network capacity calculation
TRANSCRIPT
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Capacity Boosting Solution
White Paper - Network Capacity Calculation
March/2009
TRIANGULUM PTE LTD. CONFIDENTIAL
Copyright 2009 Triangulum PTE LTD., All Rights Reserved
The information contained in this document is the property of Triangulum LTD. Except as specifically authorized in writing
by Triangulum PTE LTD., the holder of this document shall keep the information contained herein confidential and shall
protect same in whole or in part from disclosure and dissemination to third parties and use same for evaluation, operation
and maintenance purposes only.
The content of this document is provided for information purposes only and is subject to modification. It does not
constitute any representation or warranty from Triangulum LTD as to the content or accuracy of the information contained
herein, including but not limited to the suitability and performances of the product or its intended application.
Leveraging Knowledge. Triangulum PTE LTD., the Triangulum logo are trademarks of Triangulum PTE LTD. All othertrademarks are the property of their owners.
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CONTENT
1. INTRODUCTION ........................................................................................................ 3
1.1. OBJECT ......................................................................................................................... 3
1.2. SCOPE OF THIS DOCUMENT............................................................................................... 3
1.3. AUDIENCE FOR THIS DOCUMENT......................................................................................... 3
2. EXECUTIVE SUMMARY ............................................................................................. 4
3. NETWORK CAPACITY ................................................................................................ 5
3.1. CAPACITY AND QUALITY OF SERVICE.................................................................................... 5
3.1.1 Circuit switched QoS ........................................................................................... 63.1.2 Packet switched QoS ........................................................................................... 63.1.3 Network utilization.............................................................................................. 7
3.2. CLASSICAL APPROACH...................................................................................................... 7
3.2.1 Signaling capacity ................................................................................................ 83.2.2 Circuit switch capacity......................................................................................... 93.2.3 Packet switch capacity ...................................................................................... 10
3.3. ADVANCED TRAFFIC MANAGEMENT APPROACH................................................................... 12
3.3.1 Resource utilization ........................................................................................... 123.3.2 Traffic mix management ................................................................................... 133.3.3 New approach for capacity assessment ........................................................... 13
4. CASE STUDY ............................................................................................................ 15
4.1. NETWORK DESCRIPTION................................................................................................. 15
4.2. IMPLEMENTATION RESULTS............................................................................................. 15
5. CONCLUSIONS ......................................................................................................... 19
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1. INTRODUCTION
1.1.
OBJECTThis white paper describes Triangulum's network capacity boosting solution.
1.2.
SCOPE OF THIS DOCUMENT
This white paper contains theoretical background for network capacity
estimation methods, case studies and field results for network capacity
boosting solution implementation.
1.3. AUDIENCE FOR THIS DOCUMENT
Strategic planning technical department.
Network planning and optimization department.
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2. EXECUTIVE SUMMARY
The strong pressure on revenue margins has forced mobile network to re-
examine their approach to mobile network infrastructure investment. Many
advanced operators worldwide are examining different capacity extensions
techniques in order to drive a much lower cost of network ownership.
Designed to cope with the new challenges mobile operator currently facing,
Triangulum has come with a unique capacity extension solution, allowing
mobile operators to benefit from significant operational costs reduction,
while still maintaining a very high Quality of Service for end users and without
investing further money in new infrastructure for capacity extension.
This white paper describes the benefits of implementing Triangulum's
network capacity extension solution and describes case study based on real
implementation on very complicate GSM network.
This white paper is intended for global system for mobile communications(GSM) operators interested in understanding on how capacity extension
solution can help to increase network efficiency and save investments for
GSM radio network expansion.
This white paper contains theoretical background, case studies and field
results for network capacity extension solution implementation.
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3. NETWORK CAPACITY
The network capacity is a keyword for efficient network and operator profit.
But there is a very heavy tradeoff that should be solved in order to achieve
those profit targets from one hand this is a traffic losses and customer
satisfaction due to Quality of Service and from other hand there are
investments for network infrastructure expansion (Capital Expenses CapEx)
and deployment limitations.
Correctly designed network capacity will prevent traffic losses, will provide
high Quality of Service for end users and will minimize investments into
network expansion once network will grow.
There are few different techniques that providing an ability to estimate
network capacity. But prior to network capacity calculation some important
criteria should be defined in order to provide correct results.
3.1.
CAPACITY AND QUALITY OF SERVICE
The Quality of Service definition becomes very complicate for modern GSM
networks due to various traffics' types. A mix of signaling, voice and data
traffics causing headache for network operation departments due to fact that
end user Quality of Service cannot be measured efficiently.
The most common approach to measure Quality of Service in the network is
to define a certain set of Key Performance Indicators (KPIs) and monitor them
over the time. Once some KPIs will exceed predefined thresholds, then a
certain action should be performed in the network in order to bring this KPI
back to normal behavior. This process very often called "Optimization".
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3.1.1 CIRCUIT SWITCHED QOS
Some of well known KPIs are representing a circuit switched network capacity
issues:
SDCCH Congestion Rate
TCH Congestion Rate
It is very important to note that in order to estimate an end user perceived
Quality of Service, mentioned above KPIs should represent only congestion
events that affecting the end user experience and not a condition of "no
available resources" at specific network element. In other words, the end
user related congestion is a ratio between blocked and initiated call attempts
(Call Congestion), while often many infrastructure vendors are suggesting
usage of "Time Congestion" KPIs that are representing only network
resources conditions and not an end user experience.
Mentioned above KPIs may point out on specific bottle neck in the circuit
switched network and initiate a troubleshooting activity. In case of capacity
related KPIs a typical troubleshooting activity is a network resource
expansion i.e. new equipment installation.
3.1.2 PACKET SWITCHED QOS
The Quality of Service definition for packet switched data services is much
more complicated. This is due to reason that different data services have
different requirements for Quality of Service. The end user perceived
experience for data services can be represented by two measures:
Service start - delay
Service end - data throughput
The following graph shows dependency of different data services from two
major KPIs that affecting end user experience:
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3.1.3 NETWORK UTILIZATION
In order to provide a short cycle for Return of Investments (ROI), each
operator should closely evaluate the efficiency of each network element. It is
very important that already deployed infrastructure will be fully utilized for
revenue generating services.
For cell efficiency evaluation the cell utilization KPIs should be monitored.
The definition of utilization KPI is pretty simple and described as ratio
between amount of served traffic and available cells' resources (timeslots).
3.2. CLASSICAL APPROACH
The most commonly used technique is an Erlang B, which calculates cell
capacity under given Grade of Service value.
The Erlang B calculation allows to get a possible amount of traffic that can be
served by specific cell without exceeding a predefined blocking level. The
Erlang B calculation is assuming a certain model of voice traffic behavior,
which is applicable for on-going network dimensioning process. The
dimensioning calculation performed periodically per cell basis and as results
new requirements for hardware (TRXs) installation released for
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implementation. Sometimes, due to hardware or spectrum limitations
(inability to extend an existing cell), new requirements for new sites
deployment released upon dimensioning calculation cycle is finished.
Typically operators are defining a set of threshold for every cell configuration
in order to simplify an operational procedures and decision making for new
hardware deployment.
But implemented radio network features, like: dynamic half rate, AMR half
rate, load sharing and some more, may seriously affect a standard Erlang B
calculation's results due to more complex traffic behavior. This fact may lead
to over- or underestimation of network capacity.
An underestimation of network capacity may lead to significant Quality of
Service degradation for end users and also this will lead to real traffic losses
i.e. revenue losses for operator.
An overestimated (to be on the safe side) network capacity may lead to
excessive network infrastructure deployment (CapEx and OpEx), which
reduces at the end a profit margin for operator.
3.2.1 SIGNALING CAPACITY
The signaling processes in GSM network are responsible for the following
activities:
Mobility Management
SMS sending
Call Setups
It is possible to differentiate signaling traffic according to revenues, where
SMS and Call Setups are revenue generators, while Mobility Management
signaling traffic is consuming network resources without any revenue
generation.
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It is very important that Mobility Management signaling traffic will be as
lower as possible and will not occupy network resources that can be used for
revenue generating traffic types. Excessive Mobility Management signaling
traffic will lead to increase of network resources utilization and may affect
Quality of Service for end users or even lead to higher requirements for new
hardware.
3.2.2 CIRCUIT SWITCH CAPACITY
Circuit switched cell capacity typically estimated by Erlang B calculation,
where each combination of timeslot configuration and given Grade of Service
provides the amount of offered traffic:
Grade of Service
Lines 0.01 0.02
14 7.35 8.20
22 13.65 14.85
30 20.30 21.90
37 26.35 28.25
45 33.40 35.60
52 39.70 42.10
There is a relation between Offered traffic and Served traffic:
Served Traffic = Offered Traffic/(1+GoS)
Since Erlang B is just a mathematical model, it does not represent an instant
traffic load and end user behavior.
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The following graph shows an instant traffic behavior on specific cell, average
traffic volume (erlangs) and available number of timeslots for traffic serving:
Available performance counters are only allowing measurements for Average
Busy Timeslots KPI, which is equal to Served traffic.
3.2.3 PACKET SWITCH CAPACITY
By definition the packet switching services in GSM network performing
according Best Effort approach, where circuit switched traffic has priority
over packet switched. Due to instant voice traffic behavior there is always can
be a situation where circuit switched traffic occupies all available cell's
resources and packet switched traffic cannot be served.
The following graph shows typical instant traffic behavior and resources
availability for packet switched (PS) traffic:
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Erlangs
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Offered Traffic Average Busy TS Max Available TS
Congestion
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In order to overcome packet switched resource availability, often operators
are implementing dedicated packet switched resources for each cell. This
approach allows to provide certain Quality of Service for data traffic, while a
significant network expansion required. The following table contains a real
network TRX expansion sensitivity analysis for introduction network-wide
dedicated packet switch resources:
On-going Voice
Expansion
1 Dedicated
PS TS
3 Dedicated
PS TSs
4 Dedicated
PS TSs
New TRXs required 301 668 1442 2156
Total cells 5493 5493 5493 5493
Cells to be expanded,(%) 5.48% 12.16% 26.25% 39.25%
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3.3. ADVANCED TRAFFIC MANAGEMENT APPROACH
Our Capacity Extension Solution is based on advanced software network
optimization, which utilizes existing radio network features without changing
existing hardware configurations. The advanced traffic management
optimization allows to change a classical network expansion procedures,
while significantly reducing requirements for hardware expansion together
with significant improvement of end user perceived experience.
3.3.1 RESOURCE UTILIZATION
The most important effect from implementation of advanced traffic
management approach is a change of instant traffic behavior. The following
graph shows effect of advance traffic management implementation on cell
instant traffic behavior:
As it clearly shown above, the cell utilization become much higher than in
classical approach, while congestion management technique allows to
improve an end user perceived experience.
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3.3.2 TRAFFIC MIX MANAGEMENT
New traffic management approach allows an efficient circuit and packet
traffic mix with a significant Quality of Service improvement, while no new
requirements for infrastructure deployment. The new technique gives an
opportunity to dedicate a sufficient resource for packet switched traffic
together with ability to share additional resources with circuit switched traffic
on very efficient way, while overall capacity become even higher than it was
prior to implementation. The following graph shows ability of such traffic
management technique:
3.3.3 NEW APPROACH FOR CAPACITY ASSESSMENT
The main question that should be asked after reading this document is how
to calculate a real network capacity and how much this affects end users?
In order to answer those questions we are suggesting to estimate a network
capacity not according to classical way, where the overall network capacity is
accumulated from each cell capacity estimation (Erlang B), rather as amount
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of additional traffic that can be served by network without affecting user
experience.
The proposed method provides a clear understanding of available network
resources and shows the way for significant Capital Expenditures (CapEx)
saving.
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4. CASE STUDY
Our advanced traffic management strategy was implemented in few
complicated mobile networks. Each implementation shows dramatic increase
of network capacity. Typical capacity extension measured values are between
15% and 30%, while in some cases it was even 40%. A network capacity
increase without new hardware is leading to significant reduction in new
infrastructure requirements together with significant reduction of daily
network operation costs due to better network performance and better user
experience.
This case study is based on recent project performed by Triangulum on one of
the most busiest and complicated network around the world. The overall
project timeframe was 4 weeks only.
4.1.
NETWORK DESCRIPTION
The performance improvement solution had been implemented on network
with following specification:
Environment Dense Urban
1800 Cells 250
900 Cells 300
Available 1800 band 80 ARFCNs
Available 900 band 72 ARFCNs
Average TRXs per Cell 8
4.2.
IMPLEMENTATION RESULTS
The following table shows the network performance benchmark prior to
capacity boosting solution implementation (before) and after:
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KPI Before After Delta,%
SDCCH Assign Fail 0.93 0.40 56.99
SDCCH Drop 0.87 0.76 12.64
TCH Assign Fail 0.74 0.65 12.16
TCH Drop 0.73 0.63 13.70
SDCCH Traffic 930.87 847.81 8.92
TCH Traffic 4044.54 4769.85 17.93
SDCCH Cong 0.52 0.34 34.62
Call Congestion 2.82 0.07 97.52
TCH HR Traffic % 8.30 4.83 41.87
Bad Quality UL 2.40 2.00 16.65
Bad Quality DL 2.43 1.87 23.07
1800 TCH Traffic % 33.37 66.04 97.9
900 TCH Traffic % 66.65 33.96 -49.05
GPRS Traffic 2069.93 2845.15 37.45
EDGE Traffic 878.89 1222.35 39.08
TBF CONGESTION 0.32 0.03 90.63
The following graph shows the major project implementation stages and
results in network capacity extension, where dependency of traffic growth
(more than 20%) and Call Congestion disappears and network is able to
accumulate more traffic without losses:
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The same behavior pattern is recognizable for packet switched traffic, where
overall traffic growth was more than 35% for GPRS and EDGE traffic. The
following graph shows dependency of GPRS/EDGE traffic volume versus TBF
congestion:
The half rate vocoder utilization is significantly reduced, while traffic volume
growth was more than 20%:
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EDG E_ TRA FF IC_ ERLA NG G PRS_ TRAF FIC_ ERLA NG TBF_ CONG ES TION
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The implemented traffic management strategy helps to redistribute traffic in
the network between 900 and 1800 bands. This allows to raise utilization of
existing 1800 band cells, while 900 band cells are ready to accumulate traffic
growth without requirements for additional hardware:
The overall calculated capacity is presented in the following table:
Voice traffic growth 20%
Half rate utilization decrease 4%
Voice traffic shifted to 1800 Band 31%
Original capacity reserve 10%
Total Capacity Extension 45%
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5. CONCLUSIONS
The advanced traffic management approach, proposed by Triangulum, can
help mobile network to achieve a double benefit, first by helping to extend
the current network capacity without investing in new infrastructure and
decrease operational costs while maintaining the quality targets, and second
by implementing new techniques and methods that will help the mobile
operator to maintain and operate his network with less efforts and with
higher quality level.
For further discussion on how advanced traffic management approach could
extend a network capacity, please, contact Triangulum PTE Ltd.