COE-541 Research Presentation

Saturation Throughput Analysis for Different Backoff Algorithms in

IEEE802.11

By

Muhamad Khaled Alhamwi

260212

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Outline Introduction Backoff Algorithms Markov Models Analysis

Algorithms Throughput

Simulation Results Conclusions References Q & A

3

Introduction Backoff periods are used to minimize

collision by deferring transmission in CSMA protocols

Different existing backoff algorithms BEB EIED EILD

4

BEB Algorithm (1) Binary Exponential Backoff algorithm:

Transmit using CSMA/CA protocol If transmission was unsuccessful

Double the backoff window Otherwise (successful)

Reset the window to its minimum value

5

BEB Algorithm (2) This aggressive reduction in backoff period

can result in more collisions After successful transmission more stations

will try to transmit Higher probability of collision

6

EIED Algorithm Exponential Increase Exponential Decrease

algorithm

Transmit using CSMA/CA protocol If transmission was unsuccessful

Double the backcoff window Otherwise (successful)

Halve the backoff window

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EILD Algorithm Exponential Increase Linear Decrease

algorithm

Transmit using CSMA/CA protocol If transmission was unsuccessful

Double the backcoff window Otherwise (successful)

Subtract one from the backoff window

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Markov Model of BEB

P is the probability of collision Assumed constant (does not depend on the state)

1-P is the probability of successful transmission Wi (W0 to Wm) is the backoff window size Assuming NO limit on retransmission trials

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Markov Model of EIED (1)

Double when unsuccessful ri = 2 Halve when successful rd = 2

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Markov Model of EIED (2)

Multiply by 4 when unsuccessful ri = 4 Halve when successful rd = 2

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Markov Model of EILD

Double when unsuccessful Subtract one when successful W is the minimum Window size = W0

(20+21+22+… +2m-1)W+1 = 2mW-W+1 states

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Analysis Approach Markov Model Steady-state probabilities Transmission probability Success probability Collision probability Throughput

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BEB Analysis (unlimited retransmission) Steady-state probability

PqP

qq

m

ii

11

1 00

0

m

iiq

0

1

miqPq ii 1for ,. 1

).( 1 mmm qqPq

Solve for q0, we get

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BEB Analysis, cont’ The steady-state probabilities can be expressed by

miP

miPPq

m

i

ifor

0for )1.(

The average number of slots E[Z] spent in each state between transitions, averaged over all states is given by

)21(2

2)2(1

2

121][

1

0 P

WPWPWq

WZE

mm

i

m

i

i

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BEB Analysis, cont’ Since only one slot is used for transmission between state

transitions, the probability of backlogged station to transmit in a random slot is given by

PPPW

WZE m

21))2(1(

)1(

2

][

1

This is the same result obtained by [2] that uses 2-D Markov model

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BEB Analysis (limited ret’)

Markov model for limited retransmission Maximum number of transmissions per packet is

M+1 All states (Wm,i) have the same maximum

deference time of 2mW-1

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BEB Analysis (limited ret’), cont Steady-state probabilities are given by

M

iiii qMiqPq

01 1 ,1 ,.

Solving for q0, we get

MiP

PPq

M

i

i

0 ,

1

)1.(1

)21(21

))2(1()1(

)1(2

2

12

2

121

1

][

1

1

1

1

0

WPP

PPWW

P

qW

qWZE mM

m

M

m

i

M

mii

m

i

i

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EIED Analysis (ri=2, rd=2)

Similarly, steady-state probabilities qi:

m

iiii qmiq

P

Pq

01 1 ,1 ,.

1 Solving for q0, we get

miP

Pr

r

rrq

m

i

i

0 ,

1 ,

1

)1(1

Transmission probability in a random slot

WPPPP

PP

PP

qWZE mmmm

mm

m

ii

i

))2()1(()31()21(

))1((

))1((2

212

1

1

][

1

1111

11

0

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EILD Analysis Steady-state probabilities

iWqPiq

P

WiqP

P

q

ii

i

i

1 ),.).2mod((1

1

11 ,)1(

2

11

0

WW

ii

m

qWiZE 2

0 21

1

1

][

1

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Saturation Throughput Analysis At steady-state, each transmission sees

)1/(1*1 )1(1)())(1(1 nn PPPP τ*(P) is continuous and monotone increasing

function, τ*(0)=0, and τ*(1)=1 For BEB case, τ is given by (monotone

decreasing), τ(0) > τ*(0), and τ(1) < τ*(1)

PPPW

WZE

P m

21))2(1(

)1(

2

][

1)(

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Saturation Throughput Analysis, cont’ Solve for P, obtaining P* and τ*= τ(P*)

]length cycle[

cycle] a during ed transmittPayload[

E

ES

Where ‘cycle’ is the time between two consecutive ends of DIFS/EIFS

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Saturation Throughput Analysis, cont’ Probability of successful transmission in a cycle is a probability

of one station transmitting given that one transmitted in a slot

n

n

s

nP

)1(1

)1)((*

1**

Where n is number of backlogged stations Transmission cycle

Idle (backoff) period following DIFS/EIFS Busy period (one or more transmissions), and

followed by SIFS, ACK, and DIFS in case of success EIFS in case of collision

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Saturation Throughput Analysis, cont’ Idle period length is a product of a geometric

random variable and the slot length

slotnTE

1

)1(1

1]Period Idle[

* Busy Period length for basic mode (ignore

propagation delay

)1(.]PeriodBusy [ sbasCs

bass PTPTE

Different values of Ts, and Tc for RTS/CTS mode

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Saturation Throughput Analysis, cont’

Throughput is given by

]iodPerBusy []Period Idle[

.

X

sX EE

PayloadPS

Where X is either Basic Access Mode RTS/CTS Mode

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Saturation Throughput (Basic Mode)

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Saturation Throughput (RTS/CTS)

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Average Maximum Backoff Window

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Conclusions New Markov chain models were used to analyze

BEB, EIED, EILD algorithms EIED can provide a slight improvement over BEB in

a small network and using basic access mode EILD can provide significant improvement in a large

network The algorithms provide only slight improvement for

RTS/CTS mode

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References [1] Vukovic, I.N.; Smavatkul, N., “Saturation

throughput analysis of different backoff algorithms in IEEE802.11,” Personal, Indoor and Mobile Radio Communications, 2004. PIMRC 2004. 15th IEEE International Symposium on , vol.3, no., pp. 1870-1875 Vol.3, 5-8 Sept. 2004

[2] G. Bianchi, “Performance Analysis of The IEEE802.11 Distributed Coordination Function”, IEEE Journal on Selected Areas in Communications, pp. 535-547, Vol. 18, March 2000.

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Thank you Q & A