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Improving QoS of IPTV
and VoIP over IEEE 802.11n
Saad Saleha,, Zawar Shahb, Adeel Baiga,c
aSchool of Electrical Engineering and Computer Science (SEECS),
National University of Sciences and Technology (NUST), Islamabad, PakistanbWhitireia Community Polytechnic, Auckland, New Zealand
cCollege of Computer and Information Systems, Al Yamamah University, Kingdom of Saudi Arabia
Abstract
Tremendous growth rates of Internet Protocol Television (IPTV) and Voice over Internet Protocol (VoIP) have de-
manded the shift of paradigm from wired to wireless applications. Increased packet loss with continuously varyingwireless conditions make the transmission a challenging task in wireless environment. Our study investigates and
proposes improvement in the transmission of combined IPTV and VoIP over the IEEE 802.11n WLAN. Our major
contributions include the analytical and experimental investigations of (1) Transport layer protocol UDP/TFRC for
IPTV and VoIP, (2) Optimal physical layer parameters for IPTV and VoIP, (3) Proposition of wireless enhancement
of TFMCC (W-TFMCC) to enhance the capacity and Quality of Service (QoS) of wireless IPTV and VoIP. Analytical
and experimental evaluations show a 25% increase in capacity using TFRC with 167% more bandwidth share to TCP.
Our study shows that use of W-TFMCC with optimal parameters can enhance IPTV and VoIP capacity by 44%.
Keywords: IPTV; VoIP; DCCP; TFRC; Multi-casting; TFMCC.
1. Introduction
Internet Protocol Television (IPTV) is one of the fastest growing applications which has gained huge growth rates
in the past few years. Number of IPTV users are expected to increase by 500% from 2011 to 2016 [1]. Large growth
rate with increased users interest motivate us to study transmission of IPTV with an aim to provide better Quality of
Service (QoS). IPTV offers a number of advantages over its predecessor analog technologies. Major advantages of
IPTV include user interaction, video on demand service, economic and better Quality of Service (QoS). Architecture
of IPTV includes three entities: video head end, transport network and video receiver. Video head end is placed at
the server side and it has the tasks of video encoding and transmission of video and audio to the user end. Transport
network is the entity which plays the most crucial rule because it incorporates jitter, delay, scrambling and packet
loss effects during the transmission of video. Transport network includes both wired and wireless medium. Inside
the transport network, a number of queues having the parallel storing capabilities which shuffle the packets. Video
receiver is the last entity which has the task of decoding information, eliminating delay and jitter factors and managinga reliable QoS at the user end.
Voice over Internet Protocol (VoIP) is another fastest growing internet application which has obtained huge growth
rates in the past few years. There are 10 times more VoIP users than IPTV users[1]. Major factors for VoIP success
are cheap calling rates, better QoS and better penetration among end users. VoIP uses bi-directional traffic and has
more challenging requirements for packet loss and delay than IPTV. Transmission of VoIP requires limited packet loss
and delay for all users which becomes challenging when optimum route changes for all users.
Corresponding author
Email addresses:[email protected](Saad Saleh),[email protected](Zawar Shah),
[email protected] (Adeel Baig)
Preprint submitted to Journal of Computers and Electrical Engineering October 23, 2014
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Currently, wired access links are preferred by service providers for transmission of IPTV and VoIP services owing
to minimum packet loss and delay in the wired links. Transmission of IPTV and VoIP becomes challenging in the
wireless environment because major bandwidth restriction occurs at the user end having wireless Access Point (AP)
[2]. Packets drop from queues of the wireless AP which make it difficult to meet the QoS constraints of IPTV and
VoIP. Moreover, range and data rate are also limited in wireless links owing to the continuously varying wireless
conditions. Users demand, ease of access and freedom of mobility require an insight investigation for transmission of
IPTV and VoIP over wireless networks.
IEEE 802.11n Wireless Local Area Network (WLAN) is the latest standard proposing data rates upto 600 Mbps
(theoretically) and 300 Mbps (practically). IEEE 802.11n is equipped with a number of features which include its
Multiple Input Multiple Output (MIMO) technology and frame aggregation mechanisms at Medium Access Control
(MAC) layer and Physical (PHY) layer. Frame aggregation combines multiple frames at MAC layer and PHY layer
level. Major advantage of frame aggregation includes the reduction of header over-head time and also the reduction
in the collision time. Our previous study for IPTV and VoIP capacity over IEEE 802.11n shows that aggregation of 4
packets is the optimal aggregation size for capacity enhancement of IPTV and VoIP [3]-[4].
Enhancing QoS of IPTV and VoIP with increased capacity over IEEE 802.11n has been actively discussed in
various studies due to the challenging IPTV constraints over WiFi. Packet loss is a major factor which results incapacity reduction for IPTV and VoIP. IPTV and VoIP are extremely susceptible to packet loss because both use User
Datagram Protocol (UDP) at the transport layer.
UDP is a constant bit rate protocol. By use of UDP, packets accumulate at the AP which results in congestion
at the AP. All packets crossing the limits of queue size are dropped at the AP. Our study shows that UDP provides
less delay but it increases packet loss which becomes the bottleneck for other users. Our previous study [ 3]-[4] shows
that Datagram Congestion Control Protocol (DCCP) is the better suited protocol for transmission of IPTV and VoIP.
DCCP has two variants namely TCP-like and TCP Friendly Rate Control (TFRC). TCP-like offers high reliability
and decreases its data rate much more rapidly than TFRC. This makes it suitable for all applications demanding less
packet loss. On contrary, TFRC offers a nearly constant data rate by maintaining its data rate according to varying
conditions of the network. Behaviour of TFRC makes it suitable for all applications which require less delay. Our
investigations [3]-[4] reveal through simulations that TFRC gives better performance than UDP for transmission of
IPTV and VoIP over IEEE 802.11n.In this paper, we aim to develop an analytical model for transmission of IPTV and VoIP over IEEE 802.11n.1
Transport layer protocols UDP and TFRC are modelled by their behaviour in the wireless environment. Extensive
experiments are performed to validate the analytical results. Various physical layer parameters are modelled through
SIFS, DIFS and default behaviour of wireless environment. Optimal values of queue size, contention window, SIFS
and DIFS are proposed. Analytical values of physical layer parameters are compared with experimental results.
We propose Wireless TCP Friendly Multicast Congestion Control Protocol (W-TFMCC). TFRC and TCP-like suffer
low capacity because both use the unicast mechanisms. Capacity can be enhanced significantly by shifting unicast
transmissions to multicast transmissions. In this paper we present the results of TCP Friendly Multicast Congestion
Control Protocol (TFMCC). TFMCC is designed for wired networks which suffer low packet loss and all users are
nearly in the same conditions. TFMCC keeps a track of the user facing worst packet loss conditions and adjusts its
sending rate according to the worst case user. This is highly unsuitable for the wireless medium because all users
are present in different environments. TFMCC forms channel groups based only upon users demands. Transmission
for the worst case user would lead to lower data rate even if a single user is having high packet loss rates or RoundTrip Times (RTT).We suggest a group based protocol which keeps a track of the various conditions experienced by
different users. Our study shows that performance of W-TFMCC is greater than UDP/TFRC/TFMCC if at least two
or more users are watching same channels. Performance of W-TFMCC is equal to TFRC/TFMCC when all users are
watching different channels.
1Initial results of this research appeared in
Saad Saleh, Zawar Shah, Adeel Baig, Capacity Analysis of Combined IPTV and VoIP Over IEEE 802.11n, In the IEEE Conference on
Local Computer Networks (LCN), Sydney, Australia, Oct. 2013.
Saad Saleh, Zawar Shah, Adeel Baig, IPTV Capacity Analysis using DCCP over IEEE 802.11n, In the IEEE proceedings of Vehicular
Technology Conference (VTC), Las Vegas, USA, Sep. 2013.
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Our contributions in this work are (i) Analytical and experimental evaluation of transport layer protocols UDP/TFRC
for transmission of combined IPTV and VoIP over IEEE 802.11n, (ii) Analytical and experimental investigation of
optimum physical layer parameters of combined IPTV and VoIP over IEEE 802.11n, (iii) Proposition of a new group-
based multicast protocol W-TFMCC with performance analysis over UDP/TFRC/TFMCC through simulations and
experiments.
The rest of the paper is organized as follows. Section-2presents the related work for IPTV and VoIP over WLANs.
Section-3presents the experimental scenario and data rate estimation for IPTV and VoIP. Section-4presents the IPTV
and VoIP capacity analysis over UDP and TFRC along with fairness analysis with TCP traffic. In section-5, we show
the optimal values of IEEE 802.11n analytically and experimentally. Section-6presents the performance improvement
using multicast mechanism and our proposed W-TFMCC protocol. Section-7presents the comparison of our results
with previous state of the art approaches. Section-8concludes the paper.
2. Related Work
Transmission of IPTV over Wireless Local Area Networks (WLANs) is a challenging task because of large packet
loss, large delay and minimum available bandwidth. A number of investigations have been made for availability ofwireless IPTV. In [5], authors evaluate the capacity trends of IPTV over IEEE 802.11b and IEEE 802.11g networks.
They conclude that IPTV users and WLAN data rate have non-linear relationship with each other. Their findings show
that IEEE 802.11b and IEEE 802.11g networks can support 2 and 6 IPTV streams respectively. In [6], authors apply
the fluid model flow analysis to determine IPTV capacity. They incorporate buffer size, network hops and show a
non-linear relationship between them for reliable QoS of IPTV. In [7], an experimental investigation has been made
to evaluate the capacity of IPTV over IEEE 802.11n WLAN. Their QoS findings show that outdoor environment
deteriorates IPTV performance significantly while indoor environment can support dozens of low resolution users
with reliable QoS. In [8], Kilik and Amadou implemented a practical test bed of IPTV to observe the behaviour of
various users in IPTV channel streaming. However, their research is not focused over the improvement in various
layers of IPTV but is limited to performance of current IPTV architecture. In another study [9], Piamrat et al. study
the transmission of IPTV over the wireless home network. Authors analyze the performance of IPTV over UDP
and TCP transport layer protocols as well as various MAC layer protocols. Authors propose a solution of combinedusage of TCP with a coordinated link layer protocol. In [10], Chaparro et al. evaluate the bandwidth requirements
for transmission of high quality television content. Authors show that granularity of the estimation can be utilized
efficiently for content generator to react to changes in utilization of the network.
VoIP has been a major focus of numerous studies owing to its high demand. In [11], authors evaluate the capacity
of VoIP using various codec and packetization intervals over IEEE 802.11b network. They show through simulations
that IEEE 802.11b WLAN can support 3 to 11 users depending upon the wireless channel loss conditions. In[12],
authors evaluate the capacity of VoIP along with tracking capacity over IEEE 802.11b/g WLAN. They show through
simulations and experiments that combined VoIP and tracking capacity is 30% less than VoIP only capacity at higher
packetization intervals. In [13], authors show through experimental setup that IEEE 802.11b WLAN can support
15 calls having a packetization interval of 20 ms. They prove their experimental results through simulations and
analytical work. Transmission of combined IPTV and VoIP introduces more challenges by incorporating different
delays and packet loss thresholds for different devices. In [14], authors study the transmission of combined IPTV and
VoIP over IEEE 802.11n with varying number of hops. Authors have shown that it is possible to run 3 IPTV streamsalong with VoIP connected for 2 hops only. They prove their findings through simulations and experiments and prove
that hop count is inversely related to capacity of IPTV and VoIP. Authors conclude that performance of IPTV and VoIP
is limited in IEEE 802.11b/g networks due to less throughput. Performance is expected to enhance in IEEE 802.11n
WLAN due to provision of high data rates.
Analytical model of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) has been developed in
[15]. Author develops a markov model to estimate the packet loss probabilities and estimates the throughput of IEEE
802.11b WLAN. Performance of IEEE 802.11n has been evaluated in [16]. Authors evaluate the MAC and PHY
layer mechanisms of VoIP and show that performance of IEEE 802.11n for VoIP is significantly enhanced. Frame
aggregation mechanism of IEEE 802.11n has been evaluated in [17]. Authors show that IEEE 802.11n can enhance
channel utilization upto 95% for UDP traffic by using frame aggregation mechanisms. They conclude that MAC
level aggregation is less effective than PHY layer aggregation. In [18], authors study the IEEE 802.11n mechanisms
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in comparison to the legacy frame protection mechanisms. They show that IEEE 802.11n has enhanced QoS as
compared to its predecessor standards.
Performance of DCCP for delay sensitive applications has been evaluated in [12]. Authors show that DCCP
adjusts its data rate continuously which results in a decrease in packet loss at the queues of AP. They show through
simulations that DCCP gives much more fair share in bandwidth to TCP traffic than UDP. Our previous studies [3]
and [4] show through simulations that TFRC can increase network capacity for IPTV and VoIP. Performance of
DCCP is limited because it provides unicast mechanisms. A number of investigations have been made to increase
efficiency by proposing multicast mechanisms. In [19], authors propose a DCCP enhancement, called Multi(Uni)
DCCP, which transmits its streams based upon the number of receivers in the network. Authors show that their
protocol can not only provide an increase in capacity but also decrease network congestion. In [20], authors propose
an improvement to currently developed protocol TFMCC by changing the data rate equations. Authors conclude that
incorporation of the uni-directional delay improves the performance of TFMCC. In [21], authors develop a framework
for multicast transmission of multimedia services through wireless networks. Authors show that their framework
increases efficiency with better QoS as compared to TFRC.
Comparison of various studies [5]-[21] show that capacity of IPTV and VoIP is limited over WLANs due to low
data rates of IEEE 802.11b/g. High data rates of IEEE 802.11n motivate the concept of wireless IPTV and VoIP overIEEE 802.11n. To the best of our knowledge, very limited studies exist on the performance of IPTV and VoIP over
IEEE 802.11n.
2.1. Transport Layer Protocols
A number of transport layer protocols exist which vary in their performance. Before probing into the performance
of IPTV and VoIP, we define various transport layer protocols used in this study.
2.1.1. User Datagram Protocol (UDP)
UDP provides a constant data rate with no handshaking dialogues and no guarantee of service, ordering or dupli-
cate protection. UDP has no congestion control mechanism with extensive voice and video applications along with
the use in Domain Name System (DNS) and Routing Information Protocol (RIP) etc.
2.1.2. Datagram Congestion Control Protocol (DCCP)
DCCP implements reliable connection setup, congestion control, explicit congestion notification, feature negoti-
ation and tear down. Provides flow based semantics similar to TCP but does not provide reliable in-order delivery.
DCCP has two variants TCP-like and TFRC. Applications of DCCP include internet telephony, online multiplayer
games and streaming media.
2.1.3. TCP Friendly Rate Control (TFRC) Protocol
TFRC provides a congestion control mechanism for unicast flows operating in the internet and competing fairly
with the TCP traffic. TFRC varies its data rate continuously based upon the network congestion, packet loss rate and
round trip time. Internet telephony and streaming media are the popular applications of TFRC.
2.1.4. TCP Friendly Multicast Congestion Control (TFMCC) ProtocolTFMCC provides an equation-based congestion control mechanism for multicast connections by extending the
TFRC protocol from unicast to multicast domain. TFMCC is most suitable for multicast applications demanding a
smooth rate including streaming media based applications.
3. Modelling of IPTV and VoIP over IEEE 802.11n
This section presents the modelling of IPTV and VoIP over IEEE 802.11n. Experimental setup for transmission
of IPTV and VoIP is discussed. Bandwidth estimations for IPTV and VoIP are also presented for simulations and
analytical evaluations.
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3.1. Network Scenario
We develop an analytical model and make experimental setup for performance of IPTV and VoIP over IEEE
802.11n. The analytical model assumesNnodes communicating with each other inside the wireless AP range asshown in Fig. 1. Model assumes that network nodes are lying inside the access point coverage area and all nodes
get small packet loss and RTT from AP. AP is connected to the internet which joins AP to the IPTV and VoIP
servers present on the opposite side of the internet. Matlab has been used to generate results of analytical model. All
simulations referenced from our previous study have been cited. For simulations, ns2 has been used as the simulation
tool 2 . Support of our patch [4]has been extended for simulations of IPTV and VoIP over IEEE 802.11n.
TV
TV
TV
TV
PC
TV
VoIP
VoIPVoIP
VoIP
VoIP
16'-0"*14'-0"
16'-0"*13'-0"
18'-0"*13'-0"
8'-0"*8'-0"
16'-0"*7'-0" 10'-0"*6'-0"
11'-0"*7'-0"
22'-0"*29'-0"
63'0"
40'0"
IEEE 802.11n WLAN
Laptop
TV
Figure 1: Network Scenario for IPTV and VoIP.
For experimental analysis, we setup an experimental test-bed. Distributed Internet Traffic Generator (DITG) ver-
2.8.1 is used to generate IPTV, VoIP and FTP packets from the application layer [22]. Sender and receiver devices
have DITG installed. Packet loss readings, RTT and delays are collected from the receiver devices. Data rate of
DITG is adjusted for the data rates of High Definition Television (HDTV) and Standard Definition Television (SDTV)
streams of IPTV. DITG can be tuned for DCCP and UDP streams. Results of DITG were validated with results of
previous studies [11]. IEEE 802.11n AP used for experiments has model no. AN102025 and name ADSL WirelessModem. Transmitter and receiver devices are connected to each other through the wireless AP. The experimental
setup developed is shown in Fig. 1. Various parameters, adopted from [16] used in simulations and experiments are
shown in Table-1.
3.2. Data rate estimation of IPTV and VoIP
IPTV requires a picture resolution which takes into account a number of factors including the pixel quality given
by luminance and chrominance. Luminance is the light intensity and chrominance is the colour depth. Moreover, a
moving picture is composed of a number of frames which move in series to make a moving picture. We take into
2S. McCanne and S. Floyd. ns Network Simulator. http://www.isi.edu/nsnam/ns
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Table 1: IEEE 802.11n Access Point Parameters.
Parameter Value Parameter Value
DIFS 34s SIFS 16sSlot time 9s Physical Header 20s
Contention Window (min) 15 TXOP limit 5
Channel Bandwidth 40 MHz Bit error rate 0.000008
account the frames per second effect for IPTV bandwidth estimation. Another important factor is the size of the video
resolution. Although a number of resolutions exist but there are two standard sizes used namely SDTV and HDTV
using 16:9 or 4:3 resolutions.
Compression schemes play an important role in estimating the amount of data to be transmitted through the net-
work. Moving Picture Expert Group (MPEG) has suggested a number of compression schemes and the most popular
schemes are MPEG-2 and MPEG-4. Studies have revealed that H.264 (MPEG-4) gives a much better compression
ratio than the currently used MPEG-2 standard[23]. Data rate requirement plays the most important role in evaluating
the capacity of IPTV for deploying in a given network. We evaluate the data rate by taking into account all the factors.The various factors used in the data rate calculation are shown in Table-2.Using all these factors the data rate required
in uncompressed form is given by Eq.(1).
D = RHRVCF (1)
HereRH is the horizontal resolution and RV is the vertical resolution for the picture resolution. C is the chromi-
nance factor andFis the intensity of frames per sec used for the pictures.
The data rate obtained without any compression scheme is high (797 Mbps) which is not achievable for wireless
environment. Performance of various compression schemes specially MPEG-2 and MPEG-4 motivates the use of
compression to raw data in order to decrease the data rate. Compression ratios of two popular schemes are given as
follows[23].
MPEG-2 and H.263 Compression ratio (Hcomp) = 30:1
MPEG-4 and H.264 Compression ratio (Hcomp) = 50:1
A group of picturesNgop is generated which is arranged in a certain priority given by I,P and B frames. The datarate equation after applying compression schemes is shown in Eq. (2).
D = RHRVCF Ngop/Hcomp (2)
Table-2presents the data rates required after applying compression schemes. It is worth mentioning that our data
rate calculation is with the latest standards (resolutions, compression schemes and frames per seconds etc.) which is
in accordance with the previous researches [5][6][7][9]. We used the standard IPTV packet size of 1366 bytes which
contains 1288 bytes of payload data [7]. On contrary to IPTV, VoIP requires less data rate. Data rate of VoIP depends
Table 2: Data Rate Requirement for various compression and resolution schemes.
TV F C Resolution Compression Required
(fps) RHRV Scheme Rate (Mbps)
SDTV 24 2 640 480 MPEG-2 3.93SDTV 24 2 640 480 MPEG-4 2.36
HDTV 24 3 1920 1080 MPEG-2 26
HDTV 24 3 1920 1080 MPEG-4 15.92
upon the packetization interval, amount of payload data and the transmission schemes G.711 and G.729 etc.3 For our
study, we use the popular VoIP codec G.711 (64 kbps) with a 10 ms codec sample interval.
IPTV requires a one-way delay constraint which is 50 msec [24]. On contrary, VoIP requires two-way delay
constraints which must be less than 150 msec for both directions [12]. IPTV cannot tolerate a packet loss greater than
1% while VoIP allows a packet loss upto 2%[24][12].
3Cisco, Voice Over IP - Per Call Bandwidth Consumption, available at http://www.cisco.com
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4. Optimal transport layer protocol for IPTV and VoIP
In this section, we investigate the optimal transport layer protocol for transmission of combined IPTV and VoIP
over IEEE 802.11n. Only simulations were performed in our previous studies [3]-[4]. In this section, we extend ouranalysis by conducting extensive experiments and analytical evaluations. Firstly, we investigate IPTV and VoIP with
UDP and TFRC for both applications. Secondly, we study the performance of TFRC based applications in presence
of UDP based applications. Lastly, we evaluate the performance of TFRC based applications in presence of non-real
time TCP traffic.
4.1. IPTV and VoIP capacity analysis over UDP and TFRC
In this subsection, we present the analytical framework for transmission of IPTV and VoIP over IEEE 802.11n.
Our analytical model estimates the packet loss probabilities, queue utilization ratio and expected CSMA/CA wait-off
time to estimate the throughput of IPTV and VoIP over IEEE 802.11n. As layers of computer network protocols are
independent of each other, so analytical modelling of physical layer does not change by incorporation of any other
protocol at transport layer of IPTV or VoIP. Our aim is to investigate the capacity of IPTV and VoIP over IEEE 802.11n
using UDP and TFRC at transport layer.Let traffic arrival rate be defined by Ai at any time instant i and frame service rate at queue of access point be
defined bySi at time instanti. Based upon the frame service rate and frame arrival rate, queue utilization ratioQi is
given by following Eq. (3).
Qi = Ai
Si(3)
Based upon Eq. (3), average queue utilization ratio Q for a period ofT time units is given by the average of
summation of queue sizes on every instant as shown in Eq. (4).
Q=
Ti=1QiTi=11
(4)
To determine the transmission rate, we evaluate the probability of successful transmission by station i. Let pibe the probability of successful transmission andj be the transmission probability of station i. Station i transmits
successfully if no other station is transmitting. Eq. (5) shows the probability of successful transmission.
pi =
N1j=0ji
(1 j) (5)
If station i is transmitting, a collision occurs if at least one of the remaining stations transmits. Let ci be the
collision probability of stationi. Conditional collision probability is given by Eq. (6).
ci =1
N1j=0ji
(1 j) (6)
ci =1 pi (7)
IEEE 802.11n uses Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). LetWibe the expected
wait-off time for any station i with C Wj as contention window size and pi as the collision probability with Ai as
expected number of transmission attempts. Let m be the retry limit. Average wait-offtime E[Wi] and average trans-
mission attemptsE[Ai] are given by Eq. (8)and Eq. (9), respectively[15]. It is worth mentioning thatCWjrepresents
the size of the contention window while p irepresents the collision probability.
E[Wi]=
m1k=0
pik(1 pi)
kj=0
CWj
2 + pi
m
mj=0
CWj
2 (8)
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E[Ai]=
m1
k=0
pik(1 pi)(k+ 1) +pi
m(m + 1) (9)
Based on the expected wait offtime and expected number of transmission attempts, transmission probability Tiis
given by Eq. (10).
Ti = E[Ai]
E[Wi] +E[Ai] (10)
IEEE 802.11n transmits frame on the physical layer level which can be modelled by incorporating SIFS, DIFS,
frame transmission time and acknowledgement time. Let Ts be the time taken by a frame if it is transmitted success-
fully. LetTc be the time if a frame is not transmitted successfully. Ts andTc can be modelled by viewing the frame
transmission timeTf rame,S I F S ,Tackand DIFSas given in Eq.(11) and Eq. (12).
Ts =Tf rame+ S I F S + Tack+ DI FS (11)
Tc =Tf rame+ Tacktimeout (12)
Also, collision time is a function of collision probability to success probability. Based on [15], average collision
timeTavg(c) can be derived from the packet loss probability p iand packet collision timeTc as shown in Eq. (13).
Tavg(c)= pi
1 piTc (13)
Eq. (3)-Eq. (13)are used to evaluate the throughput using collision time and transmission probability. Analytical
results for capacity of IPTV and VoIP using UDP are shown in Table-3.Results show that IPTV and VoIP users have
an inverse relationship with each other. This behaviour shows that IPTV users occupy majority share in bandwidth
which reduces share for VoIP users. Network congestion also increases with large number of IPTV users which
increases delay for further VoIP users. Similar trends are observed experimentally for IPTV and VoIP users. Resultsfrom Table-3show that 4 IPTV users can be accommodated with 1 VoIP user maximally. All of our results represent
the steady state conditions where throughput of all supportable IPTV and VoIP streams is at saturation level. It is
important to mention that all of our simulation, experimental and analytical results differ by a small amount based
upon the following reasons.
Analytical results show maximum capacity because all analytical results present a mean estimate of capacity of
IPTV and VoIP users based upon their bandwidth requirements in wireless medium.
Simulations present an estimate of users obtained by simulating the environment in ns2. Collisions at a partic-
ular instant decrease the capacity in simulations.
Experimental results show minimum capacity because of the particular environment e.g. room walls, obstacles,
transmitting device location and receiving device location and reception system etc deteriorate the capacity
from the ideal analytical capacity.
Table 3: IPTV and VoIP capacity over IEEE 802.11n using UDP.
Simulation Analytical Experimental
IPTV VoIP IPTV VoIP IPTV VoIP
1 36 1 39 1 32
2 24 2 28 2 21
3 11 3 14 3 8
4 2 4 6 4 1
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IPTV using UDP encounters packet loss at the AP because UDP is a constant bit rate protocol and packets drop from
queues of AP. UDP cannot cope fairly with the network congestion and maintains its data rate at any situation. To
resolve congestion less mechanism of UDP, DCCP has been proposed. DCCP has two variants namely TCP-like and
TFRC.
TCP-like uses the congestion control mechanism similar to TCP. TCP-like has no retransmissions. TCP-like
applies congestion control to acknowledgements, it works on units of packets instead of bytes and TCP-like uses no
retransmissions. These features make it different from TCP but in reliability it resembles TCP because it decreases its
data rate much more sharply in congested situations similar to TCP.
We have shown previously that TCP-like gives poor performance for IPTV and VoIP because TCP-like decreases
its data rate in congested situations. Decrease in data rate increases the delay for all packets reaching the receiver end.
IPTV is a real time service with limitations of packet loss and delay. Large delay disrupts the support for many users.
On contrary to TCP-like, TFRC is the protocol which resembles UDP in some aspects like no retransmissions
and less reliability etc. Instead of constant bit rate, TFRC adjusts its data rate continuously according to the packet
loss rate and RTT experienced at the user end. Any increase in packet loss or RTT implies network congestion which
results in throughput reduction of TFRC. TFRC increases its data rate in low packet loss and RTT conditions.
Lets, p,R and tRTO be the segment size, packet loss rate, round trip time and TCP retransmission timeout value,respectively. Let b be the packets acknowledged by a single TCP acknowledgement. Using above parameters, through-
put of TFRC is modelled by the Eq. (14). It is pertinent to mention that we define throughput as the physical layer
data rate sent by the transmitter on the physical link. Throughout this paper, we add the various standard header fields
into the transport layer header to estimate the physical layer throughput.
X= s
R
2bp
3 + tRTO 3
3bp
8 p(1 + 32p2)
(14)
Analytical results of throughput for a range of packet loss probabilities and RTT are shown in Fig. 2. RTT trends
show that RTT is inversely related to the data rate. Packet loss trends show that packet loss is inversely related to the
throughput governed by TFRC. Moreover, trends of TFRC are more drastic for change in packet loss than change in
RTT.
0.04 0.045 0.05 0.055
5
5.5
6
6.5
7
7.5
x 107
Round Trip Time (RTT) (ms)
Throughput(bps)
0.5 1 1.5 2
x 104
2
3
4
5
6
7
8
x 107
Packet Loss Probability (p)
Throughput(bps)
p=0.000021
p=0.000023
p=0.000019
RTT=41ms
RTT=45ms
RTT=49ms
Figure 2: TFRC round trip time and packet loss probability versus throughput
Table-4shows the capacity of IPTV and VoIP over IEEE 802.11n using TFRC for both applications. Results show
that TFRC can accommodate more IPTV users than UDP. TFRC adjusts its data rate by decreasing its data rate in
congested situations. Coping with the network situations makes TFRC a better suitable candidate for transmission of
IPTV and VoIP with increased capacity. Analytical and experimental results show that IPTV and VoIP with TFRC
can accommodate at least 5 IPTV users with 0 VoIP users. This suggests that TFRC provides 1 more HDTV user than
UDP. Comparison of Table-3and Table-4shows that UDP and TFRC provide same VoIP capacity for small number
of IPTV users. On contrary, large number of IPTV users can be accommodated with the use of TFRC. This suggests
that TFRC is more suitable for IPTV than VoIP. VoIP has small packet size with different packetization interval than
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IPTV. This suggests that VoIP suits well to UDP than TFRC. In next subsection, we aim to figure out IPTV and VoIP
running different protocols either UDP or TFRC.
Table 4: IPTV and VoIP capacity over IEEE 802.11n using TFRC.
Simulation Analytical Experimental
IPTV VoIP IPTV VoIP IPTV VoIP
1 35 1 39 1 32
2 22 2 26 2 20
3 11 3 17 3 8
4 2 4 6 4 1
5 1 5 4 5 0
4.2. Cross-protocol performance of IPTV and VoIP using UDP and TFRC
In this section, we analyze the performance of IPTV and VoIP over the protocols UDP and TFRC. Based on thecurrent network architecture, both IPTV and VoIP use UDP at the transport layer. Aim of this section is to investigate:
How about changing only IPTV or VoIP transport layer protocol without influencing other network traffic?
We evaluate the performance of TFRC based IPTV in presence of UDP based VoIP. UDP is a constant bit rate
protocol. Available capacity in network decreases with UDP because TFRC decreases its data rate based on the
increase in packet loss rate and RTT. On contrary, UDP keeps sending packets with constant bit rate. Our analysis
shows that data rate of TFRC is highly dependent upon the bit rate of UDP. To increase the TFRC based IPTV
connections, UDP connections must be reduced. A comparison of analytical and experimental performance versus
simulation results is shown in Table-5.
Table 5: IPTV(TFRC) and VoIP(UDP) capacity over IEEE 802.11n using TFRC.
Simulation Analytical Experimental
IPTV VoIP IPTV VoIP IPTV VoIP1 7 1 9 1 5
2 5 2 6 2 4
3 3 3 4 3 1
4 0 4 2 4 0
Similarly, we evaluate the performance of UDP based IPTV with TFRC based VoIP. Table-6shows the analytical
and experimental results versus simulation results. Results show that TFRC follows same trends in presence of UDP.
Number of UDP connections must be reduced in order to avoid network congestion. Results show UDP and TFRC
cannot co-exist fairly with each other because UDP occupies all the network bandwidth irrespective of the packet loss
and delay encountered by the system.
Table 6: IPTV(UDP) and VoIP(TFRC) capacity over IEEE 802.11n
Simulation Analytical Experimental
IPTV VoIP IPTV VoIP IPTV VoIP
1 8 1 10 1 6
2 6 2 7 2 4
3 4 3 5 3 3
4 1 4 2 4 0
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4.3. Fairness Analysis of IPTV and VoIP with TCP traffic
Studies show that 80% of network traffic is non-real time traffic[12]. This suggests that fairness of IPTV and VoIP
traffic must be studied with Transmission Control Protocol (TCP) traffic in the network. To implement TCP traffic,we use a packet size of 1000 bytes with File Transfer Protocol (FTP) at application layer. TCP is used at the transport
layer of FTP which makes FTP a suitable candidate to test non-real time reliable traffic. Multiple TCP connections
are established because probability of achieving minimum window size is highest with a single TCP source.
Capacity and fairness results from analytical and experimental evaluations of IPTV and VoIP traffic using UDP
with FTP traffic are shown in Table-7. Results show that TCP decreases its window size in presence of constant bit
rate protocol UDP. This suggests that UDP provides not only less capacity but also provides unfair share in bandwidth
to TCP traffic in the network.
We test the performance of IPTV and VoIP using TFRC with FTP traffic in the network as shown in Table-7.
Results show that TCP competes fairly with TFRC traffic in the network. Bandwidth analysis shows that TFRC
provides more share in bandwidth to TCP traffic than UDP. TCP gets 4.3 Mbps throughput in presence of UDP while
11.5 Mbps throughput in presence of TFRC experimentally. Comparable performance gains with similar trends are
observed for both SDTV and HDTV. TFRC provides at least 167.4% more throughput to TCP than UDP.
Our study over various transport layer protocols suggests that TFRC provides better capacity than UDP for trans-mission of IPTV and VoIP over IEEE 802.11n. TFRC adjusts its data rate according to the network conditions which
makes it a better candidate for IPTV and VoIP. Our investigation suggests that TFRC must be adopted for all real time
applications. Performance of TFRC deteriorates severely in presence of UDP due to congestion less mechanism of
UDP. TFRC provides much more fair share in bandwidth to TCP than UDP. In the next section, we aim to investigate
the optimum physical layer parameters for combined IPTV and VoIP over IEEE 802.11n.
Table 7: PERFORMANCE STATISTICS FOR COMBINED IPTV AND VoIP ALONG WITH TCP TRAFFIC
IPTV Combined Average Throughput (Mbps)
Flows Simulation Analytical Experimental
HDTV UDP- UDP: 50.7 UDP: 51 UDP: 47.2
TCP TCP: 6.8 TCP: 7 TCP: 4.3
HDTV TFRC- TFRC: 66.5 TFRC: 68.2 TFRC:62.3TCP TCP: 14.2 TCP: 16.3 TCP: 11.5
SDTV UDP- UDP: 51.3 UDP: 52.9 UDP: 48.4
TCP TCP: 6.1 TCP: 8.4 TCP: 4.2
SDTV TFRC- TFRC:64.7 TFRC: 67.3 TFRC:61.2
TCP TCP: 14.4 TCP: 16.2 TCP: 12.3
5. Optimal Physical layer parameters of IEEE 802.11n for IPTV and VoIP
IEEE 802.11n is equipped with a number of parameters and enhanced features including queue size, SIFS, DIFS,
contention window size and physical layer header time. Simulation results of our previous investigations [3]-[4] for
transmission of IPTV and VoIP are shown in Table-8. In this section we present the analytical and experimentalevaluation of all the parameters.
Table 8: Parameters for IEEE 802.11n
Parameters Default Parameters Proposed Parameters [4]
Queue Size 50 pkts 70 pkts
SIFS 16s 14.4s
DIFS 34s 30.6s
Physical Header 20s 18s
Contention Window 15 11
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5.1. Trends of SIFS, DIFS and Physical header
Layers of computer network protocols are independent of each other. So, all layers can be modelled independently.
Parameters like SIFS, DIFS, contention window and physical header time belong to the physical layer. It means thatany change in physical layer parameters needs to be modelled at only physical layer level.
Let TS I F S be the time duration required to wait for SIFS time, TDIF Sbe the time duration required to wait for
DIFS time,TPHYbe the time duration required for physical header transmission and Tpayloadbe the time required to
transmit payload data. Various time periods as observed at the physical layer are shown in Table-1. Throughput at
physical layer given byXcan be modelled by Eq. (15) assuming RTS/CTS is disabled. Eq. (16)shows the throughput
equation if RTS/CTS is enabled.
X= s
TS I F S + TDIF S+ Tpayload+ Theader+ Tack(15)
X= s
3TS I F S + TDIF S+ Tpayload+ Theader+ Tack(16)
Using default values of all time periods, various parameters are varied in Eq. (15) and Eq. (16). Fig. 3shows theresults of simulations and analytical observations by varying various parameters. Results show that SIFS and DIFS
are inversely proportional to the throughput. Moreover, SIFS has more drastic effect on throughput than DIFS because
SIFS is encountered more than DIFS. SIFS and DIFS have no optimal values but DIFS must have the value given by
Eq. (17). TProptime is the propagation of a packet from AP to user.
TDIF S =2TS I F S + TProptime (17)
0 1 2 3
x 105
0.5
1
1.5
2
x 108
SIFS (s)
Throughput(bps)
SIFS behaviour
2 3 4 5
x 105
4
5
6
7
8
9x 10
7 DIFS behaviour
DIFS (s)
Throughput(bps)
RTS/CTS disabled
RTS/CTS enabled
RTS/CTS enabled
RTS/CTS disabled
Figure 3: Trends SIFS and DIFS with RTS/CTS enabled and disabled.
If DIFS is less than SIFS then throughput would be zero effectively because all stations would transmit when any
station is waiting for SIFS. This results in wastage of capacity in form of collisions. Trends of physical header timewith RTS/CTS enabled and disabled are shown in Fig. 4. Decrease in physical header time provides more throughput
because remaining time is used for payload transmission. We suggest a decrease of only 10% which changes physical
header time to 18s. Large change in physical header is not possible due to small clocking frequency of devices.
Results show that decrease in time durations of physical layer parameters gives more time for data transmission.
We suggest a decrease of only 10% in physical header duration which can increase capacity by at least 1 VoIP user.
Our previous simulations [4]also proposed 10% decrease in parameters through simulations only. Large decrease in
physical layer parameters is not possible due to limitation of physical devices.
5.2. Trends of Contention Window
Contention window represents the physical layer waiting time encountered in CSMA/CA which tries to avoid
collisions and also tries its best to minimize the redundant waiting time. Our previous study [4] has shown through
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1 1.5 2 2.5 3 3.5
x 105
6
7
8
9
10
11x 10
7
Physical header time (s)
Throughput(bps)
RTS/CTS enables
RTS/CTS disabled
Figure 4: Trends Physical header time with RTS/CTS enabled and disabled.
simulations that contention window size of 11 is the optimal size instead of 15. Large packet size is the major cause
for small contention window size. IPTV has got a large data rate requirement but the packet size is 1366 bytes. Large
data rate limits the support for large number of IPTV users. This suggests that only few IPTV users are competing
with each other at any particular instant. Few competing users can accommodate in a situation of small window size
as compared to large window size. Large contention window size results in redundant waiting times of all users which
decreases throughput and capacity.
Considering the CSMA/CA backoffmechanism, various transmission probabilities have been shown in [15]. An-
alytical results for IPTV and VoIP from CSMA/CA equations are shown in Fig. 5. Trends show that throughput
increases upto a contention window size of 11. This behaviour suggests that small contention window size results
in collision of packets between various users. Beyond contention window size of 11, throughput decreases. This
suggests that large contention window size results in redundant waiting time of stations which decreases throughput
slightly. Our analytical and simulation results confirm that contention window size of 11 is the optimal size. Results
suggest that only optimal contention window size should be used for practical applications running IPTV and VoIP.
Moreover, for large scenarios, contention window size can be estimated practically by computing the throughput ob-tained by all devices at varying contention window sizes. Contention window size providing maximum throughput
is the optimal size for that particular configuration of various devices. It is pertinent to mention that slight tuning of
contention window is required for applications running TCP traffic simultaneously with IPTV and VoIP traffic based
upon the number of competing devices.
0 5 10 150
10
20
30
40
50
60
70
Contention Window (CW)
Throughput(Mbps)
Analytical
Simulation
Figure 5: Contention window trends for IPTV and VoIP.
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5.3. Trends of Queue Size
Queue size represents the physical layer buffering capacity for the wireless AP. Queue size for IPTV and VoIP
over IEEE 802.11n can be modelled through queue utilization ratio. Let traffic arrival rate be Aiand departure rate beDi, then queue utilization ratio is given by eq (18).
= ArrivalRate
DepartureRate=
Ai
Di(18)
Actual queue size for any system is a function of the queue utilization ratio. Queue utilization ratio of less than 1
indicates small arrival rate as compared to serving rate. On contrary, queue utilization ratio greater than 1 indicates
less serving rate than the utilization rate. Queue size, given by B, can be represented as a function of queue utilization
ratio by Eq. (19).
P(QueueS ize= B) = 1
1 B1B (19)
Eq. (19) can be simplified arithmetically into Eq. (20).
B = 1
1 + P(20)
Queue size depends upon the traffic arrival rate. This suggests that it needs to be modelled with different traffic
categories. Traffic arrival rate of TCP and TCP-like resembles Additive Increase and Multiplicative Decrease (AIMD)
model. A simplified model for estimating TCP rate is given by Eq. (21).
R= 1
RT T
3
2P(21)
Traffic arrival rate of TFRC is modelled by the TFRC rate equation. Eq. (22)shows the rate equation of TFRC.
X=
s
R
2bp
3 + tRTO 3
3bp
8 p(1 + 32p2)
(22)
Our analysis shows that the bottleneck link in IPTV transmission is the wireless AP. TFRC increases its data rate
until it gets some packet loss or increased RTT from the AP. On contrary to TFRC, UDP is a congestion-less protocol
which provides constant bit rate. Fixed data rate of UDP provides a fixed arrival rate at the queues of AP and queue
size depends upon the transmission rate from queues of AP to the wireless user.
To model the queue size of UDP, we use a constant bit rate model having uniform distribution. IEEE 802.11n
provides a theoretical data rate of 600 Mbps while a practical data rate of 300 Mbps at physical layer level using 33
MIMO technology.
Fig. 6presents the analytical and experimental results for optimal queue size of IPTV and VoIP for transmission
over IEEE 802.11n. Results show that initially queue size increases throughput sharply. After 100 packets, increase in
throughput is nearly negligible. Results show that maximum capacity is obtained at a queue size of 70 packets. Very
large queue size results only in wastage of resources because wireless channel becomes the bottleneck link for largequeue size. Experimental results show less throughput than analytical because of varying network conditions and large
packet loss in a real network scenario. Delay is maximum for experimental results because of the wireless conditions.
Analytical results display minimum delay because they incorporate limited network conditions. Simulation results
display delay and throughput in between experimental and analytical.
5.4. Trends of Aggregation
IEEE 802.11n is equipped with the aggregation mechanisms which use aggregation at two levels. At level 1,
multiple MAC layer frames called MAC Service Data Units (MSDUs) are aggregated together to form an Aggregated
MAC Service Data Unit (A-MSDU). At level 2, multiple physical layer frames composed of physical layer header
and A-MSDUs are aggregated together to transmit an Aggregated MAC Physical Data Unit (A-MPDU).
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0 200 40010
20
30
40
50
60
70
Queue Size (Pkts)
Throughput(Mbps)
Analytical
Simulation
Experimental
0 200 40038
40
42
44
46
48
50
52
Queue Size (Pkts)
Delay(msec)
Analytical
Simulation
Experimental
Figure 6: Queue size trends for IPTV and VoIP.
LetTMPDUbe the transmission time of a single MPDU and Nbe the number of MPDUs inside a single A-MPDU.
LetTS I F S andTDIF Sbe the time required to wait for SIFS and DIFS before transmission. Then transmission time T
of an MPDU (without aggregation) is given by Eq. (23). Eq. (24) represents the transmission time TAMPDUwith an
aggregation ofNMPDUs inside a single A-MPDU.
T=TDIF S+ TMPDU+ TS I F S + TACK (23)
TAMPDU=TDIF S+ NTMPDU+ TS I F S + TACK (24)
Fig. 7shows the aggregation performance of IPTV and VoIP over IEEE 802.11n. Results show that capacity in-
creases upto 4 times aggregation due to reduction in collision time and header overhead. Beyond 4-times aggregation,
large delay disrupts the support for large number of users.
2 4 6 8
20
25
30
35
40
45
50
55
60
65
70
Aggregation (Pkts)
Throughput(Mbps)
Analytical
Simulation
Experimental
2 4 6 8
40
45
50
55
60
65
70
75
80
85
90
Aggregation (Pkts)
Delay(msec)
Analytical
Simulation
Experimental
Figure 7: Aggregation trends for IPTV and VoIP.
Comparison of physical layer parameters for IPTV and VoIP over IEEE 802.11n shows that maximum capacity
can be achieved at optimal values of all the parameters. Table-9presents the comparison of optimal parameters of
IPTV and VoIP over IEEE 802.11n. As layers are independent so changes in physical layer parameters do not affect
transport layer protocol. Optimal parameters remain same with the use of UDP or TFRC. SIFS, DIFS and physical
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header have no optimal values because decrease in physical layer parameters gives more time for payload data to
transmit. This shows that SIFS, DIFS and physical header duration must be reduced as much as possible. We suggest
a decrease of 10% in these parameters which can increase capacity by at least 1 VoIP user without effecting current
network.
Table 9: Optimal Parameters of IEEE 802.11n
Parameters Standard Values Simulations [4] Analytical Experimental
Queue Size 50 pkts 70 pkts 75 pkts 80 pkts
Aggregation 1 pkt 4 pkts 4 pkts 4 pkts
Contention Window 15 11 11 11
6. Improving performance through multicast mechanism
In this section, we aim to analyse and improve the performance of combined IPTV and VoIP over IEEE 802.11n.In this regard, we present the limitations of current IPTV architecture using TFRC. We analyse the performance of
IPTV in presence of VoIP using multicast TFMCC protocol. Finally, we present our proposed protocol W-TFMCC
by mitigating the limitations of all previous protocols. We present the performance of W-TFMCC with a test run real
network scenario and explain its performance gains.
6.1. Using Multicast for IPTV transmission
Studies reveal that capacity of IPTV is dependent upon the channel popularity [25]. Zipfs law states that the
channel viewership ofxth channel would be x-times less than the first channel [25]. Fig. 8shows the histograms of
channel viewership versus channel popularity.
2 4 6 8 10 12 14 16 18 200
0.05
0.1
0.15
0.2
0.25
Channels Popularity
Viewership
Figure 8: Channel viewership with popularity (Zipfs Law)
Trends of histogram show that channel viewership decreases exponentially as its popularity decreases. So, unicast
mechanism for transmission of IPTV results in wastage of capacity. Our results for IPTV capacity using UDP and
TFRC show that multiple receptions of same channel require multiple transmissions. This suggests that multicast
transmissions must be used for all users viewing same channel. TFRC and TCP-like employ unicast mechanism to
observe the packet loss and RTT of the receiver. Our study shows that congestion control mechanism of TFRC can
enhance capacity of IPTV. For multicast mechanisms, TCP Friendly Multicast Congestion Control Protocol (TFMCC)
has been designed which has congestion control mechanisms similar to TFRC. TFMCC selects the worst case receiver
based on the packet loss rate and makes all transmissions based on the worst case receiver. It was believed in TFMCC
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that all receivers would get the reception if the worst case receiver gets the reception. Our analysis shows that per-
formance of TFMCC is limited in wireless medium. In wireless medium, TFMCC selects the worst case receiver and
adjusts its data rate according to the packet loss rate and RTT experienced by the worst case receiver. This suggests
that any user experiencing worst-case receiver conditions deteriorates the performance of all other users viewing same
channel. Fig. 9presents the scenario in which few IPTV users lie inside first range of AP having small packet losses
while other users lying outside first range experiencing large packet loss conditions.
Figure 9: Network Scenario for IPTV and VoIP.
In this paper, we propose wireless enhancement of TCP Friendly Multicast Congestion Control Protocol (W-
TFMCC). Basic idea of W-TFMCC is to limit the capacity of only those users experiencing worst case conditions.
Throughput of all users lying in better environment must not be deteriorated. W-TFMCC estimates the packet loss
rate of all users lying in its range and makes an estimate of all users which can be provided with a reliable QoS either
HDTV streams or SDTV streams. We show that capacity of W-TFMCC provides 61% coverage area in comparison to
TFMCC and TFRC providing only 30% and 5% coverage areas respectively. Moreover, W-TFMCC results not only
in an increase in capacity but also saves resources by avoiding any redundant transmissions of channels which makes
it more efficient.
6.2. TFMCC for IPTV transmission
TFMCC is a single rate multicast congestion control protocol. It competes fairly with TCP traffic in the network
because it uses congestion control mechanism similar to TFRC. TFMCC uses the packet loss rate of the receivers
to determine the sending rate continuously. TFMCC protocol uses an equation to determine the sending rate contin-uously. Let p be the packet loss rate and s be the segment size, then TFMCC throughput X is given by Eq. (25).
X= 8s
R
2p
3 + 12
3p
8 p(1 + 32p2)
(25)
Simulations for TFMCC are performed over ns2 by extending support of [4] for IPTV and VoIP over IEEE
802.11n. Performance of TFMCC has been tested in varying environments as shown in Table-10. Different regions
have different range of packet loss and RTT. Our results for performance analysis of TFMCC over IEEE 802.11n
for transmission of IPTV and VoIP are shown in Table-11. Coverage area shows the percentage of supported users
according to Zipfs law. Results show that TFMCC gives a high coverage area 61.65% in Terrain-A with ideal con-
ditions. However, coverage area reduces to 30% in worst conditions which suggests that only 30 users are supported
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out of 100 (approximately for a certain bandwidth). Performance of TFMCC is worst in varying network conditions.
TFMCC gives increased performance over IEEE 802.11n in reliable network conditions where all users have limited
packet loss and RTT. Performance of TFMCC deteriorates in large packet loss and RTT conditions. Different users
lying in different conditions demanding same channel get worst QoS because TFMCC selects worst case receiver.
This necessitates the demand of W-TFMCC to provide better QoS to all users.
Table 10: Terrains for IPTV and VoIP over IEEE 802.11n.
Terrain Environment
Type-A HDTV Support : Low Packet Loss & Low RTT
Type-B HDTV Support : Low Packet Loss & Large RTT
Type-C SDTV Support : Large Packet Loss & Low RTT
Type-D SDTV Support : Large Packet Loss & Large RTT
Type-E SDTV Support : Very Large Packet Loss & RTT
Table 11: IPTV and VoIP capacity over IEEE 802.11n using TFRC and TFMCC respectively.
Terrain TFRC TFMCC Coverage
Type Simulation Simulation Analytical Experimental %
TV VoIP TV VoIP TV VoIP TV VoIP
A 5 1 1 35 1 39 1 32 61.65
B 4 15 1 33 1 37 1 29 54
C 4 8 1 25 1 29 1 23 49
D 4 3 1 14 1 19 1 12 44
E 3 5 1 6 1 9 1 4 30
6.3. Wireless Enhancement of TFMCC (W-TFMCC)
Our proposed protocol W-TFMCC is an enhancement of current protocol TFMCC. Basic limitation in current
mechanism arises from the varying channel conditions in wireless environment.
TFMCC transmits all streams using a single multicast transmission depending upon the worst case user reception.
Transmissions to worst case user deteriorate the data rate and effectively throughput is worstly effected for all users.
On contrary, W-TFMCC selects the worst case user depending upon the packet loss conditions and RTT experienced
by worst case user. If HDTV throughput is not possible for any user then W-TFMCC transmits a separate channel
group for users having large packet loss.
Based upon our previous investigations on TFRC, we prefer the same data rate equation of TFRC to be used for
W-TFMCC, as shown in Eq. (26).
X= 8s
R2p3 + 123p
8 p(1 + 32p2)
(26)
If packet loss or RTT or both parameters increase beyond a limit then W-TFMCC separates those users from
current multicast transmission. Fig. 10presents the scenarios of wireless environment with varying loss and RTT
conditions. Limits of packet loss and RTT for provision of HDTV and SDTV streams with reliable QoS are marked
in the figure.
Our simulation and analytical results for W-TFMCC performance in comparison to TFRC are shown in Table-12.
Results show that performance of TFRC deteriorates in worst conditions because supported users are limited. On
contrary, W-TFMCC transmits streams to group of users. For ideal channel conditions, like Terrain-A, W-TFMCC
transmits only 1 stream instead of 5 for 5 users watching same channel. To estimate the performance of W-TFMCC,
we use the users distribution as given by Zipf s law. Considering a set of 20 channels, probability of watching first five
channels is the sum of individual channels probabilities. To support 5 users watching same channel, TFRC transmits
5 streams. On contrary W-TFMCC transmits only 1 stream for 5 users watching same channel. Using Zipfs law,
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0 0.002 0.004 0.006 0.008 0.010
0.05
0.1
0.15
0.2
0.25
Packet Loss Probability
RoundTripTime(s)
HDTV
SDTV
Figure 10: Packet loss and RTT limits for SDTV and HDTV channels.
coverage area of W-TFMCC appear to be 61.65%. This suggests that 61 IPTV users can be supported out of 100 users
which is a remarkable gain. In worst terrains, coverage area decreases to 56.25% users because SDTV and HDTV
streams have to be transmitted simultaneously to support different group of users watching same channel. Results
show that W-TFMCC transforms the concept of capacity from number of users to number of channel streams. In case
of excess packet loss and RTT, W-TFMCC stops transmissions until it finds the ideal situation for SDTV or HDTV
transmissions. Capacity of W-TFMCC is always greater or equal to TFRC and TFMCC. Worst case of W-TFMCC
can occur if all users are present in different conditions and viewing different channels. In such a situation, W-TFMCC
would converge to unicast mechanism. This suggests that W-TFMCC can perform better in all environments. Fig.
11 presents the coverage comparison for 100 users using UDP/TFRC/TFMCC/W-TFMCC. Results show that W-
TFMCC performs best in worst terrains. Large number of users can be supported easily using W-TFMCC. Advantagegain increases with more users in comparison to TFRC.
Table 12: IPTV and VoIP capacity over IEEE 802.11n using TFRC and W-TFMCC respectively.
Terrain TFRC W-TFMCC Coverage
Type Simulation Simulation Analytical Experimental %
TV VoIP TV VoIP TV VoIP TV VoIP
A 5 1 1 35 1 39 1 32 61.65
B 4 15 2 30 2 34 2 26 61.65
C 4 8 2 22 2 26 2 20 61.65
D 4 3 2 12 2 18 2 15 58.7
E 3 5 2 3 2 7 2 6 56.25
Algorithm-1presents the pseudocode for performance of W-TFMCC. Xrepresents the throughput which is esti-
mated using the RTT and packet loss probability. XhdandXsddenote the reference throughputs required to transmit
HDTV and SDTV streams respectively as given by Table-2. Repeated measurements are performed after every finite
amount of time. Sampling time must be as small as possible to detect the continuously varying wireless conditions.
Users groups are formed based upon RTT and packet loss probability.
6.4. Test Run for W-TFMCC
Performance of W-TFMCC can be analysed with a test run having challenging wireless conditions. It is pertinent
to mention that Fig.12presents a real home network scenario. Wireless AP is located in one room depending upon the
available sockets and users convenience. There are four regions depending upon the signal strength in various regions.
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0
10
20
30
40
50
60
70
A B C D E
Coverage(%)
Terrain Type
UDP
TFRC
TFMCC
W-TFMCC
Figure 11: Coverage comparison of UDP/TFRC/TFMCC/W-TFMCC
Algorithm 1:W-TFMCC Protocol
1 pusr(i) ; /* Packet loss probability of user i */2 RT T(i) ; /* RTT of user i */
3 HDch=[ ] ; /* Transmitted HDTV channels list */
4 S Dch=[ ] ; /* Transmitted SDTV channels list */
5 HD(i) ; /* HDTV channel for user i */
6 S D(i) ; /* SDTV channel for user i */
7 X(i)= s
R
2bp
3 +tRTO 3
3bp
8 p(1+32p2)
;
8 ifX(i)> Xhdthen
9 HDch = [HDch H D(i)] ; /* Start HDTV transmission for i */
10 else ifX(i)> Xsdthen
11 S Dch = [S Dch S D(i)] ; /* Start SD transmission for i */
12 else
13 HDch = H Dch - pusr(i) ; /* Remove user from channel list */14 S Dch = S Dch - pusr(i);
15 end
Various regions have been marked with different patterns. We analyse the performance of all protocols in the given
test run environment. Depending upon the packet loss and RTT, our experimental receiver device splits coverage into
four different regions from Level-1 to Level-4. We consider users demand in each region such that Level-1 region
demands an HDTV and a FTP device (computer). There are three regions (rooms) having Level-2 coverage. Level-2
demands two HDTV, three VoIP phones and an FTP device (laptop). Level-3 region demands two HDTV and one
VoIP phone. Level-4 coverage area has a single HDTV demand.
UDP and TFRC use unicast transmission mechanisms. Demand of each user is fulfilled by individual and unique
transmission with UDP/TFRC. Our investigation reveals that 4 IPTV users can work using UDP while 5 HDTVdevices can work with TFRC. Unicast transmissions of UDP/TFRC are independent of each other. All users are
supplied with individual streams even if all users are viewing same channel. This suggests that UDP and TFRC waste
significant resources because of unicast mechanism.
TFMCC uses the multicast mechanism by supplying single channel stream to all users viewing same channel.
Major limitation of TFMCC arises when user in level-4 and level-1 are viewing same channel. TFMCC selects the
level-4 user because it is in worst condition as compared to user in level-1 region. All transmissions are performed
according to level-4 user. As a result, users lying in level-1 suffer poor image quality because TFMCC adjusts its
data rate according to level-4 user. Worst conditions of level-4 user deteriorate the performance of level-1 user who is
unable to watch HDTV stream.
Our proposed protocol W-TFMCC gives best performance in this environment. Packet loss and RTT of users
lying in level-1 and level-4 regions watching same channel is identified. If packet loss and RTT of level-4 user is
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greater than the possible limit for HDTV stream then level-4 user is supplied with an SDTV stream. Enhanced group-
based mechanism has sorted the problem of level-1 user by supplying it with an HDTV stream. Channels of all users
lying in different regions are identified with W-TFMCC. Packet loss and RTT of all users watching same channel are
identified. Various channel streams are supplied to different groups based upon their environment conditions. Worst
case of W-TFMCC is the scenario in which all users are lying in different conditions and watching different channels.
In such a case, performance of W-TFMCC would be similar to TFRC because it would use unicast streams for all
viewers.
TV
TV
TV
TV
PC
TV
VoIP
VoIP
VoIP
VoIP
16'-0"*14'-0"
16'-0"*13'-0"
18'-0"*13'-0"
16'-0"*7'-0" 10'-0"*6'-0"
11'-0"*7'-0"
22'-0"*29'-0"
63'0"
40'0"
WLAN
COVERAGE AREAS
Level-1
Coverage
(Maximum)
Level-2
Coverage
Level-3
Coverage
Level-4
Coverage
(Minimum)
Laptop
TV
TV
Figure 12: Test Run scenario for IPTV and VoIP using W-TFMCC.
6.5. Comparison of TFMCC vs W-TFMCC
Comparison of TFMCC with W-TFMCC shows that our proposed W-TFMCC protocol enhances capacity in
tough terrains. Among the five tested terrain types (A, B, C, D, E), which varied in packet loss and round trip time
conditions, significant performance gains are achieved for W-TFMCC. Table-11 shows that coverage of TFMCC drops
from 61.65% to 30% by moving from terrain A to E. On contrary, our proposed protocol W-TFMCC drops coverage
from 61.65% to only 56.25% by moving from terrain A to E, as shown in Table-12. Moreover, W-TFMCC provides
61.65% coverage in slight tough terrains (B, C) too. Major reason for performance enhancement of W-TFMCC isattributed to group based channel distribution.
7. Prior State-of-the-art Approaches
In this section, we present the performance results of previous state of the art approaches. In [2], authors enhance
the quality of experience (QoE) by investigating the most appropriate technology for IPTV. Authors conclude that
IEEE 802.11a provides the best performance preceded by WIMAX and IEEE 802.11g network. In [6], authors show
that 6 7 video sources over 1-hop and 2 3 video sources over 3-hop wireless network are supportable. In[7],
authors show through experiments that IPTV over IEEE 802.11ncan support 12 and 10 users in indoor and outdoor
environments, respectively. In[5], authors show that IEEE 802.11band IEEE 802.11gnetworks can support 2 and 6
streams while IEEE 802.11ncan support dozens of IPTV streams. In [8], authors perform IPTV experiments and show
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the commercial aspects of wireless IPTV. In [14], authors show through experiments that three SDTV channels with at
least one VoIP stream can be supplied over two hops in IEEE 802.11 b/g access points. In [20], authors show through
ns2 simulations that multimedia applications can be provided with less delay, less jitter and less packet loss with their
proposed protocol. In [9], authors verify through simulations that a protocol in between TCP and UDP at transport
layer can provide better streaming performance. Comparison of various studies shows that performance of previous
studies was limited owing to less throughput of predecessor IEEE 802.11 standards. Although TFRC has provided
better performance but it becomes less useful for IPTV which requires multicast wireless transmissions. Our proposed
protocol W-TFMCC has shown to support 32 VoIP users with 1 multicast IPTV user (experimentally) which is an
unprecedented effort. Major novel improvements in our analysis include the analytical and experimental investigations
of optimal transport layer protocols with optimal physical layer parameters for transmission of combined IPTV and
VoIP over IEEE 802.11n, which has not been covered in previous literature.
8. Conclusion
In this paper, we evaluate the capacity of IPTV and VoIP over IEEE 802.11n experimentally and analytically. Our
investigation over transport layer protocols shows that use of TFRC instead of UDP at transport layer can enhanceIPTV capacity by 25%. TFRC adjusts its data rate according to the congestion situations in the network which makes
it highly suitable for IPTV. Results show that TFRC provides fair share in bandwidth to TCP traffic than UDP. Our
investigation over physical layer parameters of IEEE 802.11n shows that queue size and contention window have
optimal size of 70 pkts and 11 respectively for IPTV and VoIP users. Study shows that optimal values of SIFS, DIFS,
Physical header can increase capacity by 10% at least. Trends of aggregation show an optimal aggregation of 4 pack-
ets for IPTV and VoIP beyond which large delay disrupts the support for many users. Our major contribution is the
proposition of W-TFMCC protocol with extensive simulations and experiments. Performance of TFMCC protocol
deteriorates in severe wireless conditions due to absence of group based transmission mechanism. W-TFMCC pro-
tocol provides multicast HDTV and SDTV streams to users based upon the delay and RTT of packets of all users.
W-TFMCC incorporates not only number of users but deals with the channel viewership too. Number of streams trans-
mitted by W-TFMCC are directly related to the number of channels watched by users. Results show that performance
of W-TFMCC is greater than TFRC/TFMCC if at least two users are watching the same channel. W-TFMCC adjustsits data rate according to the network conditions by making user groups depending upon the packet loss conditions.
Our study concludes that use of W-TFMCC with optimal physical layer parameters can increase network capacity at
least by 44% in comparison to UDP and TFRC respectively.
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Saad Salehreceived his MS and BS degrees in Electrical Engineering from National University of Sciences and Tech-
nology (NUST), Islamabad in 2013 and 2011, respectively. Currently, he is working as a Team Lead (Researcher) at
AN-DASH Group, SEECS, NUST, Islamabad. His research interests include computer networks, emerging issues in
IEEE 802.11 WLANs, machine learning and social networks.
Zawar Shahcompleted his PhD degree in Electrical Engineering from the University of New South Wales (UNSW),
Sydney, Australia in 2009. Currently, he is a Senior Lecturer in Information Technology (IT) at Whitireia Commu-
nity Polytechnic, Auckland, New Zealand. His research interests include QoS issues in Wireless Networks, Vertical
Handover issues between 3G/4G networks, Cloud Computing, Network Architectures and Protocols.
Adeel Baigreceived Ph.D. and M.Eng.Sc. degree in computer engineering from the University of New South Wales,
Sydney, Australia, in 2007 and 2001, respectively. Currently, he is an Assistant Professor at School of Electrical
Engineering and Computer Science (SEECS), Islamabad. His research interests are in the protocols and applications
for on-board mobile communication networks, network optimization, and QoS provisioning.
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