination of real-world OM &/or CDR data and Operations Research-based technologies the latest tools are able to derive a more precise assessment of network equipment requirements for some time into the future. In addition, these tools streamline and simplify the design process, helping Service Providers to realize lower costs, with faster time to market and improved returns on infrastructure investment.

By using real world network data such tools are able to make a far more accurate and detailed assessment of equipment engineering requirements than can ever be achieved using marketing projections alone.

By leveraging Operational Research techniques these products conduct an automatic evaluation of every possible network configuration scenario over time, to determine the best possible evolution path for the network far faster and more accurately than a human operator would ever be able to.

In this way Service Providers are enabled with the ability to derive the leanest, most precise and consistent network designs possible.

In today’s fast paced and highly competitive mobile phone industry, investment in new technology is an absolute necessity, however it creates additional challenges for service providers in the form of inherent performance risk and increased technological complexity. When combined with the challenge of securing and retaining revenues, the time and margin pressures on these businesses and their executives are immense.

To help overcome some of these challenges, mobile service providers need to secure high-powered, intelligent, decision-making capabilities, enabling them to realize the best possible return on their technology investments.

Nowhere is this more critical than in the core of mobile network. Since this requires significant investment in moving forward, is the most complex to engineer and represents the single most critical point of failure for the delivery of high bandwidth IP services to end users.

In order to simplify the core network design process and make this as precise and efficient as possible, Service Providers require a new breed of engineering tools to help them achieve their goals.

A key requirement of these tools is that they should leverage Operational Measurements available from the network to derive a definitive view over time, of subscriber demand and behavioural characteristics.

Using this information the tools are able to derive a far more accurate assessment of core infrastructure requirements than the demographic and user community assumptions that have traditionally been used to plan network evolution.

Through knowledge based trending and modelling this data, from a present day environment, it is also possible to produce a more accurate correlation between future network design and real world subscriber demand than is available from any other source.

The consequence of this is that design assumption discrepancies are minimized, the evolving network infrastructure is optimally dimensioned with infrastructure and rework costs being significantly reduced.
 

Mobile communication for the masses arrived during the nineties, when European GSM and American CDMA technologies, enabled Mobile Operators to access more customers using a fixed amount of radio spectrum. This phenomena combined with advances in handset technology and battery life, were the catalysts that fuelled a mass rollout of new digital networks across the globe.

Since this time most if not all Operators have considered the RF or ‘Radio Frequency’ Performance aspects of the Network to be amongst the most important in winning and retaining customers.

Indeed today, having built out their RF Infrastructure many Operators still consider RF Coverage, Capacity and Quality of Service to be the foremost factors fuelling customer satisfaction and Revenue Retention. However with the introduction of overlay technologies to power the Mobile Internet, importance is shifting away from RF towards the Core part of the Mobile Network - Meaning everything from the base station through to the PSTN &/or Internet.

The reason for this is that the Core Network is becoming the main conduit and therefore potentially the principal point of failure for the delivery of Mobile Internet services to customers.

As overlay technologies proliferate, the Core Network topology is also breaking up into a subset of soft switch, server-based and IP functionality, whose capacity and performance can be severely eroded by customer mobility.  This makes the Core Network a lot more complex and difficult to engineer and increases the potential for design error that can have a massive cost and revenue impacts.

Core Networks designed without taking into account customer mobility are likely to be far less efficient, causing infrastructure costs to increase drastically. More importantly though, customer quality of service can be impacted, reducing customer satisfaction with the potential for serious revenue erosion.

To maximize financial performance and ensure the success of the Mobile Internet, Mobile Operators must therefore rapidly focus on optimizing the “non-radio” portion of the network.

While RF problems can result in a small number of customers experiencing a localized loss of Mobile Internet Services, problems with the Core can affect them all.

Hence ‘the Core is the new RF’ and to ensure their success Operators must make sure they have the right solutions in place for optimal engineering and perfprmance of this segment of the network.