performance analysis of ieee802.11 distributed coordination function (dcf) author : giuseppe bianchi...

Performance Analysis of IEEE802.11 Distributed Coordination Function (DCF)

Author : Giuseppe Bianchi

Presented by: 李政修December 23 , 2003

March 26, 2003 Math884 project/wqh 2

Outline

Overview of IEEE 802.11 DCF Mathematical model

Notations Bi-dimensional Markov Chain One step transition probabilities Stationary distribution

Performance evaluation of DCF Conclusion and future work


Overview of IEEE 802.11

MAC and PHY layers specifications for wireless LANs

MAC Protocols Fundamental: Distributed Coordination

Function (DCF) CSMA/CA based Binary Exponential Backoff rules

Optional: Point Coordination Function (PCF)


Overview of IEEE 802.11 DCF

Two access techniques Basic mechanism: 2 way handshaking RTS/CTS mechanism: 4 way handshaking

Source Dest

DATA

ACK

SourceDESt

RTS

CTS

DATA

ACK


Example of RTS/CTS Access Scheme

BUSY

RTS

CTS

NAV (RTS)

DATA

ACK

NAV(CTS)

RTS

RTS

SIFS

A

B

C

BO=3 (set)

BO=8 (set)

DIFS

DIFS

DIFS

DIFS

BO=5 (set)

BO=5(resume) BO=5 (suspend)

BO=0

collision

DIFS

DIFS

BO=15 (set)

BO=10 (set)

CSMA/CA based CSMA: listen at least DIFS before talk CA: defer transmission for random back-off time after DIFS


Overview of IEEE 802.11 DCF

Backoff procedure—BEB algorithm

Backoff counter:•Initial: uni~[0,CW-1]

•Non zero: decremented for

each idle slot

•Zero: transmit C c cs

c ccc

ccs

sCWmin

CWmax

CW

t


Analytical Model to Evaluate DCF

Saturation throughput: The limit reached by the system throughput

as the offered load increases, and represents the maximum load that the system can carry in stable conditions

Assumptions Constant & independent collision probability

for each transmitted packet Ideal channel condition (no hidden terminals

and capture) Fixed number of stations operated under

overload (saturation condition)


Bi-dimensional Markov Chain model

Behavior of a single station Notations

Time scale: Discrete and integer, t, beginning of a slot time, when

backoff time counter decrements or regenerated [t, t+1], interval between 2 consecutive slot time, can

be variable length Makovian State: B(t) ={s(t), b(t)} b(t): backoff time counter at time t s(t): backoff stage at time t CWi = 2

iCWmin

m: maximum backoff stage, CWmax = 2mCWmin

p: prob.of each transmitted packet being collided


ACK

RTS

Busy channel NAV(RTS)

PACKET

CTS

RTSStation A

Station B

DIFS

DIFS

BO=3

BO=7

SIFS SIFS

ACK

DIFS

BO=4

DIFS

BO=4

RTS

collision

BO=7

BO=2 RTS

Busy channel

BO=4

BO=5

Others

Busy channel NAV(CTS)

t0 t1 t2 t3 t4 t8…...

B(t0)=(0,3) B(t9)=(1,7)

t8t9


One step transition probabilities (1)

1) P{i,k|i,k+1}=1, k : [0,Wi-2], i : [0,m] At beginning of t

Backoff counter not reach zero, no transmission

Channel sensed idle for 1 mini-slot till t+1 At beginning of t+1

Backoff counter decremented by 1

i , k i , k+11



P{0,k|i,0}=(1-p)/W0, k : [0,W0-1], i : [0,m] At beginning of t

Backoff counter reaches zero, successful transmitted [t,t+1]

At beginning of t+1 Contention window reset to CWmin (backoff stage = 0) Backoff counter chosen randomly in [0,W0-1]

P{i+1,k|i,0}= p/Wi+1, k : [0,Wi+1-1], i : [1,m-1] At beginning of t

Backoff counter reaches zero, transmit in [t,t+1], collision Contention window < CWmax

At beginning of t+1 contention window doubled Backoff counter chosen randomly in [0,Wi+1-1]

March 26, 2003 12

State transits upon backoff counter reach zero (Contention Window <CWmax)

i+1 , 1i+1, 0 i+1,Wi+1-1i+1,Wi+1-2

0 , 0 0 , 1 … 0 , W0-2 0, W0-1

i , 0

.

.

.

. . .

(1-p)/W0

p/Wi+1

TxSuccess

collision



P{m,k|i,0}= p/Wm, k : [0,Wm-1], i = m At beginning of t

Backoff counter reaches zero, transmit in [t,t+1], collision

Contention Window = CWmax At beginning of t+1

Contention Window remains at CWmax Backoff time counter chosen randomly in

[0,Wm-1]


State transits upon backoff counter reach zero (Contention Window = CWmax)

0 , 0 0 , 1 … 0 , W0-2 0, W0-1

.

.

. (1-p)/W0

m , 0m , 1 m , Wm-2 m , Wm-1

p/Wm

…

15

Bi-dimensional Markov Chain model

One step transition diagram


Results obtained from the model (1) Stationary distribution tao, Probability of a station transmit in

a randomly chosen slot time

p, Probability of a transmitted packet encounters a collision

Using numerical techniques to solve tao, p


Results obtained from the model (2)

System throughput: as a function of tao(similar to that derived in class)


Length of Ts and Tcollision


Performance evaluation of 802.11DCF (1)

Parameters Basic Access RTS/CTS

Network size Sensitive Insensitive

Prob.tao Sensitive Insensitive

CWmin Dependent Independent

CWmax Marginal effect

Negligible effect

Packet size More effective for longer packets


Network size vs. throughput

Basic and RTS/CTS access schemes



Probability tao vs. Throughput

Basic Access RTS/CTS



CWmin vs. Throughput

Basic Access RTS/CTS



CWmax vs. throughput (CWmin = 32)



Packet length vs. throughput



Conclusion and future work

Major contributions of the introduced paper Proposed analytical model

Accurate: verified by comparison with simulations Simple Account for all exponential backoff details Evaluate basic and RTS/CTS access schemes

Performance evaluation on saturation throughput What to improve

considering the upper limit of retransmission times


Conclusion and future work

Extend one hop to multihop For fixed topology Find a mathematical solution

performance analysis of ieee802.11 distributed coordination function (dcf) author : giuseppe bianchi...

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