al-jobouri, fleury, ghanbari - 2014 - engineering wireless broadband access to iptv

8/16/2019 Al-Jobouri, Fleury, Ghanbari - 2014 - Engineering Wireless Broadband Access to IPTV

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The underlying transport protocol for HTTP is TCP, which

retransmits packets when acknowledgments fail. This implies that

there is no need for the channel coding used in our paper. How-

ever, over a wireless channel, TCP has difficulty distinguishing

between packet loss due to congestion and packet loss due to

transmission errors, implying that packets will be retransmitted

even if they may be again lost through a persistently poor wireless

channel. DASH compensates for TCP’s behavior by allowing the cli-ent to control the bit-rate of the stream being downloaded (by

selection between a set of streams with differing bit-rates). Unfor-

tunately, during periods of heavy network congestion, DASH

defaults to predominantly TCP control rather than client control.

Study of a Netflix application [8] showed service interruptions of

around 300 s, which is larger than a typical Windows wired device

buffer of 240 s. The risk to display interruption on an Android

device is still greater, as the typical buffer size is only 30 s. From

the evidence of the performance studies referred to in [8], the per-

formance of DASH has until recently been relatively poorly under-

stood. The main reason [9] that commercial companies have

implemented such multi-stream systems is not delivered video

quality, which is difficult to monitor in a DASH-based system,

but the compatibility of DASH with off-the-shelf web servers and

existing content-delivery networks. The simpler UDP transport

system, which is the subject of this paper: reduces the risk of video

service interruption; does not rely on network over-provisioning

[9]; and as a result potentially represents a greener solution.

The authors’ robust scheme for streaming video over wireless

broadband access has been simulated for IEEE 802.16 (WiMAX)

systems [10]. WiMAX may have recently lost the technological

competition with Long Term Evolution (LTE) [11] in developed

Western countries but it is still being deployed in rural areas

[12] and in countries where 3G cellular phone coverage is poor,

including Africa and the Middle East. WiMAX is also attractive

[13] for backhauling from local IEEE 802.11 networks. Though

the authors’ scheme as a whole has been analysed in previous

works such as in [14,15], the individual codec settings have not

been analysed in isolation. In fact, it has been suggested to the firstauthor that a very helpful service to the system developer commu-

nity would be to analyze codec settings independently of each

other, which is what this paper sets out to do.

The authors’ scheme combines data-partitioning as a form of

error resilience [16] with the addition of Forward Error Correction

(FEC) using rateless channel coding [17] at the application layer,

together with retransmission of extra redundant data when

required. Retransmission is limited to one round to avoid accumu-

lating latencies. The current authors have introduced into their

video streaming scheme various error resilience measures [18]

that exist in the literature: different rates and types of Intra-

Refresh (IR) Macroblocks (MBs) [19], Constrained Intra Prediction

(CIP) [20] and where necessary, redundant data-partitioned Net-

work Abstraction Layer (NAL) units (codec level packets) [21].The impact of each of these measures is analyzed in isolation from

each other, for Constant Bit Rate (CBR) as well as Variable Bit Rate

(VBR) streaming. CBR allows storage and bandwidth capacity to be

planned in advance, at a cost in video quality fluctuations. VBR

enables greater compression efficiency relative to CBR, which is

why it is generally used for disc storage. VBR can benefit from

two or even three-pass encoders, which are unsuitable for live

video compression. The relative merits of CBR and VBR are further

discussed in [22]. In general, we have noticed that many research-

ers on similar topics have not explored the effect of video settings

on their schemes and the authors believe that it is important to

investigate this aspect of any protection scheme in order to under-

stand the overall outcome of the scheme. In particular, it is impor-

tant to determine how critical the video codec settings are to the

success of a protection scheme. Is the scheme robust to changes

or should certain settings be set within a given range?

The remainder of this paper is organized as follows. The follow-

ing Section adds further information on how IPTV can be delivered

to the consumer, as well as supplying background technical con-

text. Section 3 selects research from the literature that reveals

the motivation behind the codec-based approach to video stream-

ing used in this paper. Particular attention is paid to video stream-ing over WiMAX in that section. Section 4 then outlines the

approach taken to protect IPTV streams. As the main focus of this

paper is the configuration of the scheme rather than the scheme

itself, the description is necessarily brief. Section 5 continues by

detailing how the video codec settings were modelled in order to

provide the evaluation that appears in Section 6. Section 7 summa-

rizes the findings and rounds off with some observations about

video streaming in this environment.

2. Context

Readers requiring further information on: IPTV, technical con-

text of H.264/AVC data-partitioning, and/or Raptor codes can con-

sult this Section.

2.1. IPTV delivery

There are two basic forms of IPTV: (1) That delivered over

closed or proprietary managed networks, including cable TV, often

to set-top boxes (STBs) that perform decoding and possibly decryp-

tion; and (2) That delivered over the unmanaged public Internet,

often displayed directly on desktop or laptop computer screens.

The latter may be called Web or Internet TV [23] or latterly

Over-the-Top (OTT) TV, as a way of distinguishing it from the ser-

vice that the telecommunications companies hoped to challenge

terrestrial broadcasters with by means of a high-quality service

delivered over closed networks. Increasingly the industry trend,

apart from cable TV, is towards the latter model of IPTV, i.e. OTTTV. There is no place for STBs when mobile IPTV [24] is delivered,

hence, our interest in OTT TV. The two forms of IPTV may differ in:

the picture quality of the stream offered (lower for unmanaged);

the amount of content available (higher for unmanaged); the for-

mats that the video is compressed to (the need to update the STB

is an issue); the way content is secured (unmanaged delivery

may not be encrypted or employ selective encryption [25]

instead); and the frame resolutions presented (lower resolutions

for unmanaged delivery). A flexible way to deliver IPTV is to set-

up (and tear-down) connections [26] using the Real-Time Stream-

ing Protocol (RTSP) (over reliable TCP transport), with subsequent

data delivery using the Real-time Transport Protocol (RTP) over

UDP transport. The Real-time Control Protocol (RTCP) can also

allow end-to-end feedback to the IPTV server to control the bitrate. RTSP also can support so-called trick mode functionality such

as rewind and pause.

To allow unmanaged delivery, OTT TV, to compete with Stan-

dard TV (SDTV) Quality-of-Experience (QoE), TV and video material

can be locally cached [27], reducing latency to the access link,

which in our paper is represented by a WiMAX base to subscriber

station link. Whether streaming over managed or unmanaged net-

works, packets will be lost at the access network. This is the case,

whether over broadband wireless or xDSL (Digital Subscriber Line),

as the latter also suffers from burst errors [28]. Prior to that,

whether managed or unmanaged networks are in use, video

streams are aggregated over high-capacity optical networks, such

as in Swisscom’s Bluewin IPTV service [29]. Only Passive Optical

Networks (PONs) can reduce the error rates at the access link but

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currently PONs are not widely deployed. The approach adopted in

this paper is potentially applicable across a range of access link

types, as it provides protection against error bursts and causes only

moderate delays. If a multicast service is required, it can also be

readily adapted from its unicast form by dropping acknowledg-

ments to the base station and increasing the level of FEC. This pos-

sibility was tested by us in [30] and, therefore, this paper confines

itself to unicast delivery.

2.2. H.264 codec

Features of the H.264 codec are used in this work. H.264/

Advanced Video Coding (AVC) standardization was initiated by

the Video Coding Experts Group (VCEG), which is a working group

of the International Telecommunication Union (ITU-T). The Joint

Video Team carried out the final task of developing H.264/AVC

[3], a co-operative effort of both Moving Picture Expert Group

MPEG and VCEG in 2003. Fig. 1 shows the video frame structure.

A video-frame in H.264/AVC is divided into MBs [31], which are

the basic unit for motion prediction. Each MB can be further sub-

divided into blocks that are transform-coded in order to de-corre-

late the data. For transmission, a video frame can be split into

slices, each of which occupies a network packet. When data-parti-

tioning is enabled, each slice can be further sub-divided in up to

three partitions, data-partitions-A, -B and -C, each of which can

occupy a separate network packet. It will be necessary to split a

network packet if its size exceeds the Maximum Transport Unit

(MTU) of the network.

2.3. Rateless channel coding

We selected Raptor codes [32] as our rateless code. Fig. 2 is a

simple diagram of how a Raptor encoder works. k represents

source symbols and m represents received symbols. A systematic

Raptor code is arrived at [32] by first applying the inverse of the

inner code to the first k symbols before the outer pre-coding step.

Systematic channel codes separate the redundant coding data fromthe information data, allowing the information data to be passed

directly to the source code decoder without channel decoding if

no errors are detected (usually by means of checksums).

For a rateless code, even if there were no channel errors, there is

a very small probability that the decoding will fail (the probability

converges to zero in polynomial time in the number of input sym-

bols), which failure can be modeled statistically by the scheme

introduced in [28]. In compensation, these codes are completely

flexible, have a theoretical linear decode computational complex-

ity, and generally their overhead is considerably reduced compared

to fixed erasure codes. Furthermore, if the packets are pre-encoded

with an inner code, as in Raptor codes to achieve a systematic code,

a weakened Luby Transform (LT) [33], with reduced computational

complexity compared to the original LT [28], can be applied to thesymbols and their redundant symbols.

In [32], an implementation of Raptor code is reported decoding

at several gigabits per second on a 2.4 GHz Intel Xeon processor. By

way of comparison, in 2013 smartphones generally had a four-core

processor running at around 1.5 GHz, though high-end smart-

phones had 64-bit processor clock speeds of around 2.2 GHz. As a

measure of its acceptability for mobile multimedia, Raptor coding

has been adopted for two wireless standards, Digital Video Broad-

casting (DVB) for handheld devices (DVB-H) [34] and Third Gener-

ation Partnership Project (3GPP) Multimedia Broadcast/Multicast

Services (MBMSs) [35], though neither uses the codes for unicastor accepts repair packet requests, as occurs in this paper. Impor-

tantly though, using Raptor code in these standards at the block-

level rather than the byte-level, as herein, can significantly impede

its throughput.

Notice that in these standards [34,35], application-layer Raptor

coding is applied at the packet-erasure correction level, while

physical-layer channel coding occurs at the bit-level. If physical-

layer correction fails according to checksum detection [36] then a

packet is marked as an erasure to be corrected at the application

layer. However in our paper, upon physical-layer correction failure,

packets are not marked as erased but their data are passed to the

application layer for byte-level Raptor code correction. A related

procedure is proposed for mobile phones in [37], when, after phys-

ical-layer correction failure, partially decoded packets are passed

to the application layer for block-level correction.

In a Raptor code, a belief-propagation (BP) algorithm can be

employed to decode the inner LT code. A BP implementation in

[38] treated decoding as a soft decoding task rather than correction

of erasures. The alternative is a hardware implementation of Rap-

tor’s inner code using Gaussian elimination. Gaussian elimination

has a total complexity of order O(nk2) to solve a linear equation

system with n output symbols and k unknowns (the original data

symbols), resulting in a linear per data symbol complexity of

O(nk). The outer code in [28] is selected as a Low-Density Parity-

check Code (LDPC), which is also an optional physical-layer code

in IEEE 802.11n, either using Gaussian elimination or in [39] a BP

algorithm in hardware. As Gaussian elimination is at the heart of

Raptor decoding, optimizations of the algorithm intended for hard-

ware implementation on mobile phones [40] are available.

3. Related research

A number of research papers have considered some aspects of

the video streaming method used by us. In [41] a packetization

method was presented for robust H.264 video transmission over

an IEEE 802.11 wireless local area network (WLAN) configured as

home network. Video robustness was enhanced by using small

NAL units and by retrieving possible error-free IP packets from

the received MAC frame. An aggregation scheme with a recovery

mechanism was deployed and evaluated via simulation. For fixed

physical-layer resources, the system provided a 2.5-dB gain in

video quality (PSNR) compared to making no NAL packetizationadjustments for similar throughput efficiency. Equally an 80%

Macro

block

Frame

Frame

slicesDP-A DP-B DP-C

DP-A DP-B DP-C

DP-A DP-B DP-C

Fig. 1. Video frame structure, DP-A = data-partition-A and similarly for DP-B andDP-C.

+ + + + + + ++ +++

codingOuter

LTcoding

Redundantnodes

k

m

Fig. 2. Raptor encoding scheme.

L. Al-Jobouri et al./ J. Vis. Commun. Image R. 25 (2014) 1493–1506 1495

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improvement in throughput was achieved for a similar video qual-

ity. However, data partitioning as a way of varying NAL unit sizes

was not used. The work in [41] was tailored to IEEE 802.11 WLANs

using the Distributed Coordination Function (DCF) for negotiation

of access to the wireless channel. As a result, data throughput

was strongly influenced by the data frame size. Broadband wireless

systems tend to employ centralized packet scheduling, typically

through Time Division Multiple Access (TDMA) with pre-config-ured frame sizes into which packets from each node (subscriber

station) are packed. Consequently, data partitioning for such sys-

tems is a more appropriate way of managing packetization issues.

Research in [42] used Forward Error Correction (FEC) and Auto-

matic Repeat re-Quest (ARQ) to support streaming over WiMAX,

exploiting features of the WiMAX standard. In particular, channel

state information held at WiMAX stations served to dynamically

construct the MAC Protocol Data Unit (MPDU). The size of these

units was thus determined such that the packet dropping probabil-

ity was minimized without compromising goodput. Simulation

results showed that the ARQ-enabled adaptive algorithm was

always better than the non-adaptive algorithm. The scheme in

[42] anticipated our work but no particular application was catered

for in [42] other than it should be a real-time streaming one and,

indeed, the authors of [42] were particularly concerned with voice

over IP (refer to [43]). Because our work is specialized for video

streaming it can apply aspects of video source coding to streaming.

We also utilize adaptive channel coding rather than the block

codes of [42]. While we utilize ARQ to request additional FEC data

according to channel conditions, ARQ in [42] was employed to

change the MPDU size, as the possibility of altering the channel

coding rate was not available to the authors of [42].

In [16] the researchers compared non-scalable video coding

with data partitioning using H.264/AVC under similar application

and channel constructions for conversational applications over

mobile channels. The experimental results showed that by using

the data-partitioning scheme the number of entirely lost frames

can be lowered and the probability of poor-quality decoded video

can be reduced. In the data-partitioning scheme of [16], differentialprotection was achieved by selecting from a set of discrete channel

coding rates, through punctured convolutional codes. However, in

order to determine the protection level, an optimization procedure

became necessary to minimize potential distortion. This procedure

depended on the quantization parameter (QP) and the coding rate

for each partition. The wireless channel characteristics also had to

be known in advance by the encoder. However, leaving aside the

computational complexity of the optimization search in [16], there

is another key difference between the scheme of [16] and this

paper. In [16] no feedback occurred, so that it was not possible to

request additional redundant data. In fact, when using punctured

convolutional codes in [16] (rather than the rateless codes used

herein) it was not possible to generate additional redundant data.

Data-partitioning can be viewed as a simplified form of SNR orquality layering. Extended quality layering can also be applied to

video streaming across WiMAX. In [44], adaptive multicast stream-

ing was proposed for WiMAX using the Scalable Video Coding

(SVC) extension for H.264. WiMAX channel conditions were mon-

itored in order to vary the bitrate accordingly. Unfortunately, the

subsequent decision of the JVT standardization body for H.264/

AVC not to support fine-grained scalability (FGS) implied it will

be harder to respond to channel volatility in the way proposed in

[44], which is one reason why we do not employ SVC and a number

of other issues surrounding SVC are mentioned in the rest of this

paragraph. Other work concerned with video streaming over

WiMAX links has also investigated: combining scalable video with

multi-connections in [45]; and comparing [46] H.264/SVC with

H.264/AVC for WiMAX. However, the data-dependencies betweenlayers in H.264/SVC medium-grained scalability remain a concern.

Unlike in FGS, enhancement layer packets may successfully arrive

but not be able to be reconstructed if key pictures also fail to arrive.

Besides, for commercial one-way streaming, simulcast is now

likely to be preferred to H.264/SVC for the reasons outlined in

[47]. In [47], it was found that the extra overhead from sending

an SVC stream compared to an H.264/AVC stream meant that the

cost of bandwidth consumption outweighed the reduced storage

cost of SVC once more than 64 sessions had occurred (assuming16 simulcast streams or 16 video layers per session). In another

comparison [48], it was proposed that scalable video with unequal

error protection cannot provide any advantage over H.264/AVC

with equal error protection in a wireless environment, due to the

overhead of scalable video coding compared to that of single-layer

coding.

4. Outline of streaming system

This Section outlines an effective video streaming system for

WiMAX that provides error resilience through source-code data

partitioning [16] and which works without the need to apply priv-

ileged protection to the high-priority partitions. As already men-

tion in Section 1, the main point of this paper is to draw

attention to the importance of correctly configuring the video

codec parameters. Therefore, this Section provides a basic outline

only and the interested reader is referred to the authors’ other

works, such as [14] and [15], for more details and variants of our

streaming system.

The H.264/AVC QP is set by us in such a way that temporally-

coded texture data occupies a larger part of a frame’s data than

that occupied by data in each of the other two partitions. If this

texture data should be dropped, it can be replaced more easily

through error concealment at the decoder than data in the other

two partitions. Error concealment (backward error correction)

[49] is a non-normative feature [50] of H.26/AVC that nevertheless

is present in the H.264/AVC JM reference code (found at http://

iphome.hhi.de/suehring/tml/). The texture data in partition-C ispacketized in a WiMAX MAC Service Data Unit (MSDU), within a

MAC Protocol Data Unit (MPDU) [10,51].

In contrast to the authors’ counter-intuitive approach, the intu-

itive approach is to give special protection to the partition-A,

which for predictively-coded frames includes motion vectors as

well as other important parameters. Partition-B, bearing intra-

coded MBs, may also be given special protection, as it contains spa-

tially-coded data whenever suitable references in other video

frames are not available. As an example of the Unequal Error Pro-

tection (UEP) approach, in [52] hierarchical modulation was

employed to favor those partitions with more important data for

the reconstruction of the video frame. For example, partition-A

motion vectors can be used for motion copy error concealment

when partition-C data are lost and, therefore, the intuitiveapproach is to protect partition-A (possibly combined with parti-

tion-B). Readers should consider for themselves from the evalua-

tion of this paper whether UEP measures are necessary.

Though no special protection is given, it is still necessary to pro-

tect the bit-stream (without privileging partitions A and B) against

the risk of packet loss. This was achieved through Equal Error Pro-

tection (EEP) of FEC provision. Application-layer rateless coding

[53] was selected for its flexibility and its linear computational

complexity at both the decoder and the encoder. To avoid long

latencies, which would occur if packet-level FEC were to be

applied, redundant data were added to the packets themselves,

treating the bytes within each packet as the data symbols. Again

to reduce latency, just a single Automatic Repeat reQuest (ARQ)

was made if the available data were insufficient to reconstruct acorrupted packet. Additional rateless redundant data were added


http://iphome.hhi.de/suehring/tml/http://iphome.hhi.de/suehring/tml/http://iphome.hhi.de/suehring/tml/http://iphome.hhi.de/suehring/tml/


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to the next available packet to be transmitted, according to the

amount calculated in the way specified by us elsewhere [14].

In an extension to the basic IPTV streaming scheme, we also

added redundant NAL unit packets. A discussion of alternative

redundant packet schemes is postponed to Section 6.4.

5. Simulation model

This Section details how we set about modeling the WiMAX

system for the evaluation of Section 6.

5.1. Simulation system

Fig. 3 shows the overall data flow of the simulation system. Raw

video (.YUV) is encoded by H.264/AVC into compressed form. The

compressed file is passed for later extraction of any dropped pack-

ets. At the same time, a video trace file is generated, which will

become an input into the ns-2 simulator [54]. The trace file con-

tains the size of each video packet and the transmission schedule.

However, the trace file does not contain any video data. After sim-

ulation using the wireless channel model, the simulator outputs alist of sent and dropped packets. This is used to filter from the ori-

ginal compressed data file any data that did not arrive at the des-

tination. The file is subsequently decoded by the H.264/AVC

decoder. The decoder outputs a raw video file in YUV (YCbCr) for-

mat. This file would normally be displayed but, for the simulation,

it is compared with the original raw input video. This allows the

objective video quality to be calculated as Peak Signal-to-Noise

Ratio (PSNR), through a pixel-by-pixel comparison.

Two video clips with different source-coding characteristics

were employed in the tests in order to judge the dependency of

the results upon video source-coding complexity. The first test

sequence was Paris, which is a studio scene with two upper body

images of presenters and moderate motion. The background is of

moderate to high spatial complexity leading to larger slices. Theother test sequence was Football, which has rapid movements

and consequently has high temporal coding complexity. Both

sequences were encoded at Common Intermediate Format (CIF)

(352 288 pixel/picture). CIF resolution was used for ready com-

parison with the prior work of others on video communication to

mobile devices.

5.2. Wireless channel model

The Gilbert–Elliott channel mode employed in this work has

been used by researchers in the wireless field [55,56] because of

its ability to model error burst patterns as experienced at the recei-ver. This channel model was introduced into the ns-2 event-driven

simulator [54]. The Gilbert–Elliott channel model itself is a two-

state Markov chain. It is based on: good and bad states; the prob-

abilities of these states; and the probabilities of the transition

states between them. In the case of the bad state, losses happen

with higher probability while in the good state losses happen with

lower probability. PGG refers to the probability of being in the good

state and PGB is the probability of a transition from the good state

to the bad state. PBB is the probability of being in the bad state and

PBG refers to the probability of a transition from the bad to good

state. PGG (PBB) can be interpreted as the probability of remaining

in the good (bad) state, given that the previous state was good

(bad). Conversely, PGB represents the probability that given that

the previous state was good, a transition is made from the good

to the bad state. By the law of total probability, all probabilities

sum to one (certainty). Therefore, we have PGG + PGB = 1, resulting

in (1). A similar argument for the bad state leads to (2).

P GG ¼ 1 P GB ð1Þ

P BB ¼ 1 P BG ð2Þ

For the stochastic process to remain stationary in time,

pG pGB ¼ pB pBG ð3Þ

where pG and pB are the steady state probabilities of being in a good

or bad state respectively. Again by the law of total probability,

pB = 1 pG. Substituting this expression for pB into (3) easily leads

to:

pG ¼ pBG

pBG þ pGBð4Þ

Similarly, pG = 1 pB. Substituting this expression for pG into

(3) easily leads to:

pB ¼ pGB

pBG þ pGBð5Þ

The Gilbert–Elliott model good and bad states have their own

error distributions that are independent of the process of arriving

or leaving those states, i.e. forming a Hidden Markov Model. Sup-

pose the probability of packet loss is pG and pB in the good and

bad states respectively. Then the average packet loss rate produced

by a Gilbert–Elliott channel is given in (6) by the usual expression

for the expectation of a probability distribution.

p ¼ pGpG þ pBpB ð6Þ

To model the effect of slow fading at the packet-level, as the Gil-

bert–Elliott model’s parameters, the PGG was set to 0.96,

PBB = 0.95, PG = 0.01 and PB = 0.02. Additionally, it is still possible

for a packet not to be dropped in the channel but nonetheless to be

corrupted through the effect of fast fading (or other sources of

noise and interference). This byte-level corruption was modelled

by the second Gilbert–Elliott model, with the same parameters

(applied at the byte level) as that of the packet-level model except

that PB (now probability of byte loss) was increased to 0.165. Effec-

tively, this second model emulates fast fading between good and

bad conditions.

The slow fading parameters in the Gilbert–Elliott model wereestablished empirically by a long series of trial simulations aimed

Video file

.YUV

JM 14.2

H.264/AVC

encoder

Generate

video trace

Received trace

packets

Sent trace

packets

Checking

dropped

packets

Filtered video

stream

Reconstructed

YUV file

PSNR

calculation

JM 14.2

H.264/AVCdecoder

Sending

node

Receiving

node

Network

channel model

Fig. 3. Simulation system.


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at establishing packet loss rates (PLRs) that were known from

experience to be critical to the acceptable reconstruction of a video

stream by a decoder. Specifically, PLRs below 5% can be tolerated

without protection measures, while above 10% it is difficult for

error resilience measures and/or channel coding to reconstruct a

video sequence. This observation can be generalized in the above

dual Gilbert–Elliott model to achieve data loss rates in the range

5–10%. It is only realistic to specify a data loss range because of the statistically nature of the model’s behaviour. In this paper,

we have presented results in the data loss range that was selected

as critical. It is perfectly possible for a link to be benign and no data

losses to occur but clearly one should engineer a streaming solu-

tion to cope with critical conditions. As the channel coding protec-

tion in this paper is adaptive, the problem of transmitting

redundant overhead in a benign channel is reduced. As extra

redundant data cannot be transmitted more than once, the possi-

bility of attempting video repair when no amount of protection

will work is also avoided. Fig. 4 is an example from preliminary

tests in which the Gilbert–Elliott PB parameter is systematically

varied while the other Gilbert–Elliott parameters were set as

above. This allows the relationship to the PLR for four reference

video clips to be found. By observation, the relationship is approx-

imately linear.

In [57] for an IEEE 802.15.4 wireless link, the authors take

extensive measurements of a bursty link to arrive at a metric for

burstiness, which is then found to be a generalisation of the burs-

tiness in a Gilbert–Elliott model. However, the Gilbert–Elliott

model differed from ours in representing the hidden bad state to

result in the loss of all packets and likewise the good state to result

in all packets surviving. An interesting observation of the authors

of [57] is that burstiness tends to occur when a mobile device is

at the limits of the range of a radio link, so that small changes in

the physical channel cause the signal to drop below the receiver’s

sensitivity. In [56], the estimation of model parameters from chan-

nel measurements is also treated for wired Internet examples.

5.3. WiMAX simulation configuration

The physical (PHY) layer settings selected for WiMAX simula-

tion on ns-2 [58] are given in Table 1. The antenna was modelled

for comparison purposes as a half-wavelength dipole. The Time

Division Duplex (TDD) frame length was set to 5 ms, as this is

the only value supported by the WiMAX Forum [59]. As mentioned

under modulation, the physical-layer FEC convolutional code rate

was ½. Video was transmitted over the downlink with UDP trans-

port (see Section 2.1). In order to introduce sources of traffic con-

gestion, an always available FTP (File Transfer Protocol) source

was modelled with TCP transport to a Subscriber Station (SS) from

the WiMAX Base Station (BS). Likewise a CBR source with packet

size of 1000 byte and inter-packet gap of 0.03 s was downloaded

to another SS.

6. Evaluation of codec settings

This Section evaluates in turn the codec configurations intro-duced in Section 1.

6.1. Intra-Refresh Macroblocks

As previously mentioned, in H.264/AVC data partitioning

[16,60], motion vectors (MVs) are packed into partition-A bearing

NAL units, allowing motion copy error concealment at the decoder

to partially reconstruct a picture, despite missing partition-C NAL

units (containing quantized transform coefficient residuals). Parti-

tion-B NAL units contain intra-coded (spatially encoded) MBs,

which are substituted for inter-coded MBs according to encoder

implementation (only the decoder input format is standardized

in H.264/AVC). Therefore, when Intra-Refresh (IR) MBs are

included alongside naturally intra-encoded MBs, partition-B slicesgrow in size. This means that data-partitioned video compression

provides a convenient way to examine the effect of various

amounts of IR MB provision. Once the H.264/AVC encoder has

formed a NAL unit, it can also provide a RTP header prior to encap-

sulation by IP/UDP network protocol headers.

A point to note is the different way that random IR MBs are

specified in the H.264/AVC JM 14.2 implementation compared to

that of cyclic IR line intra update. In random IR MB, a maximum

percentage of IR can be specified, which percentage includes

already encoded IR MB. If the given quota of IR MB is already lar-

gely occupied by naturally encoded MBs (those encoded to cover

newly revealed objects or to improve the quality of the video up

to a given bit budget or for some other encoder-dependent reason),

then only a small amount of extra randomly inserted MBs will beadded. In contrast, if a line of IR MBs is inserted then these MBs

0

5

10

15

20

25

0.03 0.06 0.09 0.12 0.15 0.18 0.21 0.24 0.27 0.3

PB

P a c k e t l o s t %

Foreman

Car Phone

Highway

Paris

Fig. 4. Example plot showing the relationship between Gilbert–Elliott PB parameter

and packet loss rate for several CIF video sequences at 30 Hz, with data-partitioningapplied.

Table 1

IEEE 802.16 (WiMAX) parameter settings.

Parameter Value

PHY OFDM

Frequency band 5 GHz

Bandwidth capacity 10 MHz

Duplexing mode TDD

Frame length 5 ms

Max. packet length 1024 BRaw data rate 10.67 Mbps

IFFT size 1024

Modulation 16-QAM 1/2

Guard band ratio 1/8

DL/UL ratio 3:1

Channel model Gilbert–Elliott

SS transmit power 245 mW

BS transmit power 20 W

Approx. range to SS 1 km

Antenna type Omni-directional

Antenna gains 0 dBD

SS antenna height 1.2 m

BS antenna height 30

PHY = Physical layer, IFFT = Inverse Fast Fourier Transform, DL/UL = Downlink/

Uplink, QAM = Quadrature Amplitude Modulation, SS = Subscriber Station,

BS = Base Station, TDD = Time Division Duplex, OFDM = Orthogonal Frequency

Division Multiplexing.



7/14

are added in addition to those intra-coded MBs that have already

been included by the encoder, as shown in Fig. 5.

Football was VBR encoded with a Group-of-Pictures (GoP) struc-

ture of IPPP. . . at 30 frame/s. (Refer forward to Section 6.3 to see

the tests that led to choice of the more favourable IPPP. . . GoP

structure.) From Table 2, it is apparent that, as the percentage of

IR MBs is increased, the size in bytes of partition-B increases for

the same QP. Because more MBs are assigned to partition-B, thesize of partition-C reduces. And because of the large amount of nat-

urally-encoded intra MBs, this effect is gradual until 25% of random

IR MBs are added. 25% of random IR MBs is shown in Table 2, as

that amount approximately corresponds to the total partition-B

size if cyclic line intra update is turned on instead (with approxi-

mately the same number of MBs).

Fig. 6 illustrates the range of metrics we extracted from our

codec configuration tests. However, it should be noted that, in

Fig. 6, increasing the provision of IR MBs from 2% to 5%, then to

6% and finally 25% (in the case of MB line intra update), increases

the throughput and, hence, the bandwidth requirements in respect

to co-existing traffic. The 25% IR commitment tested is large in

practice, due to the coding inefficiency of spatial reference coding.

It results in larger packets and the size of packets is the most

important factor affecting the percentage of dropped packets, as

is also evident from the decrease in dropped packet percentages,

Fig. 6a, when the QP increases (and video quality decreases). From

Fig. 6a and c, higher-quality video (QP = 20, 25) benefits from ran-

dom insertion (and this effect is reversed for low-quality video).

From the objective video quality (PSNR) resulting, Fig. 6c, it can

be seen that reducing the IR MB percentage to 2% actually

improves the PSNR at QPs 30 and 35. From this one can conclude

that there is little if anything to be gained by raising the IR percent-

age. This is not surprising, as at lower QPs the encoder has a greater

bit budget and, hence, can include more naturally-encoded intra

MBs. In addition, the main effect of reducing the percentage of IR

MBs is that the size of partition-B-bearing packets is reduced. In

turn, this makes these packets less likely to be affected by channel

conditions, especially burst errors arising from fast fading. Conse-quently, more partition-B packets survive intact, again causing a

relative gain in video quality.

Packet end-to-end delay, Fig. 6d, is the mean delay of those

packets unaffected by channel conditions. The results show that

this is generally small in duration, though with a tendency to

increase due to the propagation delay of larger packets at lower

QPs. Significantly, a lower percentage of IR MBs, in addition to bet-

ter quality video in many cases, actually results in lower delay.

Turning to corrupted packets, there are larger percentages of

corrupted packets at higher QPs, Fig. 6b. These are packets that

have not been repaired completely by the adaptive channel coding

scheme. Because of the additional transmission time, the mean

end-to-end delay of corrupted packets is higher than other packets,Fig. 6e. In fact, it is the extent of the delay that is the main contri-

bution of corrupted packets to the quality-of-service. However,

though the percentage of corrupted packets increases at higher

QPs, the packet sizes decrease due to the reduced coding efficiency.

Smaller packets take less time to re-transmit compensating for the

increase in the number of corrupted packets.

6.2. Constrained intra prediction setting

In order to decode partition-B and -C, the decoder must know

the location from which each MB was predicted, which implies

that partitions B and C cannot be reconstructed if partition-A is

lost. Though partition-A is independent of partitions B and C, CIP

should be set in the codec configuration [20] to make partition-Bindependent of partition-C. (Though reference [20] refers to a pro-

posal to add constrained inter prediction to H.264/AVC, it also

describes constrained intra-prediction, which is already a part of

the codec standard.) By setting this option, partition-B MBs are

no longer predicted from neighboring inter-coded MBs. This is

because the prediction residuals from neighboring inter-coded

Fig. 5. Differences between random intra-refresh MBs (upper frames with 6%) and MB cyclic line intra update (lower frames).

Table 2

Mean size of different partitions in bytes for Football at various QPs.

QP 2% Intra-refresh MB 5% Intra-refresh MB 6% Intra refresh MB

A B C A B C A B C

20 1842 2678 3889 1845 2767 3867 1846 2810 3850

25 1687 1697 2533 1690 1763 2511 1696 1793 2502

30 1459 1047 1496 1463 1082 1482 1467 1098 1479

35 1117 572 688 1120 595 682 1123 604 681

QP 25% Intra-refresh MB MB line intra update

A B C A B C

20 1893 3450 3669 1885 3385 3683

25 1746 2216 2379 3683 2160 2400

30 1505 1346 1405 1498 1312 1414

35 1146 729 646 1143 716 652


http://-/?-


8/14

MBs reside in partition-C and cannot be accessed by the decoder if

a partition-C packet is lost. There is a by-product of increasing

packet sizes due to a reduction in compression efficiency but the

increase in size may be justified in error-prone environments.

The two video clips (Paris and Football) were VBR encoded at

CIF, with a GOP structure of IPPP(for choice of GoP structure again

refer forward to Section 6.3). . .

at 30 Hz and with 5% IR MBs(choosing a lower percentage as a result of the tests in Section 6.1).

Table 3 presents NAL unit sizes for the Paris sequence with and

without CIP, showing the increase in partition-B and -C sizes,

which results from the loss in encoding efficiency. Notice that

any NAL units that are above the maximum packet size of 1024

B in Table 3 are later constrained by the encoder to the MTU when

forming an RTP packet prior to encapsulation by network headers.

The reason for this precaution is to avoid these larger NAL units

being segmented at the link layer, avoiding the possible separation

of header information from NAL data.

At lower QPs, i.e. higher-quality video, the relative size of parti-

tion-C NAL units means that the more important partition-A and -B

packets are less likely to suffer channel error. However, the larger

packet sizes mean that congestion may have more of an impact,because longer packets take longer to transmit and free the

channel. At higher QPs, the advantage of differential packet sizes

is lost but the generally smaller packet sizes compensate to some

extent. There is also a small growth in partition-B and -C packet

size when CIP is turned on.

From Table 4 for Football one sees that though the relative rank-

ing of sizes between the partition types is similar, the actual sizes

are larger than those for Paris (see Table 3). The larger sizes are due

to the temporal coding complexity of Football. For high QP, the rel-

atively larger size of partition-A NAL units compared to the other

partitions NAL units may create a problem, as it does not result

0

6

12

18

24

30

20 25 30 35

D r o p p e d p a c k e t s %

QP

2% Intrarefresh MB

5% Intra

refresh MB

6% Intra

refresh MB

MB Line Intra

Update

0

6

12

18

24

30

20 25 30 35

C o r r u p t e d p a c k e t s %

QP

2% Intra

refresh MB

5% Intra

refresh MB

6% Intra

refresh MB

MB line Intra

Update

(a) (b)

0

8

16

24

32

40

20 25 30 35

M e a n P S N R ( d B )

QP

2% Intra

refresh MB

5% Intra

refresh MB

6% Intra

refresh MB

MB Line

Intra Update

0

0.03

0.06

0.09

0.12

20 25 30 35 P a c k e t m e a n e n d - t o - e n d d e l a y ( s )

QP

2% Intra

refresh MB

5% Intra

refresh MB

6% Intra

refresh MB

MB Line Intra

Update

(c) (d)

0

0.03

0.06

0.09

0.12

0.15

20 25 30 35 C o r r u p t e d p a c k e t s m e a n d e l a y ( s )

QP

2% Intra

refresh MB

5% Intrarefresh MB

6% Intra

refresh MB

MB LineIntra Update

(e)

Fig. 6. Mean performance metrics for Football with 2%, 5%, 6% IR MBs and MB line intra update.

Table 3

Paris video sequence: Mean NAL unit size in bytes according to partition type and

video quality.

QP Without CIP (B) With CIP (B)

A B C A B C

20 740 495 4097 738 504 4154

25 601 336 2058 601 356 2093

30 473 210 838 473 238 857

35 331 124 281 330 149 291



9/14


10/14

GoP structures: IPPP. . . (i.e. one initial I-picture and all P) and

IBBPBBP. . . (i.e. insertion of bi-predictive B-pictures for greater

coding efficiency but still with one initial I-picture). Before starting

those tests, we examined the effect of the two different GoP struc-ture types on the sizes of video frames. One potential impact of the

GoP structure is that B-pictures increase coding efficiency at a cost

in coding complexity due to the need to reference at least two

other pictures. Unfortunately, with the inclusion of B-pictures,

the mean size of P-pictures increases, as a result of the increased

reference distance between P-pictures. For example, for QP = 20,

the IBBPBBP. . . mean P-picture size is as high as 15 kB, which

may well result in a series of large packets.

The tests were again performed on Paris and Football. Both

sequences were VBR encoded video at 30 Hz, CIF, with 2% IR MBs

randomly inserted. Recall from Section 6.1 that inserting 2% of IR

MBs gave the best video quality and the lowest delay, which is

why this percentage of IR MBs was selected for these tests. CIP

was configured and the two different GoP types (IPPP. . .

andIBBP. . .) generated the video traces.

The effect of adding B-pictures is evident in Fig. 12, in which

many more packets are dropped for Football at QP = 20. ‘Dropped

packets’ includes buffer overflow and outright channel drops.

Repeated simulations of the IBBP. . . configuration of Football for

QP = 20 confirmed the packet drop spike at this setting. The effect

derives from the larger P-pictures that are the result of inserting B-

pictures into the GoPs, when P-pictures are already large because

of the lower QP setting. The result is a series of large P-picture-

bearing packets. As previously mentioned, from Table 5, the Foot-

ball mean P-picture size at QP = 20 for IBBP. . . is almost twice the

size of that when an IPPP. . . GoP structure is configured and simi-

larly twice the size of P-pictures for either of the Paris GoP config-

urations at QP = 20 in Table 5. The IBBP. . . GoP structure

particularly impacts the more temporally complex sequence,

resulting in large B-partition packets. A series of large packets

results in more transmission errors and more packet drops if the

send buffer becomes saturated. The general reduction in packet

drop numbers in Fig. 12 for decreasing QP, results in an increase

in video quality in Fig. 13. Moreover, an IPPP. . . GoP structure is

preferable except at QP = 35. However, at QP = 35 all GoP struc-

tures result in a PSNR of over 25 dB.Corrupted packet levels are generally high, Fig. 14, but in

respect to GoP structure it seems that an IPPP. . . structure may

be more favorable for temporally complex content (Football) and

vice versa for less active sequences. As was previously remarked,

the main consequence of higher levels of packet corruption, after

the application of the proposed adaptive scheme, is in greater

delay for a greater percentage of packets, Fig. 15. Apart from the

anomaly at QP = 20 for Football with an IBBP. . . GoP structure, as

0

0.005

0.01

0.015

0.02

0.025

20 25 30 35

C o r r u p t e d p a c k e t s m e a n d e l a y ( s )

QP

Paris with

CIP

Pariswithout CIP

Football

with CIP

Football

without CIP

Fig. 11. Paris and Football video sequences: Protection scheme mean delay of

corrupted packets, with and without CIP.

0

4

8

12

16

20

20 25 30 35


QP

FootballIPPP...

Football

IBBP...

Paris

IPPP...

ParisIBBP...

Fig. 12. Dropped packets for differing GoP structure and content.

Table 5

Mean P-picture size (bytes) according to QP for two different GoP structures.

QP Football Paris

IPPP. . . IBBP. . . IPPP. . . IBBP. . .

20 8905 15,520 5102 7590

25 6301 10,311 2824 4249

30 4185 6381 1398 2238

35 2444 3756 647 1100

0

7

14

21

28

35

20 25 30 35


QP

Football

IPPP...

Football

IBBP...

Paris

IPPP...

Paris

IBBP...

Fig. 13. Video quality (PSNR) for two different GoP structures and content.

0

7

14

21

28

35

20 25 30 35

C o r r u p t e d p a c k e t s %

QP

FootballIPPP...

FootballIBBP...

ParisIPPP...

ParisIBBP...

Fig. 14. Percentage of corrupted packets for two different GoP structures andcontent.



11/14

a result of many more large packets each resulting in more trans-

mission delay (refer back to the discussion of Fig. 12 and Table 5),corrupted packet delay is approximately twice that of normal

packet end-to-end delay, Fig. 16, reflecting the single retransmis-

sion of extra redundant that is permitted. Again for Football,

QP = 20 the mean packet delay is much higher in Fig. 16 as a result

of many more large P-picture packets each with more transmission

delay when using an IBBP. . . GoP structure. It was also confirmed

that for a moderate increase in mean packet size, making parti-

tion-B completely independent of partition-C through CIP resulted

in a small (a few dB) improvement in video quality, whenever the

QP setting allowed sufficient packets to be delivered.

6.4. Redundant NAL units

To improve video quality it is possible to provide redundantNAL unit packets. There is a variety of ways of providing redundant

packets.

It is possible to use redundant picture slices [62] or duplicate

picture slices [63]. Redundant picture slices employ a higher QP

and, hence, coarser quantization than the original slices. Those

interested in investigating the use of redundant slices further

should notice that methods to refine the selection of redundant

slices [64] have also been designed. However, in our scheme using

redundant picture slices will cause additional drift between the

encoder and the decoder, if (say) a partition-A packet was matched

with a partition-C packet’s data with a different QP. Therefore, we

tested the inclusion of duplicate picture slices/data partitions using

the same QP as the original slice.

Even so, there is an implementation issue when employingduplicate picture slices. Though both redundant/duplicate slices

and data-partitioned slices co-exist in the Extended profile, they

are not jointly implemented in the JM implementation of H.264/

AVC [65] and, in fact, appear to not to be implemented at all in

most other software codec implementations such as QuickTime,

Nero, and LEAD randomly to name a few. However, when employ-

ing data-partitioning, it is also possible through repeated runs of

the encoder to create an additional stream of all partition-A slice

packets or an additional stream consisting of partition-A and par-tition-B packets or, indeed, a complete duplicate version of the ori-

ginal stream.

To test the use of duplicate packets, the same two video clips

(Paris and Football) with different source coding characteristics

were employed in the tests to judge content dependency. Both

sequences were VBR encoded, with a GoP structure of IPPP. . . at

30 Hz. 5% IR MB data were added to each picture, increasing the

size of partition-B packets (refer to Table 2). Again a low percent-

age of IR MBs was added as a result of the gains in video quality

experienced in Section 6.1’s tests from avoiding higher percentages

and, as before, the favorable IPPP. . . GoP structure was selected as a

result of the tests in Section 6.3.

The duplicate NAL units do not amount to a change in bitrate

because the packets are simply replicated. However, the end-to-

end packet delay will obviously increase because of the interleav-

ing of the duplicate slice packets. In the redundant/duplicate NAL

unit scheme, retransmission of extra redundant data was sched-

uled for all corrupted packets, even if two packets duplicated each

other. This is because it is not possible to know in advance whether

the extra redundant data will arrive for any one of the two packets.

This provision has a significant effect in improving the video qual-

ity at higher QPs. The reason is that retransmitting extra redundant

data by two alternative means increases the chance that a packet

can be reconstructed.

Fig. 17 shows the effect of the various schemes on packet drops

when streaming Paris. ‘Data-partition’ in the Figure legend refers to

sending no redundant/duplicate packets. ‘Redundant X’ refers to

sending duplicate redundant packets containing data-partitions

of partition type(s) X in addition to the rateless coded data-parti-tion packets. From Fig. 17, the larger packet drop rates at

QP = 20, due to the larger packets, will have a significant effect

on the video quality.

Fig. 18 shows the pattern of corrupted packet losses arising

from simulated fast fading. There is actually an increase in the per-

centage of packets corrupted if a completely redundant/duplicate

stream is sent (partitions A, B, and C), though this percentage is

taken from corrupted original and redundant/duplicate packets.

However, the effect of the corrupted packets on video quality only

occurs if a packet cannot be reconstructed after application of the

adaptive retransmission scheme.

0

0.02

0.04

0.06

0.08

20 25 30 35

C o r r u p t e d p a c k e t s m e a n d e l a y ( s )

QP

Football

IPPP...

Football

IBBP...

Paris

IPPP...

Paris

IBBP...

Fig. 15. Corrupted packet mean delay for two different GoP structures and content.

0

0.015

0.03

0.045

0.06

20 25 30 35

P a c k e t s M e a n e n d - t o - e n

d d e l a y ( s )

QP

Football

IPPP...

Football

IBBP...

Paris

IPPP...

Paris

IBBP...

Fig. 16. Mean end-to-end packet delay for differing GoP structure and content.

0

1

2

3

4

5

20 25 30 35


QP

Data

partition

Redundant

A

Redundant

A,B

Redundant

A,B,C

Fig. 17. Paris sequence protection schemes’ packet drops.


http://-/?-http://-/?-http://-/?-


12/14

Examining Fig. 19 for the resulting video quality (PSNR), one

sees that data partitioning with FEC protection, when used without

redundant/duplicate packets, is insufficient to bring the videoquality to above 31 dB, that is to a ‘good’ quality. However, it is

important to notice that sending duplicate redundant partition-A

packets alone (without redundant packets from other partitions)

is also insufficient to raise the video quality to a ‘good’ rating

(above 31 dB). Therefore, to raise the video quality to a ‘good’ level

requires not only the application of the adaptive rateless channel

coding scheme but also the sending of duplicate data streams.

The impact of corrupted packets, given the inclusion of retrans-

mitted additional redundant data, is again largely seen in addi-

tional delay. As before, there is an approximate doubling in per

packet delay between the total end-to-end delay for corrupted

packets Fig. 20 and normal packet end-to-end delay, Fig. 21. It

must be recalled, though, that for the redundant schemes there is

up to twice the number of packets being sent. Therefore, delay is

approximately further doubled, still though with end-to-end

delays remaining in the tens of millisecond range. As previously

noted, this type of delay range is acceptable even for interactive

applications, but may contribute to additional delay if the WiMAX

link forms part of a longer network path.

The experimental results for Football are summarized in Table 6.

Table 6 shows how packet drops and losses are reflected in video

quality. Very large numbers of packets are dropped at QP = 20

because of the larger packet sizes. However, there is a threshold

effect, as the numbers of dropped packets decline quickly with

increasing QP (as packet sizes reduce). The protection pattern for

redundant/duplicate packets is accentuated compared to Paris, in

the sense that providing duplicate redundant versions of more

than just partition-A packets is now clearly seen to be preferable.

Given that in Quality-of-Experience subjective tests for mobile

devices [66], news scenes rather than sport are preferred by view-

ers, it may be advisable to favor content without rapid motion,

especially if small footballs or similar sports’ balls need to be

tracked by the viewer.

6.5. Discussion

As is normal in a research environment and in papers of this

nature, we have made a set of simulations of IPTV video streaming

rather than a testbed. The disadvantage of a testbed, whatever itsmerits in terms of verisimilitude is a lack of flexibility. Therefore,

0

6

12

18

24

30

20 25 30 35

C o r r u p t e d P a c k e t s %

QP

Data partition

RedundantA

Redundant

A,B

RedundantA,B,C

Fig. 18. Paris sequence protection schemes’ corrupted packets.

0

7

14

21

28

35

20 25 30 35


QP

Data partition

Redundant

A

RedundantA,B

RedundantA,B,C

Fig. 19. Paris sequence protection schemes’ video quality.

0

0.03

0.06

0.09

0.12

0.15

20 25 30 35

C o r r u p t e d

p a c k e t m e a n d e l a y ( s )

QP

Data

partition

Redundant

A

Redundant

A,B

RedundantA,B,C

Fig. 20. Paris sequence protection schemes’ mean delay for corrupted packets.

0

0.03

0.06

0.09

0.12

20 25 30 35

P a c k e t m e a n e n d - t o - e n d d e l a y ( s )

QP

Data

partition

Redundant

A

Redundant

A,B

Redundant

A,B,C

Fig. 21. Paris sequence protection schemes’ mean end-to-end delay for normal

packets.

Table 6

Football redundant/duplicate NAL unit results.

QP Data-partition Redundant A Redundant A, B Redundant A, B, C

Dropped packets (%)

20 6.92 2.69 13.55 23.12

25 4.23 2.50 1.38 4.88

30 3.97 1.44 0.46 0.12

35 1.66 1.44 0.38 0.00

Corrupted packets (%)

20 30.76 31.37 22.72 14.51

25 30.64 30.79 30.27 25.11

30 27.56 30.79 27.42 26.97

35 21.92 16.55 24.73 22.35

PSNR (dB)

20 19.98 23.65 23.11 19.65

25 20.96 26.47 27.58 33.9230 21.16 29.45 29.16 34.50

35 23.27 27.65 27.59 30.73



13/14

in an ideal world both types of tests should be conducted. In the

absence of a testbed then detailed simulation can be indicative of

the streaming performance if not a conclusive demonstration. Both

types of test environments may not anticipate all the physical con-

ditions that may arise such as distances from the base station,

types of channel fading, and multi-path effects. It should be

noticed though that the Gilbert–Elliott channel model used in the

tests is not a physical model of channel conditions but a modelof the burst errors experienced at the receiver. In other words, it

models the error patterns rather than the physical conditions that

given rise to error conditions. This distinction may explain the pop-

ularity of this type of channel model for studies of video commu-

nication over wireless networks.

Certain aspects of the proposed scheme such as data-partition-

ing, CIP, IR MB percentage, and GoP structure can be configured at

encoding time, allowing pre-storage of TV programs within server

banks. Unfortunately, the wireless environment is notoriously vol-

atile, especially if mobile stations are present. It is for this reason

that we include the rateless channel coding element that allows

the video server, herein collocated at the WiMAX base station, to

adapt the rateless channel coding rate to adapt to channel condi-

tions. Compared to (say) dropping frames the adaptive channel cod-

ing solution is more fine-grained, as it occurs at the packet level.

Consequently, the user experience is less likely to be disrupted.

Other adaptive solutions are possible that take advantage of

flexibilities within the hardware. For example, the authors have

themselves experimented with a form of WiMAX adaptive modula-

tion in [67]. The disadvantage of such approaches is that they are

technology dependent in the sense that the firmware within a base

station may need to be modified, sometimes through cross-layer

intervention. A software adaptive approach such as the one using

adaptive rateless coding in this paper can more easily be deployed

and modified for differing broadband wireless technologies.

7. Conclusion

Both FEC and data-partitioning of IPTV video streams are a way

of providing graceful quality degradation in a form that will work

in good and difficult wireless channel conditions. This paper

showed that video configuration also affect the video quality,

dropped packets and delay. In that respect, it was shown that it

is better to include a small percentage of IR MBs that can build

their effect over time than employ the cyclic IR line update scheme.

Packet size, which is determined by content, video quality, and GoP

structure is an important determinant of packet drops. The use of

equal error protection is a way of taking advantage of the natural

packet size differential, which is in inverse order of the priority

of the data partitions. Thus, smaller packet lengths already confer

a lower risk of channel error. However, the inverse size order of

data partitions (larger partition-A and -B) was seen to occur whensmaller QPs were chosen. It was also confirmed that for a moderate

increase in mean packet size, making partition-B completely inde-

pendent of partition-C resulted in a small but significant improve-

ment in video quality.

An interesting observation is that there is a need to reduce

packet size to reduce packet loss, despite the combined effect of

redundant packets and application adaptive channel coding. This

is because during ‘bursty’ error conditions (as was simulated by

the Gilbert–Elliott channel model) it is possible that both the origi-

nal packet and its redundant counterpart may be dropped or cor-

rupted. However, this effect is dependent on choice of QP, as a

low QP can lead to high packet drop rates with poor video quality.

In general, in poor channel conditions with both slow and fast fad-

ing, it is not sufficient to employ just application-layer FEC unlessstream replication also takes place.

The evaluation tests performed in this paper employed two ‘ref-

erence’ video sequences from a number of such sequences that

video coding experts provide as a test of codec implementations.

Another valid approach, particularly when developing a specific

product is to select from video actually requested by members of

the public. For example, video requests can be selected from a real

trace file and used to select popular videos that can subsequently

be used in tests. In fact, this approach represents future work forthis research. Future work will also confirm the validity of the

wireless channel model by streaming video over a live WiMAX

link.

Acknowledgments

Laith Al-Jobouri, who has recently completed his doctorate at

the University of Essex, UK, would like to thank his financial spon-

sors at the Ministry of Science and Technology, Baghdad, Iraq.

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