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An Evaluation of Quality of Service for H.264 over
802.11e WLANs
Richard MacKenzie∗, David Hands† and Timothy O’Farrell‡
∗School of Electronic & Electrical Engineering, University of Leeds, Leeds, UK†BT Innovate, British Telecommuncations PLC, Adastral Park, Ipswich, UK
‡Institute of Advanced Telecommuncations, Swansea University, Swansea, UK
Email: [email protected], [email protected], [email protected]
Abstract—802.11 wireless local area networks are now acommon feature in the home. In order to meet the quality of service (QoS) demands for the increasing number of multimediaapplications on these home networks the 802.11e amendmentwas developed. A suitable video coding standard for thesemultimedia applications is H.264 due to its high compressionand error resilience. In this paper we investigate how the qualityof H.264 video is affected as the number of concurrent videostreams sent over a multi-rate 802.11e network is increased.
Several packet mapping schemes are compared. We show thatthe mapping schemes which differentiate video packets based ontheir frame type are more successful at maintaining acceptablevideo quality when congestion occurs, providing a more gradualquality degradation as congestion increases rather than the cliff-edge quality drop that tends to occur with the other mappingschemes. These differentiated schemes are more successful forvideos that do not have a high amount of temporal activity. Wealso identify that impairments caused by congestion tend to occurtowards the bottom of each frame when the flexible macroblockordering (FMO) feature of H.264 is not used but the use of FMOcan reduce this effect.
I. INTRODUCTION
A common feature in the modern home is an 802.11
[1] wireless local area network (WLAN) with an internet
connection. The increase in 802.11 physical layer data rates
along with the availability and affordability of high speed
internet connections has led to an increase in the number of
multimedia internet applications used in the home. There are
a wide range of video applications now available including
low resolution video such as Youtube, video conferencing,
and standard definition and high definition internet protocol
television (IPTV). The home network typically consists of
many devices which may be requesting different services at
the same time. Each service may have its own quality of
service (QoS) requirements. The 802.11e amendment to theoriginal standard was developed to meet the need to be able
to provide QoS over 802.11 networks. Enhanced distributed
channel access (EDCA) allows for service differentiation by
having four parallel queues which can each have different
priorities to access the wireless channel.
This work is funded as an industrial case scholarship agreement betweenBritish Telecommunications PLC (BT) and the Engineering and PhysicalSciences Research Council (EPSRC) under BT/EPSRC case studentshipagreement CT1080038286
The H.264 video coding standard [2] was developed by the
Joint Video Team (JVT) which was formed by a partnership
between the ITU-T Video Coding Experts Group (VCEG)
and the Moving Pictures Experts Group (MPEG). This coding
standard is appropriate for internet video applications due to
its high coding efficiency and is designed to be “network
friendly” for applications which include video telephony, TV
broadcasting and internet streaming [3].Different packets in a video stream can be of varying
importance to the decoding process, so prioritising the more
important packets can help to maintain a better quality received
video. Over an 802.11e network simply mapping packets into
the appropriate EDCA queues can have a significant effect
on the QoS of video applications. There is a great deal of
work related to providing video QoS using EDCA. In [4],
[5] and [6] a variety of traffic mapping schemes have been
investigated. Each scheme prioritises packets based on their
slice type, slice group or partition type depending on how the
video has been encoded. The priority assigned to each packet
determines which EDCA queue each packet is mapped into.
In all of these works the video is of CIF resolution (352x288)and is encoded at bitrates typically well below 1Mb/s. IPTV
services are usually of standard definition television (SDTV)
or high definition television (HDTV) resolutions with bitrates
ranging upwards from 1.5Mb/s. This is reflected in some of
the more recent works focused on IPTV in the home such as
[7], [8], [9] and [10].
In this paper we investigate how many concurrent SDTV
streams can be maintained with acceptable QoS. Several
packet mapping schemes are tested and compared to see which
perform the best. Tests are performed over a range of physical
layer rates to show how each scheme would cope with a
sudden change in the physical layer rate. We identify that
losses tend to occur towards the bottom of each frame if theflexible macroblock ordering (FMO) feature of H.264 is not
used and have results to show that FMO can reduce this effect.
This work on FMO extends the work in [9] by testing a greater
range of both traffic mapping schemes and FMO patterns to
see which can offer the best performance. Peak signal-to-
noise ratio (PSNR) has been a common way to judge video
quality as in [4], [5], [6] and [7]. PSNR is, however, a poor
indicator of perceptual quality [11]. In [8] the video quality
estimation tool described in Annex D of the J.144 standard for
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objective perceptual video quality measurement techniques has
been used [12]. We are using the tool described in Annex A
of the same standard. Within the standard these models are
not validated for error impairments such as dropped packets.
Also the various mapping schemes used in our tests produce
different types of video impairments. In [10] subjective quality
values have been collected for the same mapping schemes used
in this paper. The correlation between those subjective scores
and the objective quality scores acquired using the Annex A
model is 0.91.
We have mainly focussed on sending synchronised videos
over EDCA because this is the most challenging scenario when
trying to provide QoS while sending multiple videos over
EDCA. We do, however, show how the system performance
changes when the videos are not synchronised and show that
the overall QoS of the system is not significantly changed.
The rest of this paper is organised as follows. An overview
of the EDCA protocol and the H.264 standard are provided in
sections II and III. Section IV describes the packet mapping
schemes that we will be comparing. The testing procedure
follows in section V. Test results are shown in section VIfollowed by a summary in section VII.
II. EDCA PROTOCOL
The distributed coordination function (DCF), as defined
in the 802.11 standard, provides contention based channel
access using carrier sense multiple access with collision avoid-
ance (CSMA/CA). The 802.11e amendment was developed
to meet the need to be able to provide quality of service
(QoS) over 802.11 WLANs. This amendment specifies the
enhanced distributed channel access (EDCA) function which
provides differentiated, contention-based channel access for
eight user priorities (UPs). Each UP is mapped into one of
four access categories (ACs). Within the 802.11 standard thedescription of the traffic intended for each of the four ACs
are voice, video, best effort and background. These ACs are
named AC VO, AC VI, AC BE and AC BK respectively.
Each AC has its own queue which contends for the channel
using its own EDCA function. Each EDCA function uses its
own set of EDCA parameters which includes an arbitration
interframe space (AIFS[AC]), a minimum and a maximum
contention window value (CWmin[AC] and CWmax[AC]) and
a transmission opportunity (TXOP) limit (TXOP limit[AC]).
AIFS[AC], CWmin[AC] and CWmax[AC] are used in the same
way as the distributed interframe space (DIFS) and the mini-
mum and a maximum contention window values (CWmin and
CWmax) are used by the DCF. The TXOP limit[AC] specifiesthe maximum duration of an EDCA function’s TXOP. If
TXOP limit[AC] = 0 then that EDCA function can only
attempt one frame exchange each time it contends for the
channel. If, however, TXOP limit[AC] > 0 then once that
EDCA function has successfully contended for the channel
it can attempt multiple frame exchanges, separated by short
interframe spaces, without having to contend for the channel
again so long as the total duration of the TXOP does not
exceed the TXOP limit[AC].
III. H.264 STANDARD
The H.264 standard can be described as two distinct layers:
The video coding layer (VCL) and the network abstraction
layer (NAL). The VCL deals with the block based compression
of video samples while the NAL puts the coded video data into
a suitable and flexible form for mapping onto various transport
mechanisms.
The VCL provides efficient compression of the video. Eachframe within the video consists of one or more slices and each
slice can be independently decoded provided that all required
reference frames are available. Each slice will typically consist
of consecutive macroblocks in raster scan order. In this case
the loss of a slice can therefore result in the loss of all coded
information for the entire area of the frame that the lost slice
covered. Error concealment for this area can be very difficult
as all coded information within this area has been lost. Flexible
macroblock ordering (FMO) is an error resilience feature of
H.264 which can help improve the situation of a missing
slice. Each macroblock is assigned to a slice group. Each
slice then contains consecutive macroblocks from within the
same slice group. The pattern of the slice group is defined
by the slice group map. One common slice group map type
is interleaved. The value for run length defines how many
consecutive macroblocks are assigned to each slice group
before switching to the next slice group. Another common
slice group map type is the dispersed map type. Here the
slice groups are scattered. For example with two dispersed
slice groups the slice group map has the appearance of a
checkerboard. If a slice is lost when FMO is being used the
missing macroblocks are more likely to have neighbouring
macroblocks, from other correctly received slice(s), available
which can provide more local information to help improve
error concealment.Frames used for reference are generally considered to be
more important than non-reference frames. If a reference frame
contains errors then these errors can propagate into other
frames that reference it. For this work all frames formed by
B-slices are considered non-reference while frames formed by
either I-slices or P-slices can be used for reference. I-frames
(frames formed by I-slices) are considered the most important
as they make no reference to other frames and are used as
references for the successful decoding of any associated P-
frames or B-frames. In contrast to the relative importance of
frame types, B-frames tend to offer the highest compression
while I-frames tend to offer the lowest compression. This
results in the larger encoded frames tending to be the mostimportant.
Parameter sets, which are created separately from slice
information, contain syntax elements that can apply to the
decoding of many frames. A slice refers to the parameter set
that it uses in its slice header. Therefore the parameter set
information (PSI) must have arrived at the decoder before any
slices that require it. As PSI is required to correctly decode
slice data it should be considered extremely important.
A NAL unit (NALU) consists of a 1B header plus a payload
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0
0.1
0.2
0.3
0.4
0.5
0.6
2 4 6 8 10 12
Best Effort
Scheme 1
Scheme 2
Scheme 3
Video Load (Mb/s)
P L R
(a) All slices PLR
0
0.2
0.4
0.6
0.8
1
2 4 6 8 10 12
Best Effort
Scheme 1
Scheme 2
Scheme 3
Video Load (Mb/s)
P L R
(b) I-slice PLR
0
0.2
0.4
0.6
0.8
2 4 6 8 10 12
Best Effort
Scheme 1
Scheme 2
Scheme 3
Video Load (Mb/s)
P L R
(c) P-slice PLR
0
0.2
0.4
0.6
0.8
1
2 4 6 8 10 12
Best Effort
Scheme 1Scheme 2
Scheme 3
Video Load (Mb/s)
P L R
(d) B-slice PLR
Fig. 1: Mean PLR for each mapping scheme
average PLR for I-slices and P-slices only are shown in Fig.
1b and Fig. 1c respectively. Here we find that the default
scheme always has the highest PLR for both I-slices and P-slices, followed by mapping scheme 1. Mapping scheme 2
shows a total protection of I-slices even at the total video load
of 12Mb/s. Mapping scheme 3 has a high protection of I-
slices, although not as high as scheme 2. Scheme 3 does on
the other hand offer a higher protection of P-slices than scheme
2. Fig. 1d shows the average PLR for B-slices only. The
non-differentiated mapping schemes show a relatively good
protection of B-slices compared to how they protect I-slices
and P-slices. The differentiated mapping schemes both show
(a) No packet losses (b) Best Effort
(c) Scheme 1 (d) Scheme 2/3
Fig. 2: Comparison of video streaming schemes with 2Mb/s
‘Fries’ video sequence using different mapping schemes
the same behaviour in their protection of B-slices. For the
differentiated mapping schemes, while the access point is not
congested all B-slices are totally protected but as soon as the
access point becomes congested almost every B-slice is lost.
This results in most B-frames being a frame repeat which
effectively means that during congestion there is a drop in the
frame rate of the video when the differentiated schemes are
used. These PLR results do show that although scheme 1 offers
the lowest PLR overall, the non-differentiated schemes offer
poorer protection to more important slices. The differentiated
schemes however sacrifice the less important B-slices during
congestion in order to maintain a higher protection for themore important I-slices and P-slices.
As shown by the PLR results each mapping scheme offers
different levels of protection for each slice type. This leads to
different characteristics in the decoded video. Fig. 2 compares
the same frame from the ‘Fries’ video sequence encoded at
2Mb/s, for the various mapping schemes. Fig. 2a shows the
decoded sequence when there are no packet losses. Fig. 2b,
Fig. 2c and Fig. 2d show sequences that suffer losses when
the total video load is 8Mb/s for the default scheme, scheme 1
and the differentiated schemes respectively. The differentiated
schemes both output identical frames in this scenario: Both
have perfectly reconstructed I-frames and P-frames, while all
B-slices have been lost resulting in all B-frames being framelosses thus effecting a form of temporal scaling. Therefore the
frame in Fig. 2d, which was a B-frame, shows no noticeable
impairments but is actually a repeat of an earlier frame. Both
non-differentiated schemes do show noticeable impairments.
These impairments tend to be focused towards the bottom of
the frame. The reason is that no flexible macroblock ordering
(FMO) has been used so the macroblocks from each frame are
encoded in raster scan order. The encoded slices are therefore
produced and sent in scan order with each frame transmission
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1
2
3
4
5
1 2 3 4 5 6
Best Eff ort Sche me 1
S che me 2 S che me 3
Number of Streams
p M O S
(a) 2Mb/s sequences
1
2
3
4
5
1 2 3
Best Ef fo rt Sche me 1
S che me 2 S che me 3
Number of Streams
p M O S
(b) 4Mb/s sequences
Fig. 3: Video quality results for ‘Fries’ video sequence
1
2
3
4
5
1 2 3 4 5 6
Best Ef fo rt Sche me 1
S che me 2 S che me 3
Number of Streams
p M O S
(a) 2Mb/s sequences
1
2
3
4
5
1 2 3
B es t E ff ort S che me 1S che me 2 S chem e 3
Number of Streams
p M O S
(b) 4Mb/s sequences
Fig. 4: Video quality results for ‘Mobile & Calendar’ video
sequence
resulting in a burst of packets. Packets towards the end of eachburst are more susceptible to losses due to queue overflow or
exceeding the delay bound. This results in more slice losses
towards the bottom of each frame. This effect is more severe
for larger frames which tend to be the reference frames and
as a result the lossy decoded sequences tend to show lots of
impairments towards the bottom of the screen when FMO
is not used. This effect appears as soon as congestion is
experienced when videos are sent with a non-differentiated
mapping scheme while the differentiated schemes avoid this
effect when congestion is first experienced by causing B-slices
to be lost in order to maintain the integrity of the reference
frames.
The video quality scores for the ‘Fries’, ‘Mobile & Cal-endar’ and ‘Rugby’ sequences are shown in Fig. 3, Fig. 4
and Fig. 5. For the 2Mb/s sequences the schemes 1, 2 and
3 all maintain the quality of the original encoded sequences
until the number of concurrent video streams exceeds 3. The
default scheme however shows a slight drop in quality for the
2Mb/s ‘Mobile & Calendar’ sequence when there are just 3
streamed videos. The reason is a combination of the fact that
the default scheme has the lowest channel capacity due to the
EDCA parameter settings along with characteristics of this
1
2
3
4
5
1 2 3 4 5 6
Best Eff ort Sch eme 1
S che me 2 S che me 3
Number of Streams
p M O S
(a) 2Mb/s sequences
1
2
3
4
5
1 2 3
B es t E ff or t S che me 1
S chem e 2 S chem e 3
Number of Streams
p M O S
(b) 4Mb/s sequences
Fig. 5: Video quality results for ‘Rugby’ video sequence
particular sequence. This sequence has relatively high spatial
content with relatively low temporal content compared to the
other sequences. As can be seen from Table II this results in
relatively large I-frames and small B-frames. These larger I-
frames therefore result in larger bursts of packets which aremore prone to losses.
In general both of the non-differentiated mapping schemes
show a cliff-edge drop in quality as soon as congestion is
experienced. This means that as soon as the video load is
high enough to cause congestion the video quality drops
to below 2 on the ACR scale. The differentiated schemes
show better quality performance than the non-differentiated
schemes. For the ‘Fries’ and ‘Mobile & Calendar’ sequences
the differentiated schemes avoid this cliff-edge drop in qual-
ity providing a more gradual degradation in quality. The
differentiated schemes are less effective in producing this
gradual degradation in quality for the ‘Rugby’ video sequence.
This again is due to the video characteristics. The reductionin frame rate caused by the differentiated schemes during
congestion is more noticeable and therefore less acceptable
for high motion content.
This next set of tests looks to solve the issue identified
earlier where impairments tend to appear towards the bottom
of the frame during congestion. The reason that errors tended
to occur towards the bottom of each frame is that flexible
macroblock ordering (FMO) was not used so macroblocks
were encoded in, and the resulting coded slices sent in, raster
scan order. Each sent frame results in a burst of packets where
packets towards the end of the burst are more susceptible to
losses. This effect is more severe for the non-differentiated
schemes which do not protect the packet bursts caused byreference frames as well as the differentiated schemes. We
now test to see if the use of FMO can reduce this effect.
Video encoded without using FMO is now compared to video
encoded using one of three different FMO slice group map
patterns as described in Table V. The run length for the two
interleaved slice group maps is equal to one frame width,
resulting in interleaved rows. The encoder used only applies
FMO to P-frames.
Fig. 6 compares the same frame from the ‘Fries’ video
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TABLE V: FMO patterns
Number of Slice group Run length
slice groups map type macroblocks frame width
1 (no FMO) N/A N/A N/A
2 interleaved 45 1
3 interleaved 45 1
4 dispersed N/A N/A
(a) no FMO (b) 2 interleaved slice groups
(c) 3 interleaved slice groups (d) 4 dispersed slice groups
Fig. 6: Comparison of 2Mb/s ‘Fries’ video sequence using
different FMO patterns with mapping scheme 1
sequence encoded at 2Mb/s. The total video offered load is
8Mb/s and mapping scheme 1 has been used. The use of
FMO is successful at preventing impairments from being asconcentrated towards the bottom of the frame. This is done
by spreading lost slice information throughout the screen. By
doing this missing macroblocks are more likely to have some
correctly received neighbouring macroblocks. The decoder
should therefore have more local information for a better
chance of successfully concealing errors in the event of losses.
Fig. 7 shows the video quality for each FMO pattern. These
values are averaged over all 3 video sequences when sent
using mapping scheme 1. When the video load is too low
to cause congestion the sequences encoded with FMO show
a lower quality value than when FMO is not used. This
is due to the lower encoding efficiency experienced when
using FMO [16]. This reduction in quality is, however, notvery significant. When congestion does occur we see that the
quality is very similar whether FMO is used or not, regardless
of which of the tested FMO patterns are used. Although results
are only shown here using mapping scheme 1, this was the
observation for all of our mapping schemes. It is important
to note however that while we find no significant benefit or
loss from using FMO, these results are decoder dependent.
The decoder used for all our tests is designed to be extremely
robust. It uses a fast error concealment method which uses
noFMO FMO - 2interleavedslicegroups
FMO - 3interleavedslicegroups FMO - dispersed
noFMO FMO - 2interleavedslicegroups
FMO - 3interleavedslicegroups FMO - dispersed
1
2
3
4
5
1 2 3 4 5 6
Number of Streams
p M O S
(a) 2Mb/s sequences
1
2
3
4
5
1 2 3
Number of Streams
p M O S
(b) 4Mb/s sequences
Fig. 7: Average pMOS for multiple video streams using
different FMO patterns with packet mapping scheme 1
temporal information whenever possible before reverting to
spatial information. Fig. 6 shows that FMO does succeed in
spreading out errors throughout the screen. This spreading of
errors should mean that each lost macroblock is likely to havemore local information available to help its error concealment.
During congestion this should allow for a decoder with more
advanced error concealment techniques to produce a higher
quality output for a video sequence encoded with FMO than
for a sequence encoded without FMO.
So far, our results have focused on sending synchronised
videos over EDCA. We now see how system performance
varies when the videos are not synchronised and the video
content in each individual test is mixed. We only provide
results in this section for scheme 1 and scheme 3 to represent
the non-differentiated and differentiated schemes respectively.
PLR results are compared between synchronised and non-
synchronised video tests in Fig. 8. While the overall sys-tem PLR remains similar for both synchronised and non-
synchronised video tests, the average PLR per slice type can
be quite different. Fig. 8a shows the PLR per slice type
when mapping scheme 1 has been used. The synchronised
videos receive better protection for B-slices at the expense of
poorer protection to the more important I and P slices when
compared to non-synchronised videos. This demonstrates why
synchronised video tests allow us to test a worst case scenario.
As, already explained, a large frame results in a large burst
of packets which will be more suseptible to losses than a
smaller burst. When there are several synchronised videos
a large frame results in several synchronised large bursts
of packets meaning that large frames have an even higherlikelihood of suffering losses. Fig. 8b shows the PLR per
slice type when using mapping scheme 3. Here there is very
little difference in how the synchronised and non-synchronised
video frames are treated. This shows that a further advantage
of the differentiated mapping schemes is that the treatment
of video packets are less affected by the relative timings of
videos than the differentiated mapping schemes.
Fig. 9 shows the video quality results for the 4Mb/s ‘Fries’
video sequences from the non-synchronised video tests. Fig.
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NON-SYNCI-SLICES NON-SYNCP-SLICES NON-SYNCB-SLICES
S YNCI-S LI CE S S YNC P-S LI CES S YNC B-S LI CES
NON-SYNCI-SLICES NON-SYNCP-SLICES NON-SYNCB-SLICES
S YNCI-S LI CE S S YNC P-S LI CES S YNC B-S LI CES
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3Number of 4Mb/s Streams
P L R
(a) Scheme 1
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3Number of 4Mb/s Streams
P L R
(b) Scheme 3
Fig. 8: PLR per slice type for multiple 4Mb/s videos. Synchro-
nised (SYNC) videos compared with non-synchronised (NON-
SYNC) videos
9a shows results when using mapping scheme 1 while Fig. 9b
shows results when using mapping scheme 3. When compared
to the average pMOS values for the synchronised tests inFig. 3b we see that when the videos are not synchronised
the average pMOS is greatly improved for scheme 1 but for
scheme 3 there is no significant improvement. For each test
scenario in Fig. 9 we have shown the mean pMOS along with
the minimum and maximum received pMOS values because
there is a large range of pMOS values experienced from
each test scenario. The reason being that the relative timings
between videos within the same test can affect how well each
video is treated. With the synchronised video tests all sent
videos in a particular test receive very similar treatment so
the mean pMOS value is a good measure for the QoS of the
system. If there is a great variation in the quality of the videos
sent in a particular test, the overall system performance islikely to be judged more by the pMOS of the poorest quality
received video than the average pMOS of all of the videos
in the system. If we compare the minimum pMOS values for
the non-synchronised tests with the average pMOS values for
the synchronised tests we see that the system performance is
very similar. Another noticeable advantage of the differentiated
schemes over the non-differentiated schemes is that during
non-synchronised video scenarios the videos receive more
even treatment when congestion is first experienced. The
tests with synchronised videos show the same loss patterns
as the non-synchronised videos where the errors tend to be
concentrated towards the bottom of the screen when FMO has
not been used.We have already shown, with the results from our earlier
tests, that sending videos through an 802.11e access point
using the differentiated mapping schemes can allow for a more
gradual quality degradation during congestion than using the
non-differentiated schemes. Those tests effected congestion by
increasing the number of concurrent video streams sent over
a single rate physical layer (PHY). Over a wireless network a
common cause of increased congestion can be a reduction in
channel capacity due to PHY rate switching. The following
1
2
3
4
5
1 2 3
MEAN MAX MIN
Number of 4Mb/s Streams
p M O S
(a) Scheme 1
1
2
3
4
5
1 2 3
MEAN MAX MIN
Number of 4Mb/s Streams
p M O S
(b) Scheme 3
Fig. 9: Video quality for 4Mb/s ‘Fries’ video sequences during
tests with non-synchronised videos
tests compare the same four mapping schemes as earlier,
as described in Table I, for different ERP-OFDM physical
layer rates which can range from 6Mb/s up to 54 Mb/s.
In a home network it is quite possible that there could be
as many as 6 linear TV connections attempted concurrently,
so we have tested for 1 up to 6 concurrent (synchronised)
video streams for each combination of mapping scheme and
PHY rate. Fig. 10 shows the video quality for 1 up to 6
concurrent 2Mb/s sequences. One subfigure is provided for
each of the four mapping schemes. The quality values (pMOS)
are averaged over the quality scores for the ‘Fries’, ‘Mobile
& Calendar’ and ‘Rugby’ sequences. The physical layer rates
tested range from 6Mb/s up to 18Mb/s. From 18Mb/s upwards
all four mapping schemes can send at least 6 concurrent 2Mb/s
videos over the network successfully without them suffering
a reduction in quality.
Fig. 11 shows the video quality for 1 up to 6 concurrent
4Mb/s sequences. Again, one subfigure is provided for each of the four mapping schemes and the quality values are averages
for the quality scores of the ‘Fries’, ‘Mobile & Calendar’ and
‘Rugby’ sequences. The physical layer rates tested range from
6Mb/s up to 54Mb/s. In order to successfully send at least 6
concurrent 4Mb/s videos over the network without suffering
any loss in video quality the physical layer rate must be at least
48Mb/s for the default mapping scheme but only 36Mb/s for
the other three mapping schemes.
When comparing the results for the multiple 2Mb/s and
4Mb/s sequences there are many similar characteristics: The
default best effort scheme, which has the lowest capacity,
shows poorer performance than the other three mapping
schemes. For each physical layer rate, the differentiated map-ping schemes do show a more gradual degradation in quality
than the non-differentiated schemes. Scheme 1 has the highest
channel capacity as it is the only scheme that does not map
any video data into the slow AC BE queue. This can allow the
maximum video quality to be maintained for a slightly higher
load than the differentiated schemes. This effect can, however,
only be seen with the 9Mb/s physical layer rate results.
In general the differentiated schemes tend to show the
best performance and also allow for a more gradual quality
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1
2
3
4
5
1 2 3 4 5 6
Number of 2Mb/s Streams
p M O S
(a) Best Effort
1
2
3
4
5
1 2 3 4 5 6
Number of 2Mb/s Streams
p M O S
(b) Scheme 1
1
2
3
4
5
1 2 3 4 5 6
Number of 2Mb/s Streams
p M O S
(c) Scheme 2
1
2
3
4
5
1 2 3 4 5 6
Number of 2Mb/s Streams
p M O S
(d) Scheme 3
18Mb/s6Mb/s 9Mb/s 12Mb/s 18Mb/s6Mb/s 9Mb/s 12Mb/s
Fig. 10: Average pMOS for multiple 2Mb/s streams sent using different physical layer datarates
1
2
3
4
5
1 2 3 4 5 6
Number of 4Mb/s Streams
p M O S
(a) Best Effort
1
2
3
4
5
1 2 3 4 5 6
Number of 4Mb/s Streams
p M O S
(b) Scheme 1
1
2
3
4
5
1 2 3 4 5 6
Number of 4Mb/s Streams
p M O S
(c) Scheme 2
1
2
3
4
5
1 2 3 4 5 6
Number of 4Mb/s Streams
p M O S
(d) Scheme 3
54Mb/s
6Mb/s 9Mb/s 12Mb/s 18Mb/s
24Mb/s 36Mb/s 48Mb/s 54Mb/s
6Mb/s 9Mb/s 12Mb/s 18Mb/s
24Mb/s 36Mb/s 48Mb/s
Fig. 11: Average pMOS for multiple 4Mb/s streams sent using different physical layer datarates
degradation than either of the non-differentiated schemes. This
gradual quality degradation can be a great benefit if there
is a sudden drop in the physical layer rate. For example
if we are streaming five 4Mb/s videos through an access
point with a physical layer rate of 36Mb/s then all mapping
schemes work successfully and maintain the maximum video
quality. If the physical layer rate drops to 24Mb/s all mapping
schemes suddenly suffer a drop in video quality. For the
default best effort scheme the quality instantly drops to below
2 on the ACR scale, the quality using scheme 1 is around
2.5, while the differentiated schemes only drop as low as
around 3.5. A further drop in physical layer rate to 18Mb/s
sees the quality using scheme 1 fall well below 2, while the
differentiated schemes are still able to stay above 2. It is this
ability to maintain a better quality during a sudden increase
in congestion that highlights the benefit of these differentiated
mapping schemes.
Both differentiated mapping schemes show similar perfor-
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mance with scheme 2 being the best. A real time video service
is almost certain to have an accompanying audio stream.
Audio streams are typically very low data rates relative to
the video stream. The recommended EDCA parameter sets
were designed with the intention that real time audio streams
are mapped into AC VO so that they do not have to compete
with the higher rate video streams which should be mapped
into AC VI. However, scheme 2 already maps I-slices into
AC VO. This means that scheme 2 should experience a drop
in audio quality well before scheme 3. While both schemes
map PSI into AC VO this low amount of data will have little
effect on audio streams. The overall quality of service for an
audiovisual service is a combined effect of both the quality
of the received video and the received audio [17]. So in order
to maintain a robust video streaming service while trying to
avoid the loss of audio information, which should be mapped
onto AC VO, we would recommend the use of traffic mapping
scheme 3.
VII. SUMMARY
In this paper we have compared streaming multiple con-
current H.264 streams through an 802.11e access point for
several traffic mapping schemes. We have shown that all
mapping schemes used provide better performance than the
default best effort service. The best performing mapping
schemes differentiate packets based on their slice type and
allow a more gradual drop in video quality as congestion is
increased, avoiding the much steeper decline in quality that
occurs with the other schemes. We have also shown how
these differentiated schemes can offer a benefit over the non-
differentiated schemes during a drop in physical layer rate.These differentiated schemes are less effective, although still
better performing than the non-differentiated schemes, when
the video content has a high amount of temporal activity.
We have shown the difference between sending multiple
synchronised videos with multiple non-synchronised videos.
We have shown that while sending synchronised videos is
a worst case scenario in terms of the average perceptual
quality of a received video, the overall system QoS is not
significantly changed. We have also identified that without
the use of FMO impairments caused by congestion tend be
concentrated towards the bottom of the frame. By distributing
errors, which are often severe, across the frame by the use of
FMO the video quality remains similar for an H.264 decoderthat does not have sophisticated error concealment techniques.
Further investigation is needed to confirm whether or not this
spreading of severe loss errors across the frame will in fact
allow a decoder with advanced error concealment techniques
to conceal errors more effectively than if FMO is not used.
This does however highlight the benefit of the differentiated
mapping schemes which are a simple and effective way to
improve the robustness of video streams on a congested
network without the need for a sophisticated decoder.
REFERENCES
[1] IEEE Part 11: Wireless LAN Medium Access Control (MAC) and
Physical Layer (PHY) Specifications, Std. 802.11-2007 (Revision of IEEE Std 802.11-1999), 2007.
[2] ITU-T Recommendation H.264: Advanced video coding for generic
audiovisual services, ITU-T Std. H.264, 2007.[3] T. Wiegand, G. Sullivan, G. Bjontegaard, and A. L uthra, “Overview of
the H.264/AVC video coding standard,” Circuits and Systems for VideoTechnology, IEEE Transactions on, vol. 13, no. 7, pp. 560–576, July
2003.[4] A. Ksentini, A. Gueroui, and M. Naimi, “Improving H.264 videotransmission in 802.11e EDCA,” in IEEE ICCCN 2005., Oct. 2005,pp. 381–386.
[5] U. I. Choudhry and J. Kim, “Performance evaluation of H.264 mappingstrategies over IEEE 802.11e WLAN for robust video streaming,”
Lecture Notes in Computer Science, vol. 3768, pp. 818–829, 2005.[6] N. Cranley and M. Davis, “Video frame differentiation for streamed
multimedia over heavily loaded IEEE 802.11e WLAN using TXOP,” in IEEE PIMRC 2007 , Sept. 2007, pp. 1–5.
[7] E. Shihab, L. Cai, F. Wan, A. Gulliver, and N. Tin, “Wireless meshnetworks for in-home IPTV distribution,” Network, IEEE , vol. 22, no. 1,pp. 52–57, Jan.-Feb. 2008.
[8] K.-H. Lee, S. T. Trong, B.-G. Lee, and Y.-T. Kim, “QoS-guaranteedIPTV service provisioning in home network with IEEE 802.11e wirelessLAN,” in Network Operations and Management Symposium Workshops,2008. NOMS Workshops 2008. IEEE , April 2008, pp. 71–76.
[9] R. MacKenzie, D. Hands, and T. O’Farrell, “Effectiveness of H.264error resilience techniques in 802.11e WLANs,” in IEEE WCNC 2009,Budapest, Hungary, April 2009.
[10] ——, “QoS of video delivered over 802.11e WLANs,” in IEEE ICC
2009, Dresden, Germany, June 2009.[11] Objective and Subjective Measures of MPEG Video Quality, ANSI T1A1
Contribution Number T1A1.5/96-121, 1997.[12] ITU-T Recommendation J.144: Objective Perceptual Video Quality Mea-
surement Techniques for Digital Cable Television in the Presence of aFull Reference, ITU-T Std. J.144, 2004.
[13] W.-S. H. A. Z. Chih-Heng Ke, Ce-Kuen Shieh, “An evaluation frame-work for more realistic simulations of MPEG video transmission,”
Journal of Information Science and Engineering.[14] T. S.-M. W. D. S. S. Wenger, M. M. Hannuksela, “RTP payload format
for H.264 video,” Internet proposed standard RFC 3984, Feb. 2005.[15] ITU-R Recommendation BT.500-11: Methodology for the subjective
assessment of the quality of television pictures, ITU-R Std. BT500-11,
2002.[16] S. Wenger, “H.264/AVC over IP,” Circuits and Systems for VideoTechnology, IEEE Transactions on, vol. 13, no. 7, pp. 645–656, July2003.
[17] J. G. Beerends and F. E. D. Caluwe, “The influence of video qualityon perceived audio quality and vice versa,” Journal of the Audio
Engineering Society, vol. 47, no. 5, pp. 355–362, May 1999.
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