802.11 ampdu and amsdu performance 2007
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Performance Analysis of A-MPDU and A-MSDU
Aggregation in IEEE 802.11n
Boris GinzburgIntel Corporation, Haifa, Israel
Email: [email protected]
Alex KesselmanIntel Corporation, Haifa, Israel
Email: [email protected]
Abstract— With recent improvements in physical layer (PHY)techniques, the achievable capacity for wireless LANs (WLANs)has grown significantly. However, the overhead of IEEE 802.11MAC layer has limited the actual throughput of a WLAN. A-MPDU aggregation suggested in IEEE 802.11n draft is a keyenhancement reducing the protocol timing overheads that enablesaggregation of several MAC-level protocol data units (MPDUs)into a single PHY protocol data unit (PPDU). Another aggrega-tion scheme proposed in IEEE 802.11n is A-MSDU aggregation,which allows several MAC-level service data units (MSDUs) to be
aggregated into a single MPDU. In this work we present a novelanalytic model for estimating the performance of a 802.11n highthroughput wireless link between a station and an Access Point(AP). We consider a 2 × 2 MIMO system and investigate howthe MAC goodput under TCP and UDP traffic is affected by theaggregation size, packet error rate and PHY settings. Our resultsdemonstrate that for UDP traffic, A-MPDU aggregation allowsto achieve a high channel utilization of 95% in the ideal casewhile without aggregation the channel utilization is limited by
just 33%. We also show that A-MPDU aggregation outperformsA-MSDU aggregation, whose performance considerably degradesfor high packet error rates and high PHY rates.
I. INTRODUCTION
With improvements in physical layer (PHY) techniques such
as the orthogonal frequency-division multiplexing (OFDM)modulation technique and multiple-input multiple-output
(MIMO) antenna technology, the achievable capacity for
WLANs has grown significantly. However, the overheads of
media access control (MAC) have limited the actual through-
put. In today’s 802.11 WLANs control frames are transmitted
at a basic rate while the transmission time of physical headers
is fixed. As a result, the 802.11 WLAN efficiency is severely
compromised as the data rate increases since the throughput is
increasingly dominated by these overheads for high data rates.
Therefore, both reducing MAC overheads and pursuing higher
data rates are necessary for high performance WLANs.
In IEEE 802.11e data aggregation is implemented through
controlled frame-bursting (CFB) and the block ACK scheme.Such aggregation schemes benefit from amortizing the control
overhead over multiple data packets. Performance of frame
aggregation schemes is studied in [7], [5]. The works of [2], [8]
derive analytical models of distributed coordination function.
The performance of block ACK schemes is analyzed in [4],
[6], [9]. TCP and UDP performance analysis over a 802.11
WLAN appears in [3], [10].
IEEE 802.11n [1] is a new WLAN standard that provides
both PHY and MAC enhancements to support high data
rates over 100Mbps and up to 600Mbps. The main PHY
technologies of IEEE 802.11n are MIMO and adaptive channel
coding. One key MAC-layer enhancement reducing the pro-
tocol timing overheads is the A-MPDU aggregation scheme,
which enables aggregation of several MAC-level protocol-
data units (MPDUs) into a single PHY-layer protocol data
unit (PPDU). An Aggregated MPDU (A-MPDU) consists of
a number of MPDU delimiters each followed by an MPDU.
Another aggregation scheme proposed in IEEE 802.11n is A-MSDU aggregation, which allows several MAC-level service
data units (MSDUs) to be aggregated into a single MPDU.
In A-MSDU aggregation, multiple payload frames share not
just the same PHY, but also the same MAC header. While A-
MPDU structure can be recovered when one or more MPDU
delimiters are received with errors, an A-MSDU aggregate
fails as a whole even if just one of the enclosed MSDUs
contains bit errors.
Our model. In this work, we focus on the MAC efficiency
improvements in IEEE 802.11n. We present an analytical
framework for estimating the maximum throughput of 802.11n
using A-MPDU and A-MSDU aggregation schemes. To the
best of our knowledge, we are the first to perform analysisthat (i) studies novel A-MPDU and A-MSDU aggregation
techniques, (ii) considers the goodput of MAC not counting
retransmissions and (iii) takes into account collisions of TCP
data packets with TCP ACKs. We consider a 2 × 2 MIMO
system. The maximum throughput is achieved under the best-
case scenario when there is an Access Point (AP) and only
one active station, which always has frames to send. While
aggregation reduces control overhead, the actual benefits de-
pend to a large extent on the channel conditions and MAC
settings. We study how the aggregation size, the packet error
rate and the PHY settings affect the MAC goodput.
Our results. We show that A-MPDU aggregation allows to
achieve a high channel utilization in IEEE 802.11n WLAN. Inparticular, the best-case channel utilization for the mandatory
PHY rate of 130Mbps is 84% under TCP and 95% under UDP
traffic. For the optional PHY rate of 300Mbps, the maximum
channel utilization is slightly worse, that is 78% under TCP
and 91% under UDP traffic. For A-MSDU aggregation, the
corresponding TCP and UDP channel utilization is 51% and
71% for the mandatory PHY rate of 130Mbps and 32% and
53% for the optional PHY rate of 300Mbps. Thus, A-MPDU
aggregation by far outperforms A-MSDU aggregation. We also
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Fig. 1. A-MPDU ideal channel utilization for R= 130Mbps.
Fig. 2. A-MPDU ideal channel utilization for R= 300Mbps.
overheads constitute a larger fraction of the channel access
time for higher PHY rates. Observe that without aggregation,
the channel utilization is limited by 18% and 33% under TCP
and UDP traffic, respectively.
B. A-MSDU Aggregation
1) UDP Traffic: Let T frm be the time required to transmit
an A-MSDU of K data frames and receive an ACK: T frm =T phy+T mac+K (T as+T data)+SIFS +T lphy+T ack. We ob-
tain that the ideal goodput under UDP is IdealUDPGdpt =K∗Ldata
DIFS+T bo+T frm.
2) TCP Traffic: Let T fe be the extra time required to
transmit an A-MSDU of K/2 TCP ACKs: T fe = T phy +
T mac +K(T as+T tcp−ack)
2 + SIFS + T lphy + T ack. As in
the previous section, we approximate the TCP throughput
assuming a constant collision probability of 1/CW min. The
overall time required to transmit an A-MSDU of K data
frames and an A-MSDU of K/2 TCP ACKs is 2(DIFS +T bo) + T frm+ T fe . Therefore, the ideal goodput under TCP is
IdealTCPGdpt = K∗Ldata∗(1−c)2(DIFS+T bo)+T frm+T fe
, where 1/(1− c)is the expected number of retransmission attempts before a
successful transmission.
3) Analysis of Results: The channel utilization as a function
of the aggregation size for the mandatory and optional PHY
rates is presented on Figure 3 and Figure 4, respectively.
Observe that the channel utilization grows almost linearly as K increases. The maximum channel utilization for the mandatory
Fig. 3. A-MSDU ideal channel utilization for R = 130Mbps.
Fig. 4. A-MSDU ideal channel utilization for R = 300Mbps.
PHY rate of 130Mbps is 51% under TCP and 71% under UDP
traffic. For the optional PHY rate of 300Mbps, the maximum
channel utilization is much worse, that is 32% under TCP
and 53% under UDP traffic. Note that the performance of A-
MSDU aggregation degrades significantly for high PHY ratessince MAC overheads are fixed while the time required to
transmit payload decreases.
IV. NOISY CHANNEL ANALYSIS
A. A-MPDU Aggregation
We consider Selective Repeat ARQ retransmission scheme.
1) UDP Traffic: For an A-MPDU, let: X be the average
number of new frames; Y be the average number of retrans-
mitted frames and Z be the average span of sequence numbers.
We assume that the positions of corrupt frames are uniformly
distributed over the sending window. The probability that
exactly i first frames are transmitted successfully is (1− p)i∗ p,
where p is the packet error rate. The expected sending windowshift in this case is i∗Z/(X + Y ). Note that X is the expected
sliding window shift after transmitting an A-MPDU. After
performing some calculations, we get
X ≈
È X+Y −1i=1
(1 − p)i ∗ p ∗ i ∗ Z
X + Y + (1− p)
X+Y Z (1)
=
(X + Y − 1)(1 − p)X+Y +1− (X + Y )(1 − p)X+Y + 1 − p
∗ Z
p(X + Y )
+ (1− p)X+Y
Z,
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Fig. 5. A-MPDU noisy channel utilization under UDP for R = 130Mbps.
Fig. 6. A-MPDU noisy channel utilization under UDP for R = 300Mbps.
where (1− p)X+Y is the probability that all the frames within
the A-MPDU have been transmitted successfully and Z is
the expected window shift in this case. We can approximate
Z as Z ≈ min(K/(1 − p), W ) since the expected number
of retransmissions of an individual frame is 1/(1 − p) andthe sending window size is an upper bound on the sequence
numbers span within an A-MPDU. We can also approximate
the average number of corrupt frames as Y ≈ p(X + Y ),
because Y is also the expected number of retransmissions in
the next A-MPDU. It follows that Y = pX/(1− p).
Now we can numerically find a value of X that best
approximates Equality 1 subject to the constraint that X +Y ≤K . Let T bln be the time required to transmit an A-MPDU
of X + Y data frames and receive a block ACK: T bln =T phy + (X + Y )(T ap + T data) + SIFS + T lphy + T back. We
get that the noisy goodput under UDP is NoisyUDPGdpt =X∗Ldata
DIFS+T bo+T bln.
The UDP channel utilization as a function of the packeterror rate and the aggregation size for the mandatory and
optional PHY rates is presented on Figure 5 and Figure
6, respectively. Note that the channel utilization deteriorates
quickly for low error rates and more slowly for high error
rates. Similarly to the ideal case, the performance of K = 64is only slightly better than that of K = 32.
2) TCP Traffic: Let T ben be the extra time required to
transmit an A-MPDU of X/2 TCP ACKs: T be = T phy +X(T ap+T tcp−ack)
2 + SIFS + T lphy + T back, where X is taken
Fig. 7. A-MPDU noisy channel utilization under TCP for R = 130Mbps.
Fig. 8. A-MPDU noisy channel utilization under TCP for R = 300Mbps.
from Equality 1. In this way, we get that the noisy goodput
under TCP is NoisyTCPGdpt =X∗Ldata∗(1−c)
2(DIFS+T bo)+T bln+T ben,
where c = 1/CW min. The TCP channel utilization as a
function of the packet error rate and the aggregation size for
the mandatory and optional PHY rates can be found on Figure7 and Figure 8, respectively. Observe that TCP performance
degrades faster for high packet error rates compared to that of
UDP.
B. A-MSDU Aggregation
We have that the loss probability for an A-MSDU is pa =1− (1− p)K .
1) UDP Traffic: The probability that the n-th subsequent
transmission of an A-MSDU frame is successful is (1− pa) ∗ pn−1a . The expected number of retransmissions before the first
success is∞
i=1
(1− pa) ∗ pi−1a ∗ i
= 1/(1− pa). We obtain
that the noisy goodput under UDP is NoisyUDPGdpt =K∗Ldata∗(1− pa)DIFS+T bo+T frm
. The UDP channel utilization as a function
of the packet error rate and the aggregation size for the
mandatory and optional PHY rates appears on Figure 9 and
Figure 10, respectively. Remarkably, the channel utilization
of large aggregations degrades faster and eventually becomes
worse than that of smaller aggregations as the packet error
rate increases. That is due to the fact that if just one of the
aggregated frames contains bit errors, the other frames cannot
be recovered.
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Fig. 9. A-MSDU noisy channel utilization under UDP for R = 130Mbps.
Fig. 10. A-MSDU noisy channel utilization under UDP for R = 300Mbps.
2) TCP Traffic: Remember that in our model TCP ACKs
are always transmitted successfully (except collisions). We
have that the noisy goodput under TCP is NoisyTCPGdpt =K∗Ldata∗(1−c)
DIFS+T bo+T frm1−pa
+DIFS+T bo+T fe. The TCP channel utilization
as a function of the packet error rate and the aggregation sizefor the mandatory and optional PHY rates can be found on
Figure 11 and Figure 12, respectively.
V. CONCLUDING REMARKS
In this work we develop an analytical framework to evaluate
the maximum goodput of A-MPDU and A-MSDU aggregation
in IEEE 802.11n high throughput WLAN. We consider a
Fig. 11. A-MSDU noisy channel utilization under TCP for R = 130Mbps.
Fig. 12. A-MSDU noisy channel utilization under TCP for R = 300Mbps.
2 × 2 MIMO system, which is currently being implemented
by the main vendors. The numerical results show that for
UDP traffic, A-MPDU aggregation allows to achieve a high
channel utilization of 95% in the ideal case. At the same time,
the channel utilization without aggregation is limited by 33%.
We also demonstrate that A-MPDU aggregation outperforms
A-MSDU aggregation, whose performance considerably de-
grades for high packet error rates and high PHY rates. Finally,
we investigate how the aggregation size, the packet error rate
and the PHY settings affect the MAC goodput under TCP
and UDP traffic. Our analytic model can be useful for tuning
802.11n aggregation parameters for maximal performance. We
plan to extend our results to multi-hop environments and
perform practical experiments to complement the theoretical
analysis.
Acknowledgements. We are very grateful to Solomon
Trainin and Adrian Stephens for their expert advise on IEEE
802.11n standard.
REFERENCES
[1] IEEE Computer Society, “Wireless LAN Medium Access Control(MAC) and Physical Layer (PHY) specifications: Enhancements forHigher Throughput”, IEEE P802.11n-D2.0, February 2007.
[2] G. Bianchi, ”Performance Analysis of the IEEE 802.11 DCF”, IEEE Journal on Selected Area in Comm., Vol. 18, No. 3, March 2000.
[3] R. Bruno, M. Conti, and E. Gregori, ”Throughput Analysis of UDPand TCP Flows in IEEE 802.11b WLANs: A Simple Model and ItsValidation”, Proceedings of FIRB-Perf’05, pp. 54-63.
[4] R. R. Choudhury, A. Chen, and S. Emeott ”An Analytical View of DataAggregation in IEEE 802.11 LANs”, Technical Report at Motorola
Labs, 2005.[5] S. Kuppa and G. R. Dattatreya, ”Modeling and analysis of frame
aggregation in unsaturated WLANs with Finite buffer stations”, toappear in Proceedings of IEEE ICC’06 , pp. 967-972.
[6] T. Li, Q. Ni, T. Turletti, and Y. Xiao. ”Performance Analysis of the
IEEE 802.11e Block ACK Scheme in a Noisy Channel”, Proceedingsof IEEE BroadNets 2005.
[7] C. Liu and A.P. Stephens, ”An analytic model for infrastructure WLANcapacity with bidirectional frame aggregation”, Proceedings of IEEE WCNC’05, pp. 113-119..
[8] Y.C. Tay and K.C. Chua, ”A Capacity Analysis for the IEEE 802.11MAC Protocol”, Wireless Networks, Vol. 7, pp. 159-171, 2001.
[9] I. Tinnirello and S. Choi, ”Efficiency Analysis of Burst Transmissionswith Block ACK in Contention-Based 802.11e WLANs”, Proceedingsof IEEE ICC’05, pp. 3455-3460.
[10] A. De Vendictis, F. Vacirca and A. Baiocchi, ”Experimental Analysisof TCP and UDP Traffic Performance over Infra-structured 802.11bWLANs”, Proceedings of the European Wireless 2005.