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CCAP: A Strategic Tool for Managing Capacity of CDMA Networks Teleware Co. Ltd. in cooperation with Washington University, Saint Louis, Missouri, USA
CCAP: A Strategic Tool for
Managing Capacity of CDMA
Networks
Teleware Co. Ltd.
in cooperation with
Washington University, Saint Louis,
Missouri, USA
2
What is CCAP
Graphical interactive tool for CDMA
Calculates coverage area
Calculates call capacity of a CDMA
network
Calculates subscriber network
performance
Optimizes capacity
3
Unique Characteristics of CDMA
Interference limited capacity
Not cell capacity but network capacity
Soft handoff
Absence of frequency planning
Non-predetermined growth strategy
Power control
Variable rate vocoder
Cell breathing
4
Unique Capabilities of CCAP
Capacity calculation for non-uniform cells
Capacity calculation for non-uniform
loading
Explicit analysis of intra and inter cell
interference
Soft Handoff analysis
Network performance analysis
Power control analysis
Capacity optimization
5
Development of CCAP
Project began 1995
Algorithm tested in Louisiana trial
Used for PCS auction in Korea in 1996
Algorithm updated in 1996 at Washington
University
Joint tool development by Washington
University and Teleware
Version 1.0 completed Q1 1998
6
Scope of CCAP
User definable inputs
– Elevation information
– Antenna attributes (height, gain, …)
– Path loss characteristics (Hata, COST-231, …)
– Shadow fading
– Rayleigh fading
– Imperfect power control
– Sectorization
– Voice activity detection
– Unequal cell sizes
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Scope of CCAP (cont.)
Calculate capacity taking into account
– Hard handoff reception
– Soft handoff reception
– Different number of users in cells
Network subscriber performance (Erlang
blocking probability)
Engineering and optimization of capacity
by power tuning
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CDMA Capacity Issues
Soft capacity based on code division
multiple access
– Cell size
– Loading
– Forward and reverse power
Adjustable capacity by
– Voice activity detection
– Sectorization
– Power control
– Handoff threshold
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CDMA Capacity Issues (cont.)
Power control: transmitted signal power of
mobiles are received at the base station
with the same value
– Open loop: Input from the base station is
measured at the mobile
– Closed loop: Power of the mobile user as
received at the base station is measured. The
mobile is told to increase or decrease the
transmitted power and by how much.
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CDMA Capacity Issues (cont.)
Path loss models: mean signal strength as
a function of distance
– Hata model
– COST-231
Multipath Fading: replicas of the signal
arrive at the receiver
11
CDMA Capacity Issues (cont.)
Shadow fading: is modeled by a log
normal distribution
Rayleigh fading: fast-fluctuations around
those resulting from perturbations caused
by shadow fading
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A
B
Cell I
Cell J
CDMA Capacity Issues (cont.)
Power Compensation
Factor (PCF)
User A will cause an
extremely high
interference to user B.
13
CDMA Capacity Issues (cont.)
Power Compensation
– Fine tune the nominal power of the users
– PCF defined for each cell
– Optimal PCFs maximize the capacity of the
entire network
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Base Station Database
Base Station
– Base Station Id
– Easting and Northing
– Number of antennas or sectors
Antenna
– Direction and beamwidth
– Forward power
– Power compensation factor
– Demand Estimator
– Height and gain
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Define Area of Service
Parameters needed:
– Base Station Database
– Eps: Receiver sensitivity [-120 dBm]
– Fc: Carrier Frequency [1800 MHz]
– Hte: Base Station antenna height [30 m]
– Hre: Mobile antenna height [1.5 m]
– dx: Horizontal grid size [300 m]
– dy: Vertical grid size [300 m]
(all user controlled)
Area is divided into grids
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Inter-Cell Interference
Parameters needed:
– m: Path Loss Exponent [4]
– sigma_s: Standard deviation
for the shadow fading [6 dB]
– Rayleigh: [0] for off [1] for on
– Alpha: Total number of users
in a cell divided by the
minimum number of users in
every cell.
Fij: interference of cell I on
cell J is obtained.
Cell J
Cell IRj
RiA
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Calculation of Capacity
Parameters needed:
– W/R: Total bandwidth / User data rate [19.31 dB]
– Eb/Io: Bit energy / Interference [7 dB]
– rho: Voice activity factor [3/8]
– sigma_c: Standard deviation for the imperfect
power control random variable [2.5 dB]
– Beta: Power compensation factor [1 1 1 … 1]
– Target_Pout: Log10 (Blocking Probability) [-2]
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Calculation of Capacity (cont.)
Call capacity is calculated for each cell.
Smallest value defines the capacity of the
network.
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Subscriber Performance
Parameters needed:
– erl_user: user load in Erlangs [0.025]
– N is the number of trunks or channels [1]
– B is the blocking probability [0.01]
Maximum sustainable subscribers per cell
Subscriber network performance
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Optimizing Capacity
Parameters needed:
– Initial Power Control Factor
– Same inputs as for capacity calculation
The gradient descent algorithm is used.
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Considerations for Fading
The inter cell interference - shadow fading
and Rayleigh fading
Power control overcomes both large scale
path loss and shadow fading but not
Rayleigh fading
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Soft Handoff
User is permitted to be in soft handoff to
its two nearest cells.
Better frame received by either base
station is accepted by the network.
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Soft Handoff (cont.)
Soft handoff region
for cell 0: six pointed
star
Propagation loss to
neighbor is less than
to the zeroth base
station
Within So, interference
into the zeroth base
station
1
3
4
2
5
6
0
So
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Power Compensation Factor
Initial default value is 1 for every cell
Optimize capacity by optimizing the PCF
New PCF is the factor that the nominal
power needs to be increased by for every
cell
Each PCF is used by its Base Station in
the Closed Loop Power Control
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CCAP Report
Interference pattern
Call capacity
Optimal power control factors
Optimal capacity
Subscriber network performance
