Transcript Performance Analysis of IEEE 802.11 Distributed

Performance Analysis of IEEE802.11
Distributed Coordination Function (DCF)
Author : Giuseppe Bianchi
Presented by: 李政修
December 23 , 2003
Outline
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Overview of IEEE 802.11 DCF
Mathematical model
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Notations
Bi-dimensional Markov Chain
One step transition probabilities
Stationary distribution
Performance evaluation of DCF
Conclusion and future work
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Overview of IEEE 802.11
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MAC and PHY layers specifications for
wireless LANs
MAC Protocols
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Fundamental: Distributed Coordination
Function (DCF)
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CSMA/CA based
Binary Exponential Backoff rules
Optional: Point Coordination Function (PCF)
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Overview of IEEE 802.11 DCF
Two access techniques
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Basic mechanism: 2 way handshaking
RTS/CTS mechanism: 4 way handshaking
RTS
DATA
CTS
Dest
Source
Source
DATA
DESt
ACK
ACK
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Example of RTS/CTS Access Scheme
CSMA/CA based
CSMA: listen at least DIFS before talk
CA: defer transmission for random back-off time after DIFS
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BO=3 (set)
BO=0
A
DIFS
RTS
SIFS
BO=5 (set)
DATA
CTS
B
BO=8 (set)
BO=5 (suspend)
C
BUSY DIFS
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DIFS
RTS
BO=15 (set)
DIFS
collision
ACK
BO=5(resume)
NAV (RTS)
NAV(CTS)
DIFS
RTS
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BO=10 (set)
DIFS
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Overview of IEEE 802.11 DCF
Backoff procedure—BEB algorithm
CW
Backoff counter:
CWmax
•Initial: uni~[0,CW-1]
•Non zero: decremented for
ccs
each idle slot
•Zero: transmit
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CWmin
C
c
c
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s
cc
c
c
s
t
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Analytical Model to Evaluate DCF
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Saturation throughput:
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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
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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)
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Bi-dimensional Markov Chain model
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Behavior of a single station
Notations
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Time scale:
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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
i
CWi = 2 CWmin
m
m: maximum backoff stage, CWmax = 2 CWmin
p: prob.of each transmitted packet being collided
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B(t0)=(0,3)
SIFS
DIFS
Station A BO=3
Station B
B(t9)=(1,7)
SIFS
RTS
t0 t1 t2 t3
DIFS
BO=4
PACKET
CTS
t8
BO=5
RTS
BO=7
t4 …... t8
ACK
Busy channel
t9
collision
DIFS
Others
BO=7
ACK
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DIFS
BO=4
Busy channel NAV(RTS)
BO=4
RTS
BO=2
RTS
Busy channel NAV(CTS)
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One step transition probabilities (1)
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1) P{i,k|i,k+1}=1, k : [0,Wi-2], i : [0,m]
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At beginning of t
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Backoff counter not reach zero, no transmission
Channel sensed idle for 1 mini-slot till t+1
At beginning of t+1
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Backoff counter decremented by 1
i,k
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i , k+1
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One step transition probabilities (2)
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P{0,k|i,0}=(1-p)/W0, k : [0,W0-1], i : [0,m]
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At beginning of t
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At beginning of t+1
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Backoff counter reaches zero, successful transmitted [t,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]
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At beginning of t
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Backoff counter reaches zero, transmit in [t,t+1], collision
Contention window < CWmax
At beginning of t+1
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contention window doubled
Backoff counter chosen randomly in [0,Wi+1-1]
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State transits upon backoff counter reach
zero (Contention Window <CWmax)
Tx
Success
0,0
0,1
.
.
.
0 , W0-2
0, W0-1
(1-p)/W0
i,0
i+1, 0
…
p/Wi+1
i+1 , 1
...
i+1,Wi+1-2
i+1,Wi+1-1
collision
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One step transition probabilities (3)
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P{m,k|i,0}= p/Wm, k : [0,Wm-1], i = m
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At beginning of t
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Backoff counter reaches zero, transmit in [t,t+1],
collision
Contention Window = CWmax
At beginning of t+1
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Contention Window remains at CWmax
Backoff time counter chosen randomly in [0,Wm-1]
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State transits upon backoff counter reach
zero (Contention Window = CWmax)
0,0
0,1
.
.
.
m,0
…
0 , W0-2
0, W0-1
(1-p)/W0
m,1
…
m , Wm-2
m , Wm-1
p/Wm
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Bi-dimensional Markov Chain model
One step transition diagram
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Results obtained from the model (1)
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Stationary distribution
tao, Probability of a station transmit in a
randomly chosen slot time
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p, Probability of a transmitted packet
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Using numerical techniques to solve tao, p
encounters a collision
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Results obtained from the model (2)
System throughput: as a function of tao
(similar to that derived in class)
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Length of Ts and Tcollision
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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
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More effective for
longer packets
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Performance evaluation of 802.11DCF (2)
Network size vs. throughput
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Basic and RTS/CTS access schemes
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Performance evaluation of 802.11DCF (3)
Probability tao vs. Throughput
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Basic Access
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RTS/CTS
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Performance evaluation of 802.11DCF (4)
CWmin vs. Throughput
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Basic Access
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RTS/CTS
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Performance evaluation of 802.11DCF (5)
CWmax vs. throughput
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(CWmin = 32)
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Performance evaluation of 802.11DCF (6)
Packet length vs. throughput
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Conclusion and future work
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Major contributions of the introduced paper
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Proposed analytical model
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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
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considering the upper limit of retransmission times
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Conclusion and future work
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Extend one hop to multihop
For fixed topology
Find a mathematical solution
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