1 an analytical model for the dimensioning of a gprs/edge network with a capacity constraint on a...

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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