1 an analytical model for the dimensioning of a gprs/edge network with a capacity constraint on a...
DESCRIPTION
Background 2G - GSM system (Global System for Mobile Communications) 2.5G system GPRS(General Packet Radio Service) EDGE (Enhanced Data rates for Global Evolution) 3TRANSCRIPT
1An Analytical Model for the Dimensioning of a GPRS/EDGENetwork with a Capacity Constraint on a Group of Cells
r02922008, r02922133, r02944039
Nogueira, Georges, Bruno Baynat, and Pierre EisenmannACM 2005
Outline Background Single Cell System Multiple Cell System Model Validation Performance Results Examples Conclusion
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Background
2G - GSM system (Global System for Mobile Communications)
2.5G system GPRS(General Packet Radio Service) EDGE (Enhanced Data rates for Global
Evolution)
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Circuit Switched vs. Packet Switched
Circuit Switched
Packet Switched
GPRS – Evolve from GSM Timeslot is the basic unit for sending packet Provide fast reservation Four channel coding schemes (CS1 、 CS2 、 CS3
、 CS4) Hardware Add PCU(packet control unit) in BSC Add SGSN, GGSN for sending packet
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EDGE
also known as Enhanced GPRS EDGE uses higher-order PSK/8 phase
shift keying (8PSK)
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Single Cell System Some Assumption and parameters
All mobiles have the same reception capability. they are “(d+u)”
tB: the system elementary time interval xB: the number of data bytes transferred
during tB over one time-slot
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Single Cell System For GPRS
For EDGE
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Single Cell System tbfmax: the maximum number of mobiles that
can simultaneously have an active downlink TBF(Temporary Block Flow)
ON periods correspond to the download of an element
Size is characterized by a discrete random variable Xon
an average value of xon bytes OFF periods correspond to the reading time modeled as a continuous random variable Toff average value of toff seconds
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Markovian Analysis
ON/OFF distributions : memoryless (assumed)
Linear discrete-time Markov chain.
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Markovian Analysis12
Markovian Analysis13
Markovian Analysis14
Markovian Analysis
All average performance parameters of a single cell can be expressed as function of
dimensionless parameter x cell capacity T mobiles capacity d numbers of mobiles in the cell N
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Multiple Cell System16
17Multiple Cell System
18Multiple Cell System
19Multiple Cell System
20Model Validation
Validate the analytical model by comparison with simulation results.
OPNET
21Identical cells
P cells are identical in terms of available radio resources and offered traffic.
All the mobiles generate the same traffic.
22@ P
23Different cells
The characteristics of all cells in terms of offered traffic and radio conditions are randomly generated.
All the mobiles generate the same traffic. Typically, we could represent a cell with a majority of
business users, having a specific call profile.
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@ P
25Performance Results
Assume that all the cells are identical.
Similar studies can be performed on heterogeneous cells systems with no additional complexity.
26@ P @ Mmax
Pr↓Q↑
U↑ X↓
PMQ max~
↑
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Pr↑
↑
Q↓
U↓ X↑
@ T @ P
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↑
Q(-)
U(-) X(-)
Pr↑
@ T @ N
29Performance Graphs
Can be instantaneously obtained with our analytical solution.
They allow to directly derive any performance parameter knowing the traffic load profile (N, x).
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@ N
@ x U
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@ N
@ x X
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@ N
@ x Pr
33 Assume here that the network dimensioning
is based on a maximum acceptable blocking rate of 2% for data transfer requests. In GPRS or EDGE, a transfer request rejection results in 5
seconds idle time before a subsequent request is allowed.
For this target blocking rate, we want to find the values of: Pmax: the maximum number of cells Nmax: the maximum number of GPRS mobiles that can
be admitted in each cells
Example:Maximum blocking probability
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@ N
@ x Pmax , with Pr ≦ 2%
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@ P
@ x Nmax , with Pr ≦ 2%
36 A typical 1 time-slot threshold is chosen,
i.e. a mobile that starts downloading a page has the guarantee to obtain at least 1 time-slot per TDMA for the entire transfer duration.
For this target blocking rate, we want to find the values of: Pmin: the minimum number of cells Nmax: the maximum number of GPRS mobiles that can
be admitted in each cells
Example:Minimum normalized throughput
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@ N
@ x Pmin , with X ≧ 1TS
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@ P
@ x Nmax , with X ≧ 1TS
Conclusion & future work
• Provide computational efficiency and accuracy for performance and dimensioning analyses
• Intend to extend this work and methodology to UMTS and HSDPA modeling.
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