VPAL: Video Packet Adaptation Layer for reliable video ... - MWNL

Computer Communications xxx (2010) xxx–xxx

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VPAL: Video Packet Adaptation Layer for reliable video multicast over IEEE 802.11n WLAN q Munhwan Choi a, Maria Samokhina b, Kirill Moklyuk c, Sunghyun Choi a, Jun Heo d, Seong-Jun Oh e,* a

School of Electrical Engineering and INMC, Seoul National University, Seoul 151-744, Republic of Korea Telecommunication Systems Business, Samsung Electronics Co., Ltd., Suwon 443-742, Republic of Korea c Visual Display Business, Samsung Electronics Co., Ltd., Suwon 443-742, Republic of Korea d School of Electrical Engineering, College of Engineering, Korea University, Seoul 136-701, Republic of Korea e College of Information and Communication, Korea University, Seoul 136-701, Republic of Korea b

a r t i c l e

i n f o

Article history: Received 5 October 2009 Received in revised form 10 June 2010 Accepted 16 June 2010 Available online xxxx Keywords: IEEE 802.11n WLAN Video multicast Raptor code Link adaptation

a b s t r a c t In this paper, we propose a scheme, called Video Packet Adaptation Layer (VPAL), for reliable video multicast over the IEEE 802.11n WLAN. VPAL is composed of (1) Raptor coding for reliable video transmission, (2) header compression and (3) packet aggregation, both for efficient video transmission. Most of the VPAL functionalities reside above the emerging IEEE 802.11n Medium Access Control (MAC) layer while the packet aggregation requires some changes in the MAC functionalities. The reliability of the video multicast under a strict delay requirement, is provided by achieving the target error probability of video packets, which is done by controlling both the Raptor code rate and the physical (PHY) layer transmission rate. This strategy can provide a satisfactory quality of multicast video service irrespective of the channel condition with a minimum bandwidth use. New features of the 802.11n MAC are utilized for the channel status feedback from the users. Redundant header fields in the video packets are compressed, and then these packets are aggregated to further reduce the protocol overheads. We also consider a reduced version of VPAL which does not require any change in the MAC functionalities and simply works with the IEEE 802.11n MAC. The performance of the proposed systems is comparatively evaluated in terms of the perceived video quality, i.e., peak signal-to-noise ratio (PSNR), as well as the amount of required resources via both numerical analysis and simulations. Ó 2010 Elsevier B.V. All rights reserved.

1. Introduction IEEE 802.11 wireless local area network (WLAN) [1] has emerged as the leading access technology for indoor wireless networking, as seen by the increasing number of hot-spots deployed at busy places. Also, as there has been a remarkable growth in multimedia Internet services, it is expected that more multimedia contents are transmitted over the IEEE 802.11 WLAN. Especially for the video streaming, there can be many applications where a single video content is simultaneously sent to a few users from a single access point (AP). For such an application, the bandwidth can be more efficiently used via multicast than the conventional unicast. Video streaming requires a certain level of quality of service (QoS) in terms of video packet error probability so that the per-

q Part of this paper was presented at IEEE APWCS 2008, Sendai, Japan, August 2008. * Corresponding author. Tel.: +82 2 3290 4841. E-mail addresses: [email protected] (M. Choi), [email protected] (M. Samokhina), [email protected] (K. Moklyuk), [email protected] (S. Choi), junheo@ korea.ac.kr (J. Heo), [email protected] (S.-J. Oh).

ceived video quality at the receiver, e.g., peak signal-to-noise ratio (PSNR), can be maintained at a certain level. However, the video multicast with the current 802.11 WLAN technology has a difficulty to provide satisfactory QoS due mainly to the absence of the feedback channel for the multicast. Note that the absence of the feedback channel in the video multicast also makes the PHY layer rate adaptation impossible. Therefore, with the current 802.11 WLAN standard, the transmission rate for the video multicast should be fixed at a single rate, e.g., typically the lowest transmission rate to be conservative. There have been several efforts to provide the reliability of the video multicast over the WLAN and overcome the limitation from the absence of the feedback for the multicast. In [2], an AP sets a leader in the group of multicast receivers and an automatic retransmission request (ARQ) protocol is applied between the leader and the AP, pretending as if the multicast is a unicast between the two. By setting the leader as the highest error probability user, a certain level of reliability is likely to be preserved for all the multicast receivers. As the ARQ scheme requires the feedbacks from users regarding the erroneous or error-free reception, an error detection code must be included in the ARQ scheme. On the top

0140-3664/$ - see front matter Ó 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.comcom.2010.06.018

Please cite this article in press as: M. Choi et al., VPAL: Video Packet Adaptation Layer for reliable video multicast over IEEE 802.11n WLAN, Comput. Commun. (2010), doi:10.1016/j.comcom.2010.06.018

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M. Choi et al. / Computer Communications xxx (2010) xxx–xxx

of that, forward error correction (FEC) code can be combined with the error detection code, i.e., hybrid-ARQ, to make the ARQ system more efficient. A framework for the hybrid-ARQ based video transmission is discussed in [3], where an adaptive FEC is jointly used with the variable packet sizes. FEC part of the hybrid-ARQ can adaptively change according to the channel condition of users. As discussed in [3], rate adaptation is generally used with hybridARQ schemes. Providing a rate adaptation scheme in a WLAN multicast is discussed in [4,5]. In [4], the data rate is adapted to the user with the lowest signal-to-noise ratio (SNR), and in [5], the channel conditions of all the users in the multicast group are reported for the rate adaptation. In those schemes, an auxiliary signaling is required to get the SNRs of all the users. Cross-layer design approaches along with rate-adaptive video coding are taken in [6,7] to provide a reliable video streaming. The scheme in [6] relies upon the feedback from the users for video multicast, and the application layer coding is introduced in [7] for reliable video unicast. An erasure-correction code, such as Reed-Solomon (RS) code, is applied right above the MAC layer to provide a certain level of QoS with the FEC functionality which does not require any feedback for the transmission result [8,9]. Recently, a more flexible erasure-correction code, Raptor code [10], has been introduced and employed for multimedia broadcast multicast service (MBMS) in the universal mobile telecommunication system (UMTS) cellular system [11]. A system-level simulation of MBMS in UMTS network can be found in [12]. The rate adaptation in the Raptor code can provide an additional flexibility on the top of the PHY layer rate adaptation. The jointly optimal rate adaptation between the above-MAC erasure-correction code and PHY layer channel code is investigated in [13], and the adaptive modulation and coding (AMC) are considered with the cumulative ARQ schemes for the reliable transmission in the cellular environment [14]. In this paper, we provide a mechanism for a reliable video multicast in the emerging IEEE 802.11n WLAN [15]. First, we use the Raptor code right above the MAC layer to provide the reliability. By adjusting the Raptor code rate depending upon the erasure probability determined from the lower layers, a certain level of QoS for the video multicast streaming can be guaranteed in terms of the video packet error probability. We also employ some features of the 802.11n MAC, such as power save multi-poll (PSMP)

and aggregate-MAC protocol data unit (A-MPDU). First, PSMP is used in order for the multicast transmitter, typically an AP, to get the channel condition feedback from multiple receivers periodically, for instance, once in every group of pictures (GoP) interval. Then, A-MPDU is utilized to reduce the transmission time for a set of Raptor-coded video packets. Note that the PSMP provides the channel conditions and both the Raptor code and the 802.11n PHY rate are adaptively determined according to the lowest SNR user. Finally, we propose VPAL (Video Packet Adaptation Layer), including an above-MAC layer aggregation, to further reduce the MAC overhead. We find that IEEE 802.11n A-MPDU, which is developed to reduce the MAC/PHY overhead, still involves some notable overhead. VPAL also employs a video packet header compression for the overhead reduction purpose. Being composed of Raptor coding, video packet aggregation and header compression, most parts of VPAL are implemented right above the MAC. Our proposed video multicast scheme provides QoS to all the multicast receivers in terms of the video packet error probability via the adaptation of both the Raptor code and the PHY rate while the minimum amount of wireless resource is used. Throughout the rest of the paper, we use the terms SDU (service data unit) and PDU (protocol data unit). An SDU is the data unit, which is passed to the layer in consideration from the next higher layer. A PDU, which is forwarded to the next lower layer, includes both the SDU as its payload and the header and other auxiliary fields added by this layer. The rest of the paper is organized as follows. In Section 2, we give an overview of Raptor code and its properties. Section 3 describes the proposed multicast scheme, and Section 4 presents the results of network performance by taking the overheads into consideration. Section 5 shows the video quality evaluation by simulation, and finally, Section 6 concludes the paper. 2. Raptor codes As most video streaming applications impose a strict delay requirement, employing an ARQ protocol for the video multicast is not typically desirable. There have been approaches to employ an ARQ protocol along with an erasure correction code for multicast, e.g., [16]. However, by definition ARQ protocol requires feedback(s) from all the receivers to positively or negatively acknowledge the receptions, and such overhead increases propor-

80

70

Reliability = 90.0% Reliability = 95.0% Reliability = 99.0% Reliability = 99.9% Reliability = 99.99%

Raptor code overhead (%)

60

50

40

30

20

10

0 0.001

0.01

0.1

1

Symbol erasure probability

Fig. 1. Raptor code performance with various target reliabilities for k = 100.


3


tional to the number of receivers. Therefore, to provide a reliability for the video multicast with reasonable overhead, relying upon a certain form of FEC at a layer above the MAC layer could be an attractive option. In PHY and MAC layers for wireless communication, channel codings are applied due to the error-prone nature of the wireless channel. PHY and MAC layers’ channel codings are usually implemented for the purpose of the frame error correction and detection. Cyclic redundancy check (CRC) code is mainly used for the frame error detection. When an erroneous MAC frame is received and an error is detected by the CRC, the MAC frame is considered to be dropped. In the absence of retransmissions, such a dropped frame works as a frame erasure at the higher layer. An erasure correction code can be used at the higher layer to provide a certain level of reliability in this situation. Raptor codes are introduced in [10] as a fountain erasure correction code, capable of producing an unlimited sequence of encoded symbols (i.e., n) from a block of k fixed-length source symbols – typically non-binary symbols. It is designed and optimized as an erasure-correction code and provides a large degree of freedom in parameter choices. RS codes are also powerful linear block erasure correction codes, which have been widely adopted for many real systems, but when used as an above-MAC layer’s erasure-correction code, its efficiency tends to decrease compared to the Raptor code, due to its decoder complexity [17,18]. Moreover, there are limitations in the RS code design, as there are few constraints on the sizes of the symbols and the source blocks. For a fixed number k of information symbols, a systematic Raptor code’s performance can be characterized by three parameters, namely, (1) the input symbol’s erasure probability, (2) the probability of a successful decoding (i.e., reliability) and (3) the required code rate k/n to achieve the target reliability for the given erasure probability. When k information symbols are taken into an encoder, n k output parity symbols for erasure correction are generated, where the required code rate k/n is decided by the symbol erasure probability and the required reliability for a given k. In this work, considering the MAC overhead and the efficiency, k = 100 is used, and for this

case the mapping between (n k)/n (overhead ratio) and the symbol erasure probability is shown in Fig. 1. For Fig. 1, the systematic Raptor code specified in the 3GPP MBMS standard [19] is used with a specific size of k = 100, and the recommended maximum likelihood algorithm is used as the decoding algorithm. For example, when the symbol erasure probability is 0.1, to achieve the target reliability of 99.9%, we need 28 (=n k) parity symbols, i.e., overhead is 28% and the resulting code rate is 100/128. 3. Proposed multicast scheme A video streaming system in consideration is illustrated in Fig. 2. A streaming server produces video data and packetizes it into video packets, and the generated packets are transmitted through an IP network as 802.3 Ethernet frames to reach an AP. From the application layer down to the 802.11 MAC layer, RTP (real-time protocol), UDP (user datagram protocol), IP (internet protocol), and IEEE 802.2 LLC (logical link control) protocols are used. The AP extracts video packets and encapsulates them as 802.11 MAC frames. Mobile devices receive the 802.11 MAC frames sent over the air, but due to the error-prone wireless link, 802.11 MAC frames can be lost. As the video streaming is usually done with compressed data, a MAC frame loss can be detrimental to the quality of the reproduced video. For reliable video multicast, we propose VPAL mostly operating on top of the 802.11n MAC layer as shown in Fig. 2. The basic idea of the proposed VPAL is as follows. Under VPAL, a video packet corresponds to a Raptor symbol, and hence, the Raptor symbol erasure probability is the same as the video packet error probability, which, in turn, depends on the SNR value, PHY rate and MAC frame length. Before the transmission of a chunk of video data (which corresponds to a GoP in our work), the AP determines the worst expected symbol erasure probability based on the information about the current channel status of each receiver. In this paper, a GoP data chunk of 50,000 bytes is used for the evaluation. Note that a Raptor symbol length is equal to 1/100 of a GoP size, as we use the Raptor code of information symbol number k = 100. Thus, a

...

802.11n Access Point

...

IP network

VPAL

802.3 MAC

802.11n MAC

802.3 PHY

802.11n PHY

Ethenet (Wired)

802.11 (Wireless)

RTP Encapsulation

UDP IP 802.2 LLC 802.3 MAC

802.11n Access Point 802.3 PHY RTP UDP 802.11n device Extraction

IP 802.2 LLC VPAL 802.11n device 802.11n MAC

802.11n device

802.11n PHY Fig. 2. Raptor code-based video streaming network.


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M. Choi et al. / Computer Communications xxx (2010) xxx–xxx SIFS

SIFS

AP Reciever 1

PSMP

SIFS

RM

SIFS

SIFS

Data Data

PSMP

Data

Data

FB

Reciever 2

FB FB

Reciever 3 Other receivers

SIFS

SIFS

NAV is set

NAV is set

Fig. 3. Protocol timing.

50,000 byte GoP data chunk is divided into 100 video source symbols of 500 bytes for Raptor encoding.1 Then, the AP encodes the video source symbols with the Raptor encoder, generating as many encoded Raptor symbols (i.e., including both video and parity packets) as needed to achieve a target reliability level for the given expected symbol erasure probability. Note that as the SNRs of multiple receivers can be different, the AP would perform the adaptation based on the worst SNR receiver. Also, the worst SNR receiver can vary over time due to the time-varying channel characteristics. It is possible that a user with a very poor channel condition requires a large number of Raptor code symbols per GoP in order to achieve, say 99.9% reliability. This can eventually incur a large delay. Note that a large delay can be also incurred from the video source itself by having too many Raptor symbols per GoP. This large delay can be avoided by having a strict delay bound at the AP-side. In the proposed scheme, as the number of Raptor symbols is decided at the AP based upon the channel condition feedback from users, the AP can estimate the delay by the Raptor symbols. When the delay bound can be translated into the bound on the number of Raptor symbols, only a part of required Raptor symbols can be transmitted. It is equivalent to ignore the feedback of users with very poor channel conditions. As for those users, achieving the target reliability with a small delay is not possible anyway, but the target reliability can still be achieved for other users – with the delay still being in the bound. Note that the user with an extreme bad channel quality for a long period of time is likely to be out of the IEEE 802.11n application. For the efficiency, we adopt the packet header compression method in [20]. IEEE 802.2 LLC, IP, UDP and RTP header sizes are 8, 20, 8 and 12 bytes, respectively. The header compressor converts the large header overhead to only a few bytes. In [21], using that header compression method, IP/UDP/RTP protocol headers can be compressed to 6 bytes on the average. In fact, IEEE 802.2 LLC header can be fully compressed as well because every video packet will have the same LLC header content. This implies that the adopted header compression methods can reduce each packet size by 42 bytes, i.e., from 48 bytes to 6 bytes. The protocol timing diagram is illustrated in Fig. 3. IEEE 802.11n PSMP burst of two rounds is used [15] for a transmission of video packets for every GoP. During the first round of the PSMP burst, the AP collects SNR feedbacks from the multicast receivers. A mechanism similar to the group RTS scheme in [22] is employed for the SNR feedback collection, except for the fact that the order of feedback transmissions is defined by the 802.11n-based PSMP frame. Reliable multicast (RM) and feedback (FB) frames, whose sizes are 25 and 16 bytes, respectively, are transmitted at the lowest PHY rate for the most reliable transmission. If at least one of the

FB frames is not correctly received by the AP, the procedure starts over. Note that the probability of failure in the transmission of RM and FB frames is smaller than the probability of data transmission failure, since they are short frames transmitted at the most reliable PHY rate. Therefore, if the transmission of RM frame to some stations, or the transmission of FB frame from a station fails several times, data transmission would most probably be unsuccessful anyway. If the retry limit for an RM frame is exhausted and the feedback from some stations is not correctly received, these stations are considered to have left the network. The multicast set is updated and the next attempt to transmit the data is performed. During the second round of the PSMP burst, multicast data frames are transmitted. The PHY rate for transmission is chosen based on the PHY layer link-level results. At the stage of data transmission, as illustrated in Fig. 4, each Raptor symbol forms a MAC SDU (MSDU), and at the MAC layer, an MSDU becomes a MAC PDU

Raptor source and parity symbols Above MAC Forming MPDUs

MAC header

802.11 MPDUs FCS

Forming PPDUs 802.11n A-MPDU

PHY header

802.11 PPDUs PPDU Fig. 4. IEEE 802.11n A-MPDU based scheme.

Raptor source and parity symbols VPAL Header Compression

Forming MSDUs

CRC (4 bytes) MAC header

Forming MPDUs FCS VPAL 802.11 MPDUs

FEC for MAC header (16 bytes)

Forming PPDUs

PHY header

802.11 PPDUs

1

Considering PHY, MAC, and other higher layer header overheads for the transmission of a video source symbol, and also considering the Raptor code efficiency, k = 100, which generates 500-byte video source symbols, is a proper length in this paper.

PPDU Fig. 5. VPAL operation.


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M. Choi et al. / Computer Communications xxx (2010) xxx–xxx VPAL Payload byte:

2 Frame Control

6

2 Duration

6

Dest Source Address Address

6

2

2

4

2

16

BSSID

Sequence Control

QoS Control

HT Control

L

FEC for MAC Header

MAC Header

L

4

4 ...

Raptor Symbol

VPAL Header

FCS

CRC (4 bytes)

Fig. 6. VPAL frame format.

(MPDU) comprising a MAC header, an MSDU (as its payload) and a frame check sequence (FCS) (based on CRC-32). As a baseline, we can employ 802.11n A-MPDU (aggregate MPDU) mechanism [15,23] to enhance the MAC efficiency and therefore, a number of MPDUs are aggregated together to form a single PHY PDU (PPDU) at the PHY. In this case, each frame labelled as ‘‘Data” in Fig. 3, represents a PPDU containing the aggregated MPDUs. In order to further improve the aggregation efficiency, VPAL aggregation is introduced residing between the Raptor encoding and the MAC layer. The operation of VPAL layer is illustrated in Fig. 5, and Fig. 6 shows the MAC frame format with VPAL aggregation. Multiple video and parity packets (Raptor symbols) are aggregated together while a CRC-32 is appended for the error detection of each Raptor symbol. Note that the receiver of the VPAL frame first checks whether the FCS field matches the frame payload. Only when the FCS (for a VPAL frame) fails, then individual pieces are accepted or rejected based on their own CRC information. L field in the VPAL header in Fig. 6 indicates the length of each video packet and is used to determine the boundaries. To ensure that the VPAL header as well as the L field are received correctly, a powerful error-correcting code, i.e., RS code, is employed with 16-byte redundancy. The main advantage of using this VPAL frame is a lower overhead compared to the A-MPDU due to the increased aggregation efficiency. 4. Performance analysis In this section, we analyze the performance of multicast video streaming using VPAL in terms of the total transmission time of one GoP. As long as the target reliability is satisfied, the shorter the GoP transmission time, the better. This analysis is used in Section 5.1 in order to determine the optimal (i.e., achieving the min-

imum GoP transmission time) combination of the PHY rate and Raptor code rate for a given channel condition. 4.1. Overhead considerations When computing the transmission time, two types of overhead should be considered – Raptor and PHY layer overheads. For the Raptor code overhead, the number n of the Raptor code’s output symbols is determined based on the given Raptor symbol erasure probability, which is the same as the frame error probability. The Raptor symbol erasure probability is then determined from the modulation symbol SNR, PHY mode and the length of the frame as discussed in the following. The relationship between n and the Raptor symbol erasure probability is shown in Fig. 1 for the target reliabilities. As shown in Fig. 7, we assume that the PPDUs are transmitted using HT-greenfield format in 802.11n [15]. For the PHY layer overhead, according to Fig. 7, the time needed to transmit LPSDU-byte long PSDU at PHY mode m, is the sum of times needed to transmit HT-greenfield Short Training field (HT-GF-STF), the first HT Long Training field (HT-LTF1), HT-SIGNAL field, DATA HT Long Training field (DATA HT-LTF) and the time needed to transmit the DATA field, which is transmitted at the PHY rate indicated in the HT-SIGNAL field. THT-GF-STF, THT-LTF1, THT-SIGNAL, and TDATA HT-LTF are the times needed to transmit HT-GF-STF, HT-LTF1, HT-SIGNAL, and DATA HT-LTF, respectively. Note that in the proposed protocol, every frame is preceded with a SIFS interval of 16 ls. For simplicity, we denote the time for the overhead to transmit a PPDU as OPhy, and it is defined as

OPhy ¼ T HT-GF-STF þ T HT-LTF1 þ T HT-SIGNAL þ T DATA HT-LTF þ SIFS; where THT-GF-STF = THT-LTF1 = THT-SIGNAL = 8 ls, and TDATA

HT-LTF1 (8us)

HTMCS CBW 20/40 LENGTH 7 bits 1 bit 16 bits

HT packet information fields 10 bits

= 4 ls.

DATA Coded/OFDM (MCS is indicated in HT-SIGNAL)

HT-SIGNAL (8 µ sec)

HT-GF-STF (8us)

HT-LTF

ð1Þ

CRC 8 bits

Tail 6 bits

DATA HT-LTF (4us)

SERVICE 16 bits

PSDU

Tail 6 bits

Pad Bits

PHY protocol data unit (PPDU)

Fig. 7. IEEE 802.11n PHY protocol data unit.

Table 1 Mandatory modes of IEEE 802.11n PHY. Mode m

Modulation type

Convolutional code rate r

Data rate (Mbps)

BpS

1 2 3 4 5 6 7 8

BPSK QPSK QPSK 16-QAM 16-QAM 64-QAM 64-QAM 64-QAM

1/2 1/2 3/4 1/2 3/4 2/3 3/4 5/6

6.5 13.0 19.5 26.0 39.0 52.0 58.5 65.0

3.25 6.5 9.75 13.0 19.5 26.0 29.25 32.5


6


By T m PSDU ðLPSDU Þ, we denote the time needed to transmit the DATA field of a frame at PHY rate m. It is dependent upon the length of PSDU and is calculated as follows:

Tm PSDU ðLPSDU Þ ¼

2:75 þ LPSDU tSymbol; BpSðmÞ

4.2. GoP transmission time of VPAL As shown in Fig. 3, the first round of PSMP burst is for the transmissions of an RM frame by the AP and NSTA FB frames by the stations, and the second round of PSMP burst is for the transmissions of multicast data frames by the AP. Thus, the total transmission time for a GoP is given by

ð2Þ

where dxe denotes the smallest integer that is larger than x, and tSymbol is an OFDM symbol duration of 4 ls. The number 2.75 comes from the SERVICE and Tail bits of PPDU. BpS (m) denotes bytes per symbol for a given PHY mode, and its value for different PHY modes is given in Table 1. In the table, BpS represents the number of bytes per OFDM symbol of 4 ls. The time needed to access the channel and transmit a PPDU is m Tm PPDU ðLPSDU Þ ¼ OPhy þ T PSDU ðLPSDU Þ:

m Tm Total ¼ T PSMP ðN STA þ 1Þ þ T RM þ N STA T FB þ T PSMP ð1Þ þ T Data ;

ð4Þ

where TPSMP() is the time to transmit a PSMP frame and this is a function of the number of dedicated transmitters and receivers, and NSTA denotes the number of receivers in the multicast group. TRM and TFB are the times to transmit RM and FM frames, respectively. As NSTA receivers send the feedback in sequence, NSTA is multiplied to TFB. T m Data represents the time to transmit the Raptor

ð3Þ

120 6.5 Mbps 13.0 Mbps 19.5 Mbps 26.0 Mbps 39.0 Mbps 52.0 Mbps 58.5 Mbps 65.0 Mbps Min Tx time

GoP transmission time (ms)

100

80

60

40

20

0 -5

0

5

10

15

20

SNR (dB)

(a) GoP transmission time at different rates. 1.0

Raptor code rate

1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6

PHY rate (Mbps)

0.6 65.0 58.5 52.0 39.0 26.0 19.5 13.0 6.5 -5

0

5

10

15

20

SNR (dB)

(b) Optimal combination of Raptor code rate and PHY rate for the minimum GoP transmission time. Fig. 8. GoP transmission time optimization of VPAL (GoP size = 50,000 bytes, k = 100, 99.99% reliability).


7


Raptor 99.99% reliability Raptor 99.9% reliability Raptor 99.0% reliability Raptor 95.0% reliability Raptor 90.0% reliability

140

Minimum GoP transmission time (ms)

120 90 88

100

86 84 80

82 80 78

60

-3

-2.5

-2

-1.5

-1

40

20

0 -5

0

5

10

15

20

SNR (dB)

Fig. 9. Impact of reliability level on the minimum GoP transmission time in VPAL (GoP size = 50,000 bytes, k = 100).

Table 2 Feature comparison among the considered schemes. Scheme

Rate adaptation

Raptor code

Header compression

Aggregation

Lowest Rate Tx RA only No Aggregation A-MPDU + RA + Raptor A-MPDU + RA + Raptor + HC VPAL

No Yes Yes Yes Yes Yes

No No Yes Yes Yes Yes

No No No No Yes Yes

No No No A-MPDU A-MPDU Proposed aggregation

encoded video data from a GoP and m indicates the PHY mode used in the transmission. In the following, each transmission time in Eq. (4) is analyzed. A PSMP frame consists of a MAC header (34 bytes), a PSMP parameter Set fixed field (2 bytes), and one or more PSMP STA Info fields (8 bytes), where a PSMP STA Info field is dedicated to each scheduled station [15]. Then the time to transmit a PSMP frame becomes

T PSMP ðN STA þ 1Þ ¼ T 1PPDU ððNSTA þ 1Þ L1 þ L2 þ L3 Þ;

NS

VPAL

4095 LH ; LS þ LCRC

¼

ð7Þ

where the VPAL overhead LH = 48 as shown in Fig. 6 and the CRC size LCRC = 4. The number of VPAL frames for one GoP transmission becomes

NVPAL ¼

ð5Þ

n

NS

;

ð8Þ

VPAL

where n is the number of output symbols from the Raptor encoder for one GoP considering the Raptor code overhead for the target reliability. The length of a VPAL frame which has the maximum number of aggregated Raptor symbols is determined by

where L1, L2, and L3 are the lengths of PSMP STA Info field, MAC header, and PSMP parameter Set fixed field, respectively. T m PPDU ðÞ is defined in Eq. (3). Note that for the PSMP frame, PHY mode 1, i.e., the most conservative data rate is used targeting for the receivers with very low SNR. The first PSMP schedules the transmission of an RM frame by the AP and the FM frame transmissions from NSTA receivers. Similarly, TRM and TFB are given by

When n is an integer multiple of NS_VPAL, the time to transmit the encoded video data from one GoP with PHY mode m is

T RM ¼ T 1PPDU ð25Þ and T FB ¼ T 1PPDU ð16Þ;

m Tm Data ¼ N VPAL T PPDU ðLVPAL

ð6Þ

from their sizes and the PHY mode 1. TRM and TRM are considered as PPDU’s as shown in Fig. 3. The computation of T m Data is derived below. When VPAL is considered for a better aggregation efficiency, each LS-long Raptor symbol is protected by CRC-32 and aggregated in a VPAL frame. Its format is shown in Fig. 5. Since the maximum PSDU size supported by the 802.11n PHY is 4095 bytes (see Fig. 7), the maximum VPAL frame size is assumed to be 4095 bytes. Then, the number of symbols NS_VPAL, which can be transmitted within one VPAL frame, is determined by

LVPAL

MPDU

¼ LH þ N S

VPAL ðLS

þ LCRC Þ:

MPDU Þ;

ð9Þ

ð10Þ

where N VPAL ; T m PPDU ðÞ, and LVPAL_MPDU are defined in Eqs. (8), (3), and (9), respectively. On the other hand, when n is not an integer multiple of NS_VPAL, the transmission time of the very last VPAL frame is less than T m PPDU ðLVPAL MPDU Þ depending upon the symbols to be aggregated. 5. Performance evaluation The performance of multicast video streaming using VPAL is comparatively presented in this section. As the header


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M. Choi et al. / Computer Communications xxx (2010) xxx–xxx 140 Lowest Rate Tx RA only No Aggregation A-MPDU + RA + Raptor A-MPDU + RA + Raptor + HC VPAL

Minimum GoP transmission time (ms)

120

100

80

60

40

20

0 -5

0

5

10

15

20

SNR (dB)

Fig. 10. Comparison of the minimum GoP transmission time (GoP size = 50,000 bytes).

PHY rate (Mbps)

Achieved reliability (%)

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Fig. 11. Comparison of achieved reliability and selected PHY rate (GoP size = 50,000 bytes).

compression and the packet aggregation are integral parts of VPAL, overhead reductions and the resulting transmission times are analytically considered. For the PHY layer, we assume IEEE 802.11n mandatory PHY rates with the modulation and coding schemes (MCSs) summarized in Table 1, and their link-level simulation results are used for the PHY layer performance abstraction. As we take the frame error at the PHY layer as the Raptor symbol error, the Raptor overhead needed to achieve the target reliability can be obtained using the Raptor code performance curves shown in Fig. 1 where the target reliability is defined as 99.99%. The GoP size is assumed to be 50,000 bytes. 5.1. Optimal GoP transmission time of VPAL Fig. 8 shows the GoP transmission time from Eq. (4) for a given SNR when the proposed VPAL scheme is used. The given SNR should correspond to the minimum SNR out of all the reported SNR values from the multicast receivers. Joint PHY rate and Raptor

code rate adaptation according to the graphs in Fig. 8(b) would allow to achieve the target reliability (99.99%) with the minimum GoP transmission time (labelled as ‘Min Tx time’) as shown in Fig. 8(a). We consider only the minimum GoP transmission time, achieved by using the optimal combination of the Raptor code rate and the PHY rate, for the rest of the paper. Apparently, higher SNR results in shorter minimum GoP transmission time since smaller overheads are needed to achieve the target reliability. We also observe that as the SNR increases, the optimal PHY rate increases proportionally while the optimal Raptor code rate fluctuates. This phenomenon occurs in part because there are only eight different PHY rates while there exist infinitely many Raptor code rates so that the Raptor code is used to complement the PHY to achieve the target reliability. This kind of optimization is particularly useful when the considered video multicast traffic coexists with other types of traffic. Note that the optimization, i.e., the minimization of the video transmission time, means the maximization of resources which can be used by other types of traffic.


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M. Choi et al. / Computer Communications xxx (2010) xxx–xxx 120

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(b) Delivery rate of video frames. Fig. 12. Simulation results (fading channel, average GoP size = 50,000 bytes, the number of multicast users: 1–5, average SNR = 0, 5, 15 dB).

Fig. 9 shows the impact of applying Raptor codes designed to support different target reliability levels of successful decoding as the given SNR increases. For different target reliabilities, the minimum GoP transmission times are different. Apparently, the higher the target reliability is, the larger the minimum GoP transmission time is since it would require more overheads. However, the difference in transmission times for different probabilities of successful decoding is negligible. We focus only on the Raptor codes with 99.99% of successful decoding for the rest of the paper. 5.1.1. Optimal GoP transmission time comparison To show the advantages of various features of the proposed VPAL, the following six schemes are compared, where different schemes employ different combinations of rate adaptation (RA), Raptor code, header compression (HC), and aggregation schemes: (1) Lowest Rate Tx (fixed rate) scheme without any rate adaptation

and forward error correction schemes, (2) RA only scheme with the PHY rate adaptation, but without forward error correction schemes such as Raptor code, (3) No aggregation scheme with the proposed rate adaptation (of both PHY rate and Raptor code rate) and Raptor code. (4) A-MPDU + RA + Raptor scheme with the proposed rate adaptation and Raptor code, but without header compression, based on the A-MPDU framework, (5) A-MPDU + RA + Raptor + HC scheme with header compression in addition to the A-MPDU scheme with the proposed rate adaptation and Raptor code, and (6) VPAL scheme with all the proposed methods, i.e., the header compression, the proposed rate adaptation, Raptor code, and the aggregation scheme involving the proposed VPAL frames. Table 2 summarizes the characteristics of each scheme. It should be noted here that A-MPDU + RA + Raptor + HC scheme is the best scheme, which can be implemented in the 802.11ncompliant MAC, since it employs the 802.11n A-MPDU while VPAL


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M. Choi et al. / Computer Communications xxx (2010) xxx–xxx 60 H.264 original video clip (Average PSNR = 34.87 dB) Lowest Rate Tx (Average PSNR = 20.92 dB) RA only (Average PSNR = 21.32 dB) VPAL (Average PSNR = 34.54 dB) 50

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Fig. 13. PSNR value evolution (fading channel, average GoP size = 50,000 bytes, average SNR = 0 dB).

requires the VPAL frame-based aggregation scheme, implying a MAC change. For the rest of the paper, the last three schemes are also referred to as the proposed schemes since they employ three important proposed features, namely, rate adaptation, Raptor code, and aggregation. The Lowest rate Tx scheme and the RA only scheme use the 802.11n PSMP frameworks for a fair comparison. In the RA only scheme, the highest PHY rate among the PHY rates, which can support target reliability (99.99%), is selected. Fig. 10 shows the minimum GoP transmission time for the six different schemes as the SNR varies. While we have presented the GoP transmission time analysis in Section 4 and the GoP transmission time minimization in the previous subsection, both only for the VPAL scheme, similar analyses can be done easily for other schemes, and Fig. 10 is based on such analyses. Since the Lowest rate Tx scheme uses a fixed PHY rate for the robust communication, the GoP transmission time is fixed regardless of the SNR. For the entire SNR range, the minimum GoP transmission time of VPAL is the minimum, and is followed by those of A-MPDU + RA + Raptor + HC, A-MPDU + RA + Raptor, and No aggregation. That is, by adding more features, the minimum GoP transmission time decreases further accordingly. In the case of Lowest rate Tx and RA only, their minimum GoP transmission times are larger than that of VPAL for the most considered SNR values. However, for very small SNR values, i.e., under 2 (dB), the minimum GoP transmission times of these two schemes are smaller than that of VPAL. While it looks weird in this figure, it becomes clear if we see Fig. 11, which shows both the achieved reliability and the optimal PHY rate for each scheme. That is, for such low SNR values, these two schemes without Raptor code cannot meet the target reliability level, i.e., 99.99%, at all. It should be also noted that the achieved reliability of the other four schemes, employing the Raptor code, remains the same for all the SNR values. In summary, we conclude that VPAL scheme achieves the target reliability irrespective of the SNR value while consuming the minimum GoP transmission time. 5.2. Video quality evaluation For the video quality evaluation, we consider a sample source video sequence composed of 5000 video frames, corresponding to 200 s of the playback time with 25 frames per second. Each frame has the size of 320 240 pixels and sub-sampled in YUV of 4:2:0.

The source video is encoded by H.264 codec, and the bit rate of video is about 800 kbits/s. RTP, UDP and IP protocol stacks are also considered. Using the MP4Box tool from EvalVid [24] toolset, we add a hint track which describes how the video source sequence is fragmented to fit into the 500-byte video packets. One GoP becomes about 50,000 bytes including RTP, UDP and IP headers. For our evaluation, we follow the assumption that if a GoP decoding fails, all packets from this GoP are lost. In order to obtain the packet loss traces, we use a Rician fading channel model with a Rician factor of 1 and velocity of 1 km/h for the packet loss simulation. Given the packet loss trace, we reconstruct the resultant video stream with errors utilizing EvalVid toolset. Then, the erroneously received MP4 file is decoded and PSNR is calculated. EvalVid tool is also used for the PSNR evaluation. We consider a simple scenario for fading channel and multiple receivers where each receiver has the same average SNR. Fig. 12(a) shows the average GoP transmission time while utilizing the optimal Raptor code rate and the PHY rate depending on the number of multicast receivers and the average SNR values. The average GoP transmission time is obtained by averaging the GoP transmission times for multiple GoPs across all the multicast receivers. In the case of Lowest Rate Tx scheme, the average GoP transmission time is fixed regardless of the number of receivers and the average SNR value. As the number of receivers increases, the lowest SNR value in the feedback decreases due to the fading, and hence, the average GoP transmission time increases. In high SNR environment, e.g., SNR = 15 dB, the proposed schemes reduce the GoP transmission time for video streaming with the same delivery rate. On the other hand, in low SNR environment, e.g., SNR = 0 dB, the proposed schemes require more GoP transmission time. This is due to the fact that the SNR of the worst channel receiver is always low, so these schemes operate mostly in the low PHY rate region and transmit many parity symbols. However, in terms of the video quality, they outperform the other two basic multicast schemes. Fig. 12(b) shows the average delivery rate of video frames in the same environments. The average delivery rate is almost fixed regardless of the number of receivers because each receiver experiences a similar channel environment. In high SNR environments, the delivery rate becomes almost one. That means that the frame losses rarely happen. However, in low SNR environments, the delivery rates of the two schemes without Raptor code are lower than the proposed schemes. The proposed schemes still maintain



a high delivery rate close to one, thanks to the help of the Raptor code. Fig. 13 shows the PSNR evolution of a receiver with average2 SNR = 0 dB. Since our three proposed schemes have similar PSNR performances, we show only VPAL scheme in this figure. The resultant PSNR degradation of VPAL is very minimal. That is, the average PSNR of VPAL is 34.54 dB while the average PSNR of the original H.264 video clip is 34.87 dB. It is remarkable that the PSNR degradation of VPAL is so small even for such bad channel condition (SNR = 0 dB in Fig. 13) while the average PSNR of the other two basic multicast schemes without Raptor code is very low (around 21 dB). For higher average SNR values, the schemes without Raptor code will also reach the reliability close to 100% (due to the fact that frames sent over 6.5 Mbps PHY rate are mostly received without errors), but the proposed VPAL would show a much better performance in terms of the channel occupancy time due to the joint adaptation of PHY rate and Raptor code rate. 6. Concluding remarks In this paper, we proposed VPAL, which is a Raptor code-based video multicast transmission scheme over the IEEE 802.11n WLAN. We use the feedback from the receivers for the joint adaptation of the Raptor code rate and the PHY rate, thus achieving both the reliability and the efficiency of transmission. VPAL also employ video packet aggregation and header compression schemes to improve the protocol efficiency. We plan to extend the proposed VPAL by considering a crosslayer approach which involves an application layer adaptation, e.g., hierarchical layered video coding. The proposed scheme can be also enhanced to support not only video multicast, but reliable multicast in general. In order to provide such reliable data multicast, the proposed scheme should be coupled with acknowledgment schemes. This would allow to get rid of the restriction on the channel coherence time, i.e., the time that the channel condition is assumed not to change. In this work, we have assumed 200 ms channel coherence time, which should be reasonable for typical indoor environments. Acknowledgements This research was supported in part by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2010-(C10901011-0004)) and in part by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant No. 2009-0088455). References [1] IEEE Std 802.11, International Standard [for] Information Technology – Telecommunications and information exchange between systems-Local and metropolitan area networks-Specific Requirements – Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications, IEEE 802.11-1999, 1999.

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[2] J. Kuri, S.K. Kasera, Reliable multicast in multi-access wireless LANs, in: Proceedings of the Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM ’99), vol. 2, March 1999, pp. 760– 767. [3] L. Badia, N. Baldo, M. Levorato, M. Zorzi, A Markov framework for error control techniques based on selective retransmission in video transmission over wireless channels, IEEE Journal on Selected Areas in Communications (JSAC) 28 (3) (2010) 488–500. [4] Y. Park, Y. Seok, N. Choi, Y. Choi, J.-M. Bonnin, Rate-adaptive multimedia multicasting over IEEE 802.11 wireless LANs, in: Proceedings of the 3rd IEEE Consumer Communications and Networking Conference (CCNC 2006), vol. 1, January 2006, pp. 178–182. [5] A. Basalamah, H. Sugimoto, T. Sato, Rate adaptive reliable multicast MAC protocol for WLANs, in: Proceedings of the 63rd IEEE Vehicular Technology Conference (VTC 2006-Spring), vol. 3, May 2006, pp. 1216–1220. [6] J. Villalon, P. Cuenca, L.O. Barbosa, Y. Seok, T. Turletti, Cross-layer architecture for adaptive video multicast streaming over multirate wireless LANs, IEEE Journal on Selected Areas in Communications (JSAC) 25 (4) (2007) 699–711. [7] M. van der Schaar, S. Krishnamachari, S. Choi, X. Xu, Adaptive cross-layer protection strategies for robust scalable video transmission over 802.11 WLANs, IEEE Journal on Selected Areas in Communications (JSAC) 21 (10) (2003) 1752–1763. [8] K. Choi, S. Choi, CLPC: cross-layer product code for video multicast over IEEE 802.11, in: Proceedings of MediaWIN 2006, Athens, Greece, April 2006. [9] L. Han, D. Raychaudhuri, H. Liu, K. Ramaswamy, Cross layer optimization for scalable video multicast over 802.11 WLANs, in: Proceedings of the 3rd IEEE Consumer Communications and Networking Conference (CCNC 2006), vol. 2, January 2006, pp. 838–843. [10] A. Shokrollahi, Raptor codes, IEEE Transactions on Information Theory 52 (6) (2006) 2551–2567. [11] M. Sayit, G. Seckin, Scalable video with raptor for wireless multicast networks, in: Proceedings of Packet Video 2007, 2007, pp. 336–341. [12] M. Luby, T. Gasiba, T. Stockhammer, M. Watson, Reliable multimedia download delivery in cellular broadcast network, IEEE Transactions on Broadcasting 53 (1) (2007) 235–246. [13] T. Courtade, R. Wesel, A cross-layer perspective on rateless coding for wireless channels, in: Proceedings of the IEEE International Conference on Communications (ICC’09), Dresden, Germany, June 2009, pp. 1–6. [14] Fen Hou, James She, Pin-Han Ho, Xuemin (Sherman) Shen, Performance analysis of the cumulative ARQ in IEEE 802.16 networks, Wireless Networks 16 (2010) 559–572. [15] IEEE P802.11n/D7.0, Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Enhancements for Higher Throughput, September 2008. [16] M. Rossi, M. Zorzi, F.H.P. Fitzek, Link layer algorithms for efficient multicast service provisioning in 3G cellular systems, in: Proceedings of IEEE Global Telecommunications Conference 2004 (GLOBECOM’04), Dallas, Texas, USA, November 2004, pp. 3855–3860. [17] M. Luby, LT Codes, in: Proceedings of the 43rd Annual IEEE Symposium on Foundations of Computer Science (FOCS 2002), Vancouver, Canada, November 2002, pp. 271–280. [18] D.J.C. MacKay, Information Theory, Inference, and Learning Algorithms, Cambridge University Press, 2003. [19] 3GPP TS 26.346 V6.1.0, Technical Specification Group Services and System Aspects; Multimedia Broadcast/Multicast Service Protocols and Codes, June 2005. [20] C. Bormann, C. Burmeister, M. Degermark, H. Fukushima, H. Hannu, L-E. Jonsson, R. Hakenberg, T. Koren, K. Le, Z. Liu, A. Martensson, A. Miyazaki, K. Svanbro, T. Wiebke, T. Yoshimura, H. Zheng, Nokia. RObust Header Compression (ROHC): framework and four profiles: RTP, UDP, ESP, and uncompressed, IETF RFC 3095, July 2001. [21] F. Fitzek, S. Rein, P. Seiling, M. Reisslein, RObust Header Compression (ROHC) performance for multimedia transmission over 3G/4G wireless networks, Wireless Personal Communications 32 (1) (2005) 23–41. [22] Z. Ji, Y. Yang, J. Zhou, M. Takai, R. Bagrodia, Exploiting medium access diversity in rate adaptive wireless LANs, in: Proceedings of the 10th Annual International Conference on Mobile Computing and Networking (MobiCom’04), May 2004, pp. 345–359. [23] A. Sidelnikov, J. Yu, S. Choi, Fragmentation/aggregation scheme for throughput enhancement of IEEE 802.11n WLAN, in: Proceedings of IEEE APWCS 2006, Daejon, August 2006. [24] J. Klaue, B. Rathke, A. Wolisz, EvalVid – a framework for video transmission and quality evaluation, in: Proceedings TOOLs’03, Urbana, Illinois, USA, September 2003, pp. 255–272.

2 When SNR = 0 dB, even for the user with a very poor channel condition does not necessitate too large amount of Raptor symbols to achieve 99.9% reliability. For the practical purpose, a bound on the maximum number of Raptor symbols or equivalently the minimum channel quality to be considered is needed to avoid excessive delay.
