007 wcdma radio network capacity planning
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007 Wcdma Radio Network Capacity PlanningTRANSCRIPT
WCDMA Radio Network Capacity Planning
Huawei Technologies Co., Ltd.
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Revision Record
Date Version Change description Author
1-07-2007 1A Victor Toledo
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Table of Contents
1 Traffic Model........................................................................................................ 9
Service overview............................................................................................ 9
QoS type ..................................................................................................... 11
Traffic Model ................................................................................................ 12
CS Traffic Model ......................................................................................... 13
PS Traffic Model .......................................................................................... 14
2 Uplink Capacity Analysis ................................................................................ 20
Uplink Interference Analysis- Uplink Interference Composition.................... 24
Uplink Interference Analysis- Uplink Load Factor ........................................ 23
3 Downlink Capacity Analysis ............................................................................ 26
Downlink Interference Analysis.................................................................... 29
4 Multi-service capacity estimation procedure ................................................. 30
Network capacity restriction factors ............................................................. 30
Downlink Channel code resources .............................................................. 32
Channel Element ........................................................................................ 34
Iub Interface Capacity ................................................................................. 36
Typical capacity design methods-Erlang B formula ..................................... 37
Typical capacity design methods- Equivalent Erlangs ................................. 41
Typical capacity design methods- Campbell´s theorem............................... 42
5 Network estimation procedure ........................................................................ 45
6 Capacity enhancement technologies.............................................................. 46
Transmission Diversity................................................................................. 46
Sectorization ................................................................................................ 48
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Objectives
Upon completion of this module, you will be able to:
� Grasp the parameters of 3G traffic model
� Understand the factors that restrict the WCDMA network capacity
� Understand the methods and procedures of estimating multi-service
capacity
� Understand the key technologies for enhancing network capacity
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Foreword
� WCDMA is a self-interference system
� WCDMA system capacity is closely related to coverage
� WCDMA network capacity has the “soft capacity” feature
� The capacity planning of the WCDMA network is performed under certain
traffic models
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1 Traffic Model
Service Overview
� The WCDMA system supports multiple services
� Variable-rate services (e.g. AMR voice)
� Combined services (e.g. CS & PS)
� High-speed data packet services (384k service)
� Asymmetrical services (e.g. stream service )
� Large-capacity and flexible service bearing
The WCDMA system provides the users with flexible and diversified services, which
is an important characteristic of WCDMA. In different propagation environment, the
WCDMA system requires reaching different target transmission rate values, e.g., in high-
speed motion, the rate is up to 144 kbps; in case of walking, the rate is up to 384 kbps,
and the rate in indoor environments is up to 2 Mbps. The WCDMA system supports the
variable-rate service, hybrid service, high-speed data packet service (multimedia);
supports uplink/downlink rate-asymmetrical services (Internet access); considers the
future service development requirements, and provides sufficient capacity and data
bearing capability of flexible rate matching methods. The QoS of the WCDMA service is
described by data rate, bit error rate (BER), transmission delay, and delay jitters.
Different services and service composition proportions affect the WCDMA performance
significantly. Therefore, the WCDMA network planning analysis should be based on the
prerequisite of a certain traffic model estimate.
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QoS Type
Table I.- Services and quality of service.
For the session-type service, requirement on end-to-end delay is strict. For example,
for the voice service, the delay is required to be smaller than 150ms, and must not
exceed 400ms; otherwise, it will be difficult to understand the voice. The session-type
services are typically carried by the CS domain. For the session-type services, the
system can perform no queue processing for the calls. In this case, we can use the
Erlang B formula or the extended Erlang B formula to calculate.
Compared with the session-type service, the stream-type service imposes low
requirement on the end-to-end delay. Generally, the stream-type service tolerates the
call waiting to a greater extent, and can provide the call queue mechanism. In this case,
we can use the Erlang C formula to calculate the blocking probability of this type of users
(defined as the probability of the call waiting for a specified time).
Interaction-type service refers to the service through which the user requests data
from the server. The service is described with the terminal user’s request response
pattern. Therefore, round-trip delay is the most important index of this service type. The
interaction-type services are typically carried on the CS domain. The background-service
tolerates delay to the greatest extent, and can tolerate the delay of a magnitude of an
hour. Due to such great delay tolerance, the system can save such requests in the busy
hour, and respond when the channel becomes idle; meanwhile, for such services, once a
request with higher QoS comes in, the processing can be stopped at any time. The
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system decides startup and termination at any time, the above formulas—Erlang B
formula and Erlang C formula are not applicable. Generally, according to the difference
between the maximum number of channels and the busy-hour average occupied
channels, we can calculate the traffic of the background-type service. The users of
traffic-type services also tolerate the call waiting to some extent. The system provides a
queue mechanism, and uses the Erlang C formula to calculate the blocking rate.
Objectives of Setting Up Traffic Model
� In order to determine the system configuration, we need to determine the
capacity of the air interface first.
� In the data service, different transmission model will generate different
system capacities.
� We need to set up an expected data transmission model of the customer
so that we can plan the network properly.
� In order to set up a right model, the operator should provide some statistic
data as reference.
The system has many key performance indicators, e.g., coverage, spectrum
efficiency, which are closely related to the type of service carried by the system.
Therefore, in order to predict the performance of the WCDMA system in carrying a
certain type of service, we must know the service features. Service features are
represented by the traffic model.
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Traffic Model
� Traffic model is a means of researching the capacity features of each
service type and the QoS expected by the users who are using the service from
perspective of data transmission.
� In the data application, the user behaviour research mainly forecasts the
service types available from the 3G, the number of users of each service type,
frequency of using the service, and the distribution of users in different regions.
Contents of a traffic model
The contents of a traffic model consist of service patterns and user behaviours.
Service pattern refers to the service features, and user behaviour refers to the conduct of
people in using the service. In the actual application, service pattern is closely related to,
and sometimes is no strictly different from, the traffic measurement model.
Figure 1.- The contents of the traffic model.
By determining the service pattern and the user behaviour parameters, we
determine the traffic models of various services in the network. By calculating the hybrid
services of multiple traffic models, we determine the network system configuration.
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Typical Service Features Description
� Typical service features include the following feature parameters:
� User type (indoor ,outdoor, vehicle)
� User’s average moving speed
� Service Type
� Uplink and downlink service rates
� Spreading factor
� Time delay requirements of the service
� QoS requirements of the service
For each service, since the channel structure and demodulation method are different,
the required uplink rate is different from the required downlink rate even for the same
service type and the same data rate. For a typical service, we first need to identify
whether it is uplink or downlink rate. A typical service can be described by the following
parameters:
(1) User type (indoor users, users inside a vehicle, outdoor users)
(2) User’s average moving speed (km/h)
(3) Voice, real-time data, non real time data
(4) Uplink and downlink service rates (kbps)
(5) Spread factor (SF)
(6) Signal delay requirement of the service (ms) The above parameters
ultimately determine the QoS requirements of the service.
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CS traffic model
� Voice service is a typical CS services. Voice data arrival conforms to the
Poisson distribution. Its time interval conforms to the exponent distribution.
� Key parameters of the model:
� Penetration rate
� BHCA Mean busy-hour call attempts
� Mean call duration (s)
� Activation factor
� Mean rate of service (kbps)
(Erl)For CS service, mean busy-hour traffic (Erlang) per user = BHCA * mean call
duration /3600 (Erl)
(kbps)Mean busy-hour throughput per user = BHCA * mean call duration * activation
factor * mean rate of service (kbps)
In the actual application, service pattern is closely related to, and sometimes is no
strictly different from, the traffic measurement model.
CS Traffic Model Parameters
� Mean busy-hour traffic (Erlang) per user = BHCA * mean call duration
/3600
� Mean busy hour throughput per user (kbit) (G) = BHCA * mean call
duration * activation factor * mean rate
� Mean busy hour throughput per user (bps) (H) = mean busy hour
throughput per user * 1000/3600
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PS traffic model
� The most frequently used model is the packet service session process
model described in ETSI UMTS30.03.
Figure 2.- Packet service session.
Figure 3.- Packet session description.
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PS Traffic Model Parameters
Figure 4.- Parameters used in the PS traffic model.
The service pattern-related parameters in the traffic model include: these
parameters commonly determine the pattern of one session.
We identify the service types through the different values of the parameters.
Packet Call Num/Session: Takes on the geometric random distribution
Reading Time (sec): Takes on the geographic random distribution
Packet Num/Packet Call: Takes on the geographic random distribution
Packet size: Takes on the Pareto random distribution
When using the parameters, the average values will apply.
Parameter Determining
� The basic parameters in the traffic model are determined in the following
ways:
� Obtain numerous basic parameter sample data from the existing
network.
� Obtain the probability distribution of the parameters through
processing of the sample data.
� Take the distribution most proximate to the standard probability as
the corresponding parameter distribution through comparison with the
standard distribution function.
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We have determined the traffic model parameters. The linchpin is to determine such
parameter values. The parameter value varies between different services.
ParetoGeneral standard probability distributions include: logarithmic normal distribution,
Pareto distribution, geometrical distribution, and negative exponent distribution.
� Typical Bearer Rate (kbps):
� Bearer rate is variable in the actual transmission process.
� BLER:
� In the PS service, when calculating the data transmission time, the
retransmission caused by erroneous blocks should be considered.
Suppose the data volume of service source is N, the air interface block
error rate is BLER, the total required data volume to be transmitted via the
air interface is:
During the planning, according to the actual situation, we select the typical value of
the bear rate. It will affect the activation factor, but will not affect the correctness of the
planning result.
Block error rate belongs to QoS. The service control mechanism will retransmit the
erroneous blocks. This will increase the traffic to be transmitted.
PS User Behavior Parameters
Figure 5.- User behavior parameters for PS.
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The country, region, life custom and economic level will affect the service
distribution. In the planning, we divide the users into high-end users, mid-end users and
low-end users, and believe that the BHSA and penetration rate are different between
different types of user groups. Currently, we can only use the existing analysis to make
prediction. In the future, the progress of the construction of the WCDMA pilot system will
provide us with reference.
� Penetration Rate:
� The percentage of the users that activates this service to all the
users registered in the network.
� BHSA:
� The times of single-user busy hour sessions of this service
� User Distribution (High, Medium, Low end)
� The users are divided into high-end, mid-end and low-end users.
Different operators and different application situations will have different
user distributions.
PS Traffic Model Parameters
• Session traffic volume(Byte): Average traffic of single session of the
service
• Data transmission time (s) : The time in a single session of service for
purpose of transmitting data.
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Holding Time(s): Average duration of a single session of service
� Active factor:
� The weight of the time of service full-rate transmission among the
duration of a single session.
• Busy hour throughput per user (Kb):
• PS throughput equivalent Erlang formula (Erlang)
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2 Uplink capacity analysis
Uplink Interference Analysis—Uplink Interference Composition
Basic Principles
� In the WCDMA system, all the cells share the same frequency, which is
beneficial to improve the system capacity. However, co-frequency multiplexing
causes interference between users. This multi-access interference restricts the
capacity.
� The radio system capacity is decided by uplink and downlink. When
planning the capacity, we must analyze from both uplink and downlink
perspectives.
Interference is the main factor that decides the system performance of the cellular
system. The interference in a cellular system consists of two parts: co-frequency and
adjacent frequency interference. All users in the WCDMA system use the same band. All
the users are different by modulating the respective signal to the code sequences that
are mutually orthogonal. Therefore, the receiving signal is the sum of all user signals and
the channel noise.
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• Receiver noise floor PN
− K:Boltzmann constant, 1.38×
− T:Kelvin temperature, normal temperature: 290 K
− W:Signal bandwidth, WCDMA signal bandwidth 3.84MHz
− 10lg(KTW) = -108dBm/3.84MHz
� NF = 3dB (typical value of macro cell BTS)
� IOwn:Interference from users of this cell
Interference that every user must overcome:
� is the receiving power of the user j , is active factor
� Under the ideal power control :
� Hence :
� The interference from users of this cell is the sum of power of all the
users arriving at the receiver:
• :Interference from users of adjacent cell
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� The interference from users of adjacent cell is difficult to analyze
theoretically, because it is related to user distribution, cell layout, and
antenna direction diagram.
� Adjacent cell interference factor :
� When the users are distributed evenly
− For omni cell, the typical value of adjacent cell interference
factor is 0.55
− For the 3-sector directional cell, the typical value of adjacent
cell interference factor is 0.65
Uplink Interference Analysis
Define
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Uplink Interference Analysis—Uplink Load Factor
� Define the uplink load factor
When the load factor is 1, is infinite, and the corresponding capacity is called
“threshold capacity”.
� Under the above assumption, the threshold capacity is approx 96 users.
Uplink Interference Analysis—Load Factor and Interference
� According to the above mentioned relationship, the noise will rise:
� Suppose that:
� All the users are 12.2 kbps voice users, the demodulation threshold Eb/No = 5dB
� Voice activation factor vj = 0.67
� Adjacent cell
− interference factor
− i = 0.55 Figure 6.- Total Interference calculation.
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Figure 7.- Noise raise against Load factor.
Uplink Interference Analysis—Limitation of the Current Method
� The above mentioned theoretic analysis uses the following simplifying
explicitly or implicitly:
� No consideration of the influence of soft handover
− The users in the soft handover state generates the
interference which is slightly less than that generated by ordinary
users.
� No consideration of the influence of AMRC and hybrid service
− AMRC reduces the voice service rate of some users, and
makes them generate less interference, and make the system
support more users. (But call quality of such users will be
deteriorated)
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− Different services have different data rates and demodulation
thresholds. So, we should use the previous methods for analysis,
but it will complicate the calculation process.
− Since the time-variable feature of the mobile transmission
environment, the demodulation threshold even for the same service
is time-variable.
� Ideal power control assumption
− The power control commands of the actual system have
certain error codes so that the power control process is not ideal,
and reduces the system capacity
� Assume that the users are distributed evenly, and the adjacent cell
interference is constant.
� Considering the above factors, the system simulation is a more
accurate method:
− Static simulation: Monte Carlo method
− Dynamic simulation
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3 Downlink Capacity Analysis
Downlink Interference Analysis—Downlink Interference Composition
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Suppose the power control is desired, we obtain
Then
Because
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Then
Resolve PT to obtain
where ij is the adjacent cell interference factor of the user,
defined as:
According to the above analysis, we can define the downlink load factor:
� When the downlink load factor is 100%, the transmitting power of the BTS
is infinite, and the corresponding capacity is called “threshold capacity”.
� As different from the theoretic calculation of uplink capacity, and in
the downlink capacity formula are variable related to user position. Namely, the
downlink capacity is related to the spatial distribution of the users, and can only be
determined through system simulation.
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Downlink Interference Analysis—Simulation Result
Figure 8.- Result simulation for downlink interference analysis.
Downlink Interference Analysis—Simulation Result Analysis
� When the transmitting power of the BTS is 43dBm (20W), the supported
maximum number of users is approx 114.
� In order to ensure system stability, we do not allow the mean transmitting
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power of the BTS to be more than 80% of the maximum transmitting power,
namely, 42dBm. This way, the supported number of users is 111.
4 Multi-service capacity estimation
Network capacity restriction factors
� The WCDMA network capacity restriction factors in the radio network part
include the following:
� Uplink interference
� Downlink power
� Downlink channel code resources (OVSF)
� Channel element (CE)
� Iub interface transmission resources
Uplink interference
If the uplink interference of the BTS reaches a certain extent, the terminal will be
impossible to meet the requirements of demodulation quality through improving the
transmitting power, and the terminal will be impossible for access or service.
Downlink power
When the downlink transmitting power of the BTS reaches the load threshold, no
redundant power is available for allocation. This will make the terminal impossible for
access or service.
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Downlink channel code resources
In the downlink direction, scrambles are used for identifying the cells, while the
channel codes are used for identifying the channels. The WCDMA system uses the
orthogonal variable spread factor (OVSF) code sequence in a tree distribution. The
actually usable code sequence set is made up of the code words of SF=4~128.
Channel processing unit
In view of cost, the Channel element will be configured to full capacity. In this case,
the circumstance may occur that no channel units are available for allocation.
Iub interface capacity
The Iub interface currently still uses the E1 link as physical media, which may a
bottleneck to the radio network capacity.
Downlink Transmit Power
� The downlinktransmit power has two parts: one part is used for common
channel, and the other part for dedicated (traffic) channel.
� The transmit power is allocated by the cell to each user varies with service
demodulation threshold, propagation path loss and the interference received by
the user
� The downlink transmit power of the cell is shared by all the users in the cell
� We generally use the simulation method to analyze the downlink
interference.
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Figure 9.- UE number against downlink NodeB power.
The transmitting power allocated by the cell to each user varies with service
demodulation threshold, propagation path loss and the interference received by the user.
The propagation path loss is related to the user’s position relative to this cell. The user’s
position relative to the adjacent cell BTS and this cell’s BTS, and the transmitting power
of this cell’s BTS and the adjacent cell BTS decide the interference received.
The downlink transmitting power of the cell is shared by all the users in the cell.
When the maximum transmitting power among the downlink transmitting powers that
arrive at the BTS reaches a certain threshold, the new users will be impossible to access.
Therefore, we can define the ratio of the downlink power of cell to the maximum
transmitting power of the BTS as the downlink load of the cell.
Due to the complexity of the downlink capacity analysis, we generally use the
emulation method to analyze it.
Downlink Channel Code Resources
� The WCDMA network use the codes whose SF is 4~512. The smaller the
SF is, the higher the supported data rate will be.
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� In the code tree, the allocable codes should meet the following conditions:
� No codes on the path from this code to the root node of code tree
are allocated
� No codes in the sub-tree whose root node is this code are allocated
� Try to reserve the code words whose SF is small, so as to improve
the utilization efficiency.
Figure 10.- OVSF codes.
The generation of the channel code uses the Hadamard matrix. The downlink
OVSF codes are like a code tree, and the SF is spread factor.
In the process of code allocation, it is appropriate to try to reserve the code words
whose SF is small for purpose of improving utilization, because the code words whose
SF is small can support higher data rates and can be split into code words whose SF is
larger.
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Downlink Channel Code Resources
Figure 11.- Example of code resources allocation.
Channel Element (CE)
� The Channel element the quantitative data that measures the resources
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logically occupied for service processing.
� The resource occupied by the service processing is mainly related to the
spreading factor of this service. The smaller the SF is, the greater the data traffic
will be, and more resources will be occupied.
� The SF of typical services are:
� AMR12.2kbps SF=128
� CS64kbps SF=32
� PS64kbps SF=32
� PS144kbps SF=16
� PS384kbps SF=8
Due the technical features of the WCDMA, compared with the 2G systems such as
GSM, the RNC and Node B present enormous capacity. For example, for the fully
configured NodeB, the number of channels of one carrier is 128, which is more than 10
times of that supported by a TRX of GSM. One uplink processing unit of our NODEB 1.3
has the processing capacity of 128 12.2kbps voice channels. One 3*1 WCDMA BTS is
equivalent to the GSM sites of one S10/10/10. At the beginning of the WCDMA network
construction, so high a capacity is not a necessity, and only a portion of it is required
(e.g., 10%). If we offer the quotation based on the maximum hardware channel capacity
of TRX like the GSM, it will make the operators incur enormous cost and mismatch the
user quantity. To reduce the initial investment, the operator is bound to pay the
equipment price to the supplier according to the actual use capacity, and, subsequently,
pay more equipment prices with the increase of the user quantity. This way, the operator
will reduce the initial investment and mitigate the risks.
� If we define the resources required for processing AMR 12.2kbps services
as a channel processing unit, the number of channel processing units occupied by
other services is:
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� AMR12.2kbps 1
� CS64kbps 4
� CS144kbps 8
� CS384kbps 16
� PS64kbps 4
� PS144kbps 8
� PS384kbps 16
The relative proportion of the services with different SFs can be calculated in the
following formula (related to version):
Num_SF128/128 + Num_SF64/64 + Num_SF32/32 + Num_SF16/16 + Num_SF8/8=
1
The channel unit of service can represent the channel resources occupied when
establishing the connection. It will be used when calculating the hybrid service capacity
of the cell. It is used for calculating the number of required channel boards and the
number of channel processing units configured on the board.
Iub Interface Capacity
� The contents transmitted on the Iub interface include:
� The user data encapsulated in the AAL2 format (common channel
and dedicated channel)
� Signaling data encapsulated in the AAL5 format
� BTS operation & maintenance data
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Figure 12.- Protocol stack for Iub interface.
When calculating the Iub interface traffic, it is necessary to calculate the throughput
rate of each service type. According to the planned user quantity, we obtain the total
traffic of the Iub interface, and estimate out the transmission configuration of the Iub
interface.
� Factors to be considered when estimating the interface capacity:
� Frame coding efficiency. Through segmentation and encapsulation
of the application data at each layer, the data quantity at the bottom layer
will be increased to different extents compared with the application data at
the upper layers.
� Traffic. More users will generate more data traffic.
� Maintenance efficiency. Certain bandwidth is required in the
background maintenance for BTS data transmission.
Typical capacity design methods
Erlang-B Formula
� The Erlang-B formula is used for estimating the peak traffic that meets
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certain call loss rate when the average traffic (Erlang) is given.
� The Erlang-B formula is only used for
� Circuit switched services
� Single service
� The WCDMA system provides CS and PS domain multi-services which are
determined by the radio network planning.
Figure 13.- Variation of demand with time.
In the CS domain, we use the Erlang quantity to express the traffic volume. Assume
the traffic arrival takes on a Poisson distribution.
� The prerequisite of the Erlang-B is the requests of resources take on a
Poisson distribution, namely, its variance is equal to its mean value.
� If, when a service establishes a link, the service requires the resources
which are more than the unit resources, the resource request is no longer equal to
its mean value, and the Erlang-B formula is not applicable in this case.
� Comparison of multi-service capacity estimation methods :
� Post Erlang-B
� Equivalent Erlangs
� Campbell’s Theorem
For the unitary CS services, the resources are estimated in unit resources, e.g., a
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64kbps timeslot.
Post Erlang-B((((一一一一))))
� By summing up the capacities required for different services, we obtain the
capacities required for the combined services.
� No consideration of the resource efficiency of different services
Figure 14.- Post Erlang B (-) resources calculation.
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Method of using the Post Erlang-B: First, calculate the channel resources required
according to the traffic volume of each service, then sum up the channel resources
required for all services. This method is vulnerable to overestimation of the channel
resources. We will understand this through the following example.
� Consider that two services share resources
� Service 1: 1 unit resource/connection.12 Erlang
� Service 2: 3 unit resources/connection.6 Erlang
� Calculate capacity required for each service
� Service 1: 12 Erlangs require 19 connections (19 unit resources),
meeting the 2% blocking rate
� Service 2: 6 Erlangs require 12 connections (equivalent to the 36
unit resources of service 1), meeting the 2% blocking rate
� Total 55 unit resources
� Consider that two services use the same resources
� Service 1: 1 unit resource/connection.12 Erlang
� Service 2: 1 unit resource/connection.6 Erlang
� Calculate capacity required for each service
� Service 1: 12 Erlangs require 19 connections, meeting the 2%
blocking rate
� Service 2: 6 Erlangs require 12 connections, meeting the 2%
blocking rate
� Total 31 unit resources
� However, the reasonable results should be: 18 Erlangs require 26
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connections for meeting the 2% blocking rate.
As seen from the above example, two services with the same unit resources have
18Erlangs in total. The actually required channel resources are 26 resources. However,
according to the Post Erlang-B method, 31 resources are required. So this method
obviously overestimates the required channel resources.
Equivalent Erlangs
� By converting the bandwidth from one service to another service, combine
different services and then calculate the required capacity.
� Selecting different services as the measurement benchmark will lead to
different capacity requirements.
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Figure 15.- Equivalent Erlang estimations.
The equivalent Erlang method is to convert the service of two service with different
unit channel resources to the total Erlangs of one of the services, then search the
Erlang-B table to obtain the total channel resources required. In this method, if selecting
different services as measurement benchmark, different channel resource requirements
will result.
� Consider that two services share resources
� Service 1: 1 unit resource/connection.12 Erlang
� Service 2: 3 unit resources/connection.6 Erlang
� If using service 1 as measurement benchmark, the two services are
equivalent to 30 Erlangs in total.
� 30 Erlangs require 39 connections (39 unit resources), meeting the
2% blocking rate
� If using service 2 as measurement benchmark, the two services are
equivalent to 10 Erlangs in total.
� 10 Erlangs require 17 connections (equivalent to 51 unit resources
of service 1), meeting the 2% blocking rate
As seen from the above example, if the calculation uses service 1 as benchmark,
the result is 39 channel resources; if the calculation uses service 2 as benchmark, the
result is 51 channel resources required. The difference between the two results is 12
channel resources.
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Campbell’s Theorem (I)
The Campbell theorem introduces the mean value and variance, so that the multi-
service capacity calculation result is more proximate to the actual value compared with
the foregoing two methods. Here, the amplitude “ai” represents the channel resources
required for a single connection. Generally, we specify the amplitude of the Voice12.2k
service as 1, hence:
Amplitude of other service relative to the Voice12.2k service = (service bit rate *
Eb/No) / (Voice12.2k service bit rate * Eb/No of Voice service)
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For the same GoS, different services require different capacities. According to the
calculation method of the Campbell theorem, as calculated respectively on the
benchmark of service 1 and service 2, the obtained two results will be only 2 channel
resources different from each other.
The comparison of the different capacity method
� Post Erlang-B
� Service 1 (1 unit resource/connection, 12Erl) and service 2 (3 unit
resources / connection, 6Erl), requiring 55 unit resources in total
� Equivalent Erlangs
� Calculated according to benchmark of service 1 (1 unit
resource/connection, 12Erl), a total of 39 unit resources are required
� Calculated according to benchmark of service 2 (3 unit
resources/connection, 6Erl), a total of 51 unit resources are required
� Campbell´s Theorem
� In the same conditions, 47~49 unit resources are required in total.
As illustrated for the three methods above, we assume that the conditions are
identical, calculation result through the Post Erlang-B method is 55 channel resources
required; the calculation result through the Erlang method is 39~51 channel resources
required; and the calculation result through the Campbell method is 47~49 channel
resources required. The calculation result through the Campbell theorem is more
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proximate to the actual value compared with the other two methods.
5 Network estimation procedure
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Figure 16.- Network estimation flow.
6 Capacity Enhancement Technologies
Transmission Diversity ----TxDiv
� Txdiv has two types in WCDMA system:
� Open loop TxDiv
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� Closed loop TxDiv
� TxDiv could improve downlink capacity
� Need additional amplifier
� Need equipment support
� Don’t need additional antenna
Figure 17.- Transmission Diversity feature.
� Gain of TxDiv
� The gain is obtained due to additional amplifier
� Pure gain is obtained due to TxDiv technology
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Figure 18.- Downlink capacity with Tx diversity.
� Gain of TxDiv
� The gain is obtained due to additional amplifier
� Pure gain is obtained due to TxDiv technology
� TxDiv should reduce downlink power
� TxDiv should reduce requirement of Eb/N0
� Usually ,closed loop TxDiv would obtain more gain than open loop TxDiv.
Figure 19.- Comparison of target Tx Eb/No.
� Transmission diversity can enhance the downlink capacity and coverage.
� Conclusion of capacity enhancement of transmission diversity
� STTD mode: Capacity increase of 17 ~ 24%
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� TxAA(1) mode: Capacity increase of 16 ~ 23%
� TxAA(2) mode: Capacity increase of 31 ~ 37%
� For the single-antenna transmitting, transmitting diversity can obtain extra
gain to enhance the capacity and coverage.
� In the WCDMA system, transmitting diversity breaks down into two types:
open loop transmitting diversity, and closed loop transmitting diversity. The latter
is subdivided into two modes. Different transmitting diversity modes obtain
different gains.
� Here the calculation of capacity and coverage of gain is similar to that of
receiving diversity. The main affecting factor is the downlink capacity coverage
and capacity.
Sectorization
� In the dense urban areas and the normal urban areas with high traffic,
increasing sectors of the BTS is a method of improving the capacity.
� 6-sectors BTS generally use the antenna whose horizontal lobe is 33º
� The capacity of a 6-sector BTS is 1.67 times that of a 3-sector BTS
� The capacity of a 3-sector BTS is 2.77 times that of a omni- BTS
• When there are many sectors, e.g., 6 sectors, it is necessary to plan the
mount height, azimuth angle and down tilt angle of the antenna carefully.
• In order to obtain higher capacity, the sector azimuth angle should be
designed as mutually complementary to prevent blind area of coverage. For 3-
sector and 6-sector circumstances, the azimuth angle can be planned with the
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regular hexagon apex excitement method.
• The down tilt angle of the antenna should be designed properly to align
the upper half power point of the antenna lobe with the cell edge.
• From perspective of the BTS capacity, when the cell radius is small, the
capacity of a 3-sector BTS is 2.77 times that of an omnidirectional BTS, and the
capacity of a 6-sector BTS is 1.67 times that of a 3-sector BTS.
• When the cell radius increases, the sectors will increase, and the sector
antenna gain will be higher. For the uplink, the coverage performance will be
better; for the downlink, the coupling loss will be less, and the downlink capacity
will be higher.
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