Video Streaming

H.-S. Kim et al.: Measurement Based Channel-Adaptive Video Streaming for Mobile Devices over Mobile WiMAX

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Measurement Based Channel-Adaptive Video Streaming for Mobile Devices over Mobile WiMAX Hye-Soo Kim, Student Member, IEEE, Hyeong-Min Nam, Jae-Yun Jeong, Soo-Hyung Kim, and Sung-Jea Ko, Senior Member, IEEE Abstract — The channel bandwidth variation and the disconnection during handoff are the most critical problems which degrade the video quality in wireless video streaming. To cope with these problems, we propose an efficient video streaming method in this paper, which does not only dynamically adjust the video transmission rate based on the channel bandwidth, but also minimize the error propagation during handoff. Firstly, the channel bandwidth of the mobile worldwide interoperability for microwave access, called WiMAX, is estimated by analyzing channel parameters including the carrier to interference and noise ratio (CINR) and the handoff is detected by using the handoff occurrence message (HOM). Secondly, the streaming server adjusts the next transmission rate according to the estimated channel bandwidth to avoid the network congestion and performs the intra refresh method that inserts an intra frame (I-frame) right after handoff by using the HOM to reduce the error propagation effectively. Experimental results indicate that the proposed method can improve the performance of the video streaming over mobile WiMAX1. Index Terms — Wireless video streaming, channel-adaptive, handoff, mobile WiMAX.

I. INTRODUCTION Due to the explosive growth of the wireless multimedia communication services, there are increasing demands on real-time video streaming over the wireless systems. Recent advances in high-speed networks have made it feasible to provide real-time video streaming. Among the advanced wireless standards, WiMAX is an emerging wireless communication system that provides high-data rate as well as long-range coverage [1], [2]. The higher quality and seamless streaming in video transmission over the wireless network require to cope with the problems such as channel bandwidth variation, handoff, transmission error. Among those problems, the channel bandwidth variation and the handoff due to movement of the subscriber station (SS) are the most critical problems. The channel bandwidth variation causes the network congestion when the video transmission rate exceeds the channel bandwidth. In case of the mobile WiMAX, the adaptive modulation and coding (AMC) scheme from half-rate QPSK to 5/6 1 This research was supported by SAMSUNG ELECTRONICS CO., LTD. established by Network Adaptive Video Transmission Project. Hye-Soo Kim, Hyeong-Min Nam, Jae-Yun Jeong, and Sung-Jea Ko are with the School of Electrical Engineering, Korea University, Seoul, Korea (email: [email protected], [email protected], [email protected], [email protected]). Soo-Hyung Kim is with the Telecommunication R&D Center, Samsung Electronics, Suwon, Korea (email: [email protected]).

Manuscript received January 15, 2008

64-QAM offers various data rates to the SS according to the distance between the base station (BS) and the SS. In addition, the sudden disconnection due to handoff between BSs or sectors leads to errors in several frames because the error occurred in one frame would be propagated to the subsequent frames due to the prediction of the inter mode, which degrades the video quality significantly [3],[4]. SS1

BS

Video Input

Video Encoder Next Transmission Bitrate

Transmission Rate Control Insert I-frame

Intra Refresh

SS2 Display

RTP

Video Decoder

(Video Bitstream)

RTCP (Channel Bandwidth)

RTCP (HOM)

Streaming Server

Channel Parameters

Channel Bandwidth Estimation Hanoff Detection Streaming Client

Fig. 1. Concept of the proposed channel-adaptive video transmission

To address these problems, several methods for wireless video streaming have been proposed [5], [6]. The method proposed in [5] adjusted the transmission rate to the varying throughput of wireless 3G network. However, it requires the bandwidth estimation of wireless network and needs to consider the channel bandwidth in the mobile WiMAX to adapt the video transmission rate dynamically. In [6], the periodical random intra refresh and motion information-based conditional intra refresh methods were proposed to reduce the error propagation in error-prone channel. However, it is not an efficient way to reduce the error propagation caused by handoff latency in wireless network. In this paper, we propose a channel-adaptive video streaming method over mobile WiMAX, as shown in Fig. 1, which does not only dynamically adjust the video transmission rate based on the channel bandwidth, but also minimize the error propagation during handoff. Firstly, the current channel bandwidth is estimated by using channel parameters including the CINR. The estimated channel bandwidth is then exploited to determine the next video transmission rate, thereby avoiding the network congestion. Secondly, an efficient intra refresh method is proposed that inserts I-frame right after handoff by using the HOM to reduce the error propagation effectively. The rest of the paper is organized as follows. Section II presents the proposed measurement based channel-adaptive video streaming algorithm. Experimental results and conclusions are given in Section III and Section IV, respectively.

0098 3063/08/$20.00 © 2008 IEEE

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IEEE Transactions on Consumer Electronics, Vol. 54, No. 1, FEBRUARY 2008 Channel Parameter Measurement (Uplink) CINR

RPHY_UL

Handoff Detection

Handoff Detection

Determination of Weighting Factors: Overhead, Enviroment factor, # of users

Physical Data Rate Estiamtion

Channel Parameter Measurement (Downlink) CINR

CINR

RSSI

Available Bandwdith Estimation (Uplink), ) RUL = A ⋅ RPHY _ UL

RPHY_DL RTCP APP (HOM)

Intra Refresh CAIR

(

CARC

RSSI

Physical Data Rate Estiamtion

HOM

A

) ) ) R =min RUL , R DL

CINR

Determination of Weighting Factors: Overhead, Enviroment factor, # of users A

Available Bandwdith Estimation (Downlink), ) R DL = A ⋅ RPHY _ DL

RTCP ) APP ( R DL )

) Insert I-frame

) R,Target Bit Rate

RTP (Video Bitstream)

Video Encoder

Mobile WiMAX Network

Video Streaming Server

Video Decoder

Video Streaming Client

Fig. 2. Proposed channel adaptive rate control (CARC) and channel adaptive intra refresh (CAIR) methods.

Data rate in PHY layer (RPHY)

BS 1

BS 2

Channel bandwidth CINR

5/6 64 QAM 2/3 16QAM

the AB estimation, the physical data rate in the mobile WiMAX network is first estimated since the physical data rate and the capacity are interchangeable. For the WiMAX using the orthogonal frequency division multiple access (OFDM) and time division duplex (TDD), the physical data rate, RPHY (Mbps), is obtained using the system parameters [7] in Table I as follows:

1/2 QPSK

R PHY = D rate ⋅ bmod ⋅ c rate ,

Handoff MS location

Fig. 3. Relationship of MCS scheme, physical data rate, and CINR according to the distance between SS and BSs.

II. PROPOSED CHANNEL-ADAPTIVE VIDEO STREAMING Fig. 2 shows the proposed algorithm which consists of the channel adaptive rate control method and the channel adaptive intra refresh method. A. Channel Adaptive Rate Control (CARC) In video streaming over wireless network, the available bandwidth (AB) on the end-to-end path including both wired and wireless links is determined by the wireless link capacity since the wireless link commonly provides lower capacity than the wired one in most cases. We assume that the AB is affected only by the capacity of mobile WiMAX networks. For TABLE I SYSTEM PARAMETERS System Parameters

Value

Frequency band

2.3 GHz

Channel bandwidth

9 MHz

Duplex

TDD / 5 msec

DL and UP ratio

2:1

Multiple access

OFDMA

Cell coverage

1 Km

⎧1.8432 (Msubcarriers/sec), D rate = ⎨ ⎩ 3.6864 (Msubcarriers/sec),

if uplink,

(1)

if downlink,

where Drate is the data subcarrier rate when the ratio of the downlink (DL) to the uplink (UL) is 2, bmode is the modulation gain that bmode = 2 for QPSK, bmode = 4 for 16-QAM, and bmode = 6 for 64-QAM, and crate is the coding rate (bits/subcarrier). For example, if the current modulation and coding scheme (MCS) is 5/6 64-QAM, then the physical data rate (RPHY_DL) for DL is equal to 18.432 (=3.6864·(5/6)·log264) Mbps. Fig. 3 shows that the CINR is effectively used to estimate bmode·crate in the proposed algorithm. Next, we introduce a novel method of estimating the AB. In the mobile WiMAX network, RPHY is the theoretical upper bound of the AB because the AB is influenced by various network parameters such as the channel resource overhead, the number of users, and the weighting factor related to the ) different environments of the SS. Therefore, the AB, R , for both the DL and the UL is estimated as follows: ) (1 − Poverhead ) ⋅ (1 − C overhead ) ⋅ W env R= ⋅ R PHY , N user

(2)

where Poverhead represents the ratio of the packet overhead, Nuser denotes the number of users which is equal to 2 in our experiments, and Wenv is the weighting factor related to the

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H.-S. Kim et al.: Measurement Based Channel-Adaptive Video Streaming for Mobile Devices over Mobile WiMAX

environment of the SS. Coverhead in (2) is the ratio of the channel resource used for overhead to total channel resource in one frame considering the mobile WiMAX frame structure [7]-[9] as follows: ⎧ 0.3064, if UL, C overhead = ⎨ ⎩ 0.2394, if DL.

)

NGOP_org

NGOP_org

……

P

P

P

P

(3) Connection with BS1

P

I

P

P

Handoff Latency Packet Loss

P

NGOP_org

P

P

I

P

……

Error Propagation

Connection with BS2

(a)

In general, the propagation path [10] can be divided into two types, the line of sight (LOS) link and the non-LOS (NLOS) link. For the LOS link, a signal travels over a direct and unobstructed path from the transmitter to the receiver, while the signal reaches the receiver through reflections, scatterings, and diffractions for the NLOS link. Therefore, the received signals consist of components from direct paths, multiple reflected paths, scattered energies, and diffracted propagation paths. The type of the propagation path can be identified by the received signal strength indicator (RSSI). For the LOS (NLOS) link, the value of RSSI is normally greater (less) than a certain threshold, ThRSSI. For the experiments, we obtained the weighting factor that Wenv = 0.7 for the LOS link and Wenv = 0.4 for the NLOS link. ) In the proposed system, the appropriate R for the video transmission rate determination is obtained by considering both the AB of the UL in the streaming server and the AB of the DL in the streaming client. Therefore, the estimated AB of bidirectional links is determined as follows: ) ) ) R = min( R DL , R UL ),

173

(4)

)

where R DL and RUL represent the estimated AB for the DL and ) the UL, respectively. Once R is determined, the frame-layer rate control is performed to allocate the target bit rate to each frame [11]. B. Channel-Adaptive Intra Refresh (CAIR) Algorithm Before introducing the CAIR algorithm in detail, we briefly review the background of handoff in the mobile WiMAX network. A handoff is defined as the migration of a SS between air-interfaces of different BSs. In general, there are two types of handoff, soft handoff and hard handoff. The soft handoff uses a make-before-break approach, in which a connection to the next BS is established before an SS leaves an ongoing connection to a BS. The hard handoff employs a break-before-make approach, in which a connection is ended with a BS before it switches to another BS. The hard handoff is mandatory in the mobile WiMAX, which produces the longer latency than the soft one [12]. The handoff latency causes the loss of video data and propagates the error to the successive frames up to the next Iframe is received. Next, we propose a CAIR algorithm to tackle this issue. The handoff occurrence at the link layer is first detected using the value of CINR, and then an I-frame is inserted right after the handoff using the HOM.

NGOP_org

NGOP_org

……

P

P

P

P

Connection with BS1

P

I

P

Handoff Latency Packet Loss

P

NGOP_new

I

P

P

P

P

……

Inserted I-frame by HOM

(b) The lost frame The error propagated frame

Connection with BS2 BS: Base station HOM: Handoff occurrence message The correctly decoded frame

Fig. 4. Illustration of GOP structure. (a) Original GOP structure. (b) Proposed GOP structure using the CAIR.

We find out by experiments that the handoff is observed when the CINR value is less than a certain threshold, Thhandoff. In the handoff detection method, the SS monitors the variation of CINR and identifies that the CINR value is less than Thhandoff. Considering that the CINR value, c(t), reflects the MCS which represents the distance between the SS and the BS, the handoff decision function, H(t), can be defined as H (t ) = c (t ) − c (t − 1).

(5)

If H(t) > 0 and c(t) < Thhandoff , the handoff to the new BS is performed, otherwise, the association with the current BS is maintained. Therefore, the HOM can be expressed as ⎧ True, if H (t ) > 0 and c ( t − 1) < Thhandoff , HOM = ⎨ ⎩ False, otherwise.

(6)

After that handoff occurrence is detected, the CAIR algorithm is employed to reduce the error. Fig. 4 (a) shows the original GOP structure, where the several frames including the I-frame are lost during the handoff process and thus the decoding error is propagated to the successive frames up to the next I-frame is received [13], [14]. Fig. 4 (b) shows the result of the CAIR algorithm. Note that since an I-frame is inserted right after the handoff latency time, the quality degradation caused by the error propagation can be reduced. The target number of bits allocated to the new GOP is modified as follows: ) ) R (7) B GOP = N GOP _ new ⋅ , F

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IEEE Transactions on Consumer Electronics, Vol. 54, No. 1, FEBRUARY 2008 TABLE II PHYSICAL DATA RATE WITH CINR LEVEL

Home AAA

ACR

WiBro Core Network

Home Agent

Router

WiBro Coverage RAS1

Internet RAS2

PSS1 (Streaming Server)

PSS2 (Streaming Client)

ACR ACR: Access Control Router RAS: Radio Access Station PSS: Portable Subscriber Station AAA: Authentication , authorization and accounting, * BS: Base Station (ACR + RAS) * MS: Mobile Station (PSS)

Fig. 5. Experimental scenario in WiBro network.

CINR (dB)

Modulation

Coding Rate

RPHY_DL (Mbps)

RPHY_UL (Mpbs)

26

64-QAM

5/6

18.43

-

23

64-QAM

3/4

16.59

-

20

64-QAM

2/3

14.74

-

18

16-QAM

5/6

12.29

6.14

16

16-QAM

3/4

11.05

5.53

14

16-QAM

2/3

9.83

4.92

12

16-QAM

1/2

7.37

3.69

10

QPSK

2/3

4.91

2.46

6

QPSK

1/2

3.69

1.84

3

QPSK

1/3

2.46

1.23

1

QPSK

1/6

1.23

0.61

-1

QPSK

1/12

0.61

0.30

TABLE III NETWORK PARAMETERS

WiBro PCMCIA Card

(a)

Parameters

Value

ThRSSI

-60 dB

(b)

Fig. 6. Snapshot of the experimental test platform. (a) Environment of field test. (b) Implemented video streaming system.

) where B GOP is the estimated number of bits for the new GOP, F ) is the frame rate, R is the estimated AB using (4), and NGOP_new is the size of incoming GOP after handoff. The bit allocation scheme using (7), the CAIR algorithm can achieve the best video quality under a given channel condition.

Thhandoff

0 dB

Poverhead

0.026 (= 40 Bytes / 1500 Bytes)

6000

III. EXPERIMENTAL RESULTS

0.4 for NLOS

DL AB per user UL AB per user

5500 5000 4500

Bandwidth (Kbps)

In this section, the performance of the proposed algorithm is evaluated in the wireless broadband (WiBro). The WiBro is the mobile version of regular broadband, which is defined as a subset of the IEEE 802.16 standard and is developed based on the mobile WiMAX [15]. Fig. 5 illustrates the experimental environment in the WiBro network which consists of the portable subscriber station (PSS), the radio access station (RAS), the access control router (ACR), and so on. In Fig. 5, the PSS and the RAS are the same as the SS and the BS of the mobile WiMAX network, respectively. Fig. 6 shows the snapshot of the experimental platform. In Fig. 6 (a), the PSS is connected to the WiBro network in the 60Km/h speed vehicle. Fig. 6 (b) shows the implemented video transmission system. In order to evaluate the performance of the AB estimation in the CARC method, RPHY is first estimated using (1) with the relation between the measured CINR values and the MCS in the WiBro network. The MCS according to the CINR values and the corresponding RPHY are summarized in Table II. The network parameters for the AB estimation method in (2) are shown in Table III. Fig. 7 shows the measured maximum AB per user according to Nuser. In Fig. 7, we observe that the maximum AB per user proportionally increases when Nuser decreases from 4 to 2. It is also seen that the maximum AB per user in the DL (UL) is equal to 5.8 Mbps (2Mbps) when Nuser is 2. For the sake of the AB estimation using (2), Nuser is set to 2 in our experiments.

0.7 for LOS

Wenv

4000 3500 3000

2 users

2500

1 user

3 users 4 users

2000 1500 1000 0

20

40

60

80

100

120

140

160

Time (sec)

Fig. 7. Maximum AB per user according to the number of users. (a) Maximum DL AB per user. (b) Maximum UL AB per user.

Fig. 8 plots the RSSI values during 100 sec in both LOS and NLOS cases. We find that the values of RSSI measured in LOS are relatively greater than the values of RSSI measured in NLOS, therefore, RSSI is utilized to identify whether the current environment is LOS or NLOS. In the experiments, the average value of RSSI during the RTCP feedback period (1sec) is compared with ThRSSI to obtain Wenv. As shown in Table III, Wenv = 0.7 (Wenv = 0.4) for LOS (NLOS) is selected since we find that those values produce the best results through experiments.

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H.-S. Kim et al.: Measurement Based Channel-Adaptive Video Streaming for Mobile Devices over Mobile WiMAX -40

-40

Measured DL RSSI in LOS Measured DL RSSI in NLOS

-45

Measured UL RSSI in LOS Measured UL RSSI in NLOS

-45 -50

-50

-55

-60

RSSI (dB)

RSSI (dB)

175

ThRSSI = -60 dB

-55 -60

ThRSSI = -60 dB

-65

-65

-70

-70

-75 0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

Time (sec)

50

60

70

80

90

100

Time (sec)

(b)

(a)

Fig. 8. Measured RSSI of each link. (a) Measured DL RSSI. (b) Measured UL RSSI.

Measured DL CINR Actual DL AB Estimated DL AB

3000

15

2000

10

5

1000

5

0 100

0

6000

15

4000

10

2000

10

20

30

40

50

60

70

80

90

Bandwidth (Kbps)

20

20

0

25

4000

8000

0

Measured UL CINR Actual UL AB Estimated UL AB

5000

25

CINR (dB)

Bandwidth (Kbps)

10000

30

6000

30

0

10

20

30

40

50

Time (sec)

Time (sec)

(a)

(b)

60

70

80

90

CINR (dB)

12000

0 100

Fig. 9. Estimated ABs for each link. (a) Estimated AB for DL. (b) Estimated AB for DL.

Fig. 9 shows the comparison between the estimated AB using (2) and the actual AB. As shown in Fig. 9, the proposed AB estimation method well tracks the variation of the actual AB of both the DL and the UL. Therefore, the streaming server with the CARC algorithm correctly determines the next video transmission rate according to (4). Fig. 10 (a) shows the variation of CINR and the corresponding HOMs when Thhandoff is equal to 0. In Fig. 10 (a), HOMs generated at 21 and 64 sec indicate the DL handoff and the UP handoff, respectively. It is seen that the proposed approach using (6) well detects the handoff of both DL and UL. Thus, the CAIR algorithm can insert the I-frame right after the handoff.

For the performance evaluation of the proposed methods including the CARC and the CAIR methods, we perform the PSNR comparison of each method. In Fig. 10 (b), the video transmission rates for the each method are shown as compared with the estimated AB for both DL and UL. In Fig. 10 (c), the

“FOREMAN” sequence with 1880 frames of CIF format is encoded into an MPEG-4 bitstream with the video transmission rates of each method. As shown in Fig. 10 (c), the CARC method avoids the network congestion while the constant bitrate (CBR) method generates the network congestion around 20, 60, and 85 sec. It is seen that even though the average transmission rate of the proposed CARC method (= 1.49 Mbps) is greater than the one of the CBR method (= 1 Mbps), the proposed CARC method avoid the network congestion effectively as shown in Fig. 10 (c). To evaluate the CAIR algorithm, the PSNR comparison is performed between the proposed CAIR algorithm and the method proposed in [6], namely random intra refresh (RIR). In the RIR method, I-frame is inserted when the motion activity of a frame is greater than a certain threshold. In our simulation, the number of the inserted I-frames in the RIR method is 30. In Fig. 10 (c), the CAIR effectively reduces the error propagation caused by handoff around 21 and 64 sec, while the RIR does not.

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IEEE Transactions on Consumer Electronics, Vol. 54, No. 1, FEBRUARY 2008

35

Measured DL CINR Measured UL CINR

30

CINR (dB)

25 20 15 10

HOM

HOM 5

Thhandoff = 0 dB

0 10

20

30

40

50

60

70

80

90

Time (sec) (a) 7000

Estimated AB for DL Estimated AB for UL Video transmission rate for CARC Constant bit rate (CBR)

Transmission rate (Kbps)

6000 5000 4000 3000 2000 1000 0 10

20

30

40

50

60

70

80

90

Time (sec)

(b) 55 50

RIR

CAIR

45

CAIR

PSNR (dB)

40

CBR CBR+RIR CARC CARC+CAIR

35 30 25 20

Quality Degradation

Quality Degradation

15 10

(Network Congestion + Handoff Latency)

(Handoff Latency)

5 0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

1500

(Network Congestion) 1600

1700

1800

Frame Number

(c)

Fig. 10. Channel conditions and PSNR comparison. (a) Variation of the CINR and HOM. (b) Target bit rate. (c) PSNR comparison.

Table IV shows the performance comparison for 3 sequences with the average PSNR, the standard deviation (σ ) of PSNR, and packet loss ratio (PLR). It is clearly seen that the performance of the proposed method does not only improve the average PSNR, but also reduce PLR significantly for all test sequences. From σ of PSNR as shown in Table IV, the proposed method reduces the fluctuation of the video quality. These experimental results indicate that the proposed method provides the seamless and high quality video streaming over the WiBro network.

IV. CONCLUSIONS Due to the packet loss caused by the channel bandwidth variation and the handoff latency, the video quality degradation is critical problem in video streaming services in the wireless network. To solve this problem, we proposed the channel-adaptive video streaming methods which can not only adjust the video transmission rate based on the AB estimation

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H.-S. Kim et al.: Measurement Based Channel-Adaptive Video Streaming for Mobile Devices over Mobile WiMAX

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TABLE IV PERFORMANCE COMPARISON Test Sequence

FOREMAN

NEWS

MOBILE

Method

Average PSNR [dB]

σ of PSNR [dB]

Packet loss ratio (PLR)

CBR CBR+RIR CARC CARC+CAIR CBR CBR+RIR CARC CARC+CAIR CBR CBR+RIR CARC CARC+CAIR

26.63 28.04 35.08 36.60 30.05 34.08 36.72 38.99 19.80 21.48 24.56 27.24

10.40 9.97 5.89 3.93 10.13 9.95 6.49 5.41 6.53 6.30 4.98 3.18

0.219 0.212 0.022 0.023 0.220 0.214 0.025 0.027 0.219 0.222 0.025 0.024

of the mobile WiMAX network, but also minimize the error propagation due to the handoff latency. The combination of the CARC and the CAIR enables the proposed video streaming to minimize the video quality degradation in the mobile WiMAX network. Experimental results show that the proposed method provides the seamless and high quality video streaming over the mobile WiMAX network. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9]

[10] [11]

[12] [13]

K. H. Teo, Z. Tao, and J. Zhang, “The mobile broadband WiMAX standard,” IEEE Signal Processing Mag., vol. 24, pp. 144– 148, Sept. 2007. IEEE 802.16 TGe Working Document, (Draft Standard) - Amendment for physical and medium access control layers for combined fixed and mobile operation in licensed bands, 802.16e/D4, Aug. 2004 F. Ohrtman, WiMAX handbook, Building 802.16 wireless networks. New York, NY: McGraw-Hill, Jun. 2004. G. Dong and J. Dai, “An improved handover algorithm for scheduling services in IEEE8O2.16e,” IEEE Proc. Mobile WiMAX Symposium, pp. 25–29, Mar. 2007. J. W. Kim, H. M. Nam, S. J. Lee, J. Y. Lee, and S. J. Ko, “Probing-based channel adaptive video streaming for wireless 3G network,” IEICE Trans. Communications, vol. E89-B, no. 2, pp. 357-363, Feb. 2006. P. Haskell and D. Messerschmitt, “Resynchronization of Motion Compensated Video Affected by ATM Cell Loss,” ICASSP ’92, San Francisco, CA, vol.3, pp. 545–48. Mar. 1992. S. Cherry, “WiMax and Wi-Fi: separate and unequal,” IEEE Spectrum, vol. 41, no. 3, pp. 16–16, Mar. 2004. S. Shin, C. K. Kang, J. C. Kim, and S. H. Oh, “The Performance Comparison between WiBro and HSDPA,” IEEE Proc. Wireless Communication Systems, pp. 346–350, Sept. 2005. R. Lee, J. Kim, J. Yu, J. Lee, and D. Kim, “Capacity analysis considering channel resource overhead for mobile Internet access (WiBro),” Proc. the IEEE Int. Conf. Vehicular Technology Conference, pp. 3082–3086, Jun. 2005. WiMAX’s technology for LOS and NLOS environments, [online available]:http://www.wimaxforum.org/technology/downloads/WiMAX NLOSgeneral-versionaug04.pdf Y. Kim, J. Y. Pyun, H. S. Kim, S. H. Park, and S. J. Ko, “Efficient realtime frame layer rate control technique for low bit rate video over WLAN,” IEEE Trans. Consumer Electron., vol. 49, pp. 621– 628, Aug. 2003. S. F. Yang and J. S. Wu, “Handoff management schemes across hybrid WiMAX and Wl-Fi networks,” Proc. the IEEE Int. Conf. TENCON, pp. 1–4, Nov. 2007. J. W. Kim, S. Y. Jeon, H. S Kim, J. W. Yun, and S. J. Ko, “Seamless Video Streaming Technique Supporting Error Concealment for VOD Services in Vertical handoff,” IEICE Trans. Fundamentals., vol. E89A, no. 6, pp. 1571-1577, Jun. 2006.

[14] Q. Chen, Z. Chen, X. Gu, and C. Wang, “Attention-based adaptive intra refresh for error-prone video transmission,” IEEE Trans. Commun. Mag., vol. 45, pp. 52–60, Jan. 2007. [15] S. Q. Lee, N. Park, C. Cho, H. Lee, and S. Ryu, “The wireless broadband (wibro) system for broadband wireless internet services,” IEEE Trans. Commun. Mag., vol. 44, no. 7, pp. 106–112, Jul. 2006.

Hye-Soo Kim received the B.S. and M.S. degrees in electronics engineering from the Department of Electronics Engineering at Korea University, in 2002 and in 2004. He is now the Ph.D candidate in the Department of Electronics Engineering at Korea University. His research interests are in the areas of Fast Handoff, IEEE 802.11, IEEE 802.16, 3G cellular network, NGN, Mobile QoS, IP QoS, video signal processing and multimedia communications.

Hyeong-Min Nam received the B.S. degree in Electronics Engineering from Korea University in 2004. He entered the Multimedia Communication Processing Lab in the Department of Electronic Engineering of Korea University, in 2005. He is now a Ph.D. candidate at Korea University. His interests are wireless video, QoS, video signal processing, and multimedia communication.

Jae-Yun Jeong received the B.S. degree from Korea University in the Department of Electric Electronics and Radio, in 2005. He entered the Multimedia Communication Processing Lab in the Department of Electronic Engineering of Korea University, in 2005. He is now a Ph.D. candidate at Korea University. He has currently focused on Wireless QoS, video signal processing and multimedia communication processing.

Soo-Hyung Kim received the diploma in electrical engineering from the Kwangwoon University, Korea in 1998. Since joining Samsung Electronics in 1998, he has worked as engineer in various multimedia transmission related research, standardization. He currently is a research engineer whose main area of interest is multimedia service delivery over mobile networks. The focus of his current work is on mobile broadcast services.

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IEEE Transactions on Consumer Electronics, Vol. 54, No. 1, FEBRUARY 2008

Sung-Jea Ko received the Ph.D. degree in 1988 and the M.S. degree in 1986, both in Electrical and Computer Engineering, from State University of New York at Buffalo, and the B.S. degree in Electronic Engineering at Korea University in 1980. In 1992, he joined the Department of Electronic Engineering at Korea University where he is currently a Professor. From 1988 to 1992, he was an Assistant Professor of the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn. From 1986 to 1988, he was a Research Assistant at State University of New York at Buffalo. From 1981 to 1983, he was with Daewoo Telecom where he was involved in research and development on data communication systems. He has published more than 350 papers in journals and conference proceedings. He also holds over 20 patents on data communication and video signal processing. He is currently a Senior Member in the IEEE, a Fellow in the IEE and a chairman of the Consumer Electronics chapter of IEEE Seoul Section. He has been the Special Sessions chair for the IEEE Asia Pacific Conference on Circuits and Systems (1996). He has served as an Associate Editor for Journal of the Institute of Electronics Engineers of Korea (IEEK) (1996), Journal of Broadcast Engineering (1996 - 1999), the Journal of the Korean Institute of Communication Sciences (KICS) (1997 - 2000). He has been an editor of Journal of Communications and Networks (JCN) (1998 - 2000). He received the Academic Research award from Korea University (2004). He is the 1999 Recipient of the LG Research Award given to the Outstanding Information and Communication Researcher. He received the Hae-Dong best paper award from the IEEK (1997) and the best paper award from the IEEE Asia Pacific Conference on Circuits and Systems (1996).

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