A H.264 Based Joint Source Channel Coding Scheme Over Wireless Channels

8/12/2019 A H.264 Based Joint Source Channel Coding Scheme Over Wireless Channels

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A H.264 Based Joint Source Channel Coding Scheme over Wireless Channels

Xuejuan Gao, Li Zhuo, Suyu Wang, Lansun ShenSignal & Information Processing Lab, Beijing University of Technology, Beijing, 100022, China

[email protected]

Abstract

Joint source channel coding (JSCC) is an effective

method which trade off the efficiency and the quality of

the video transmission. In this paper, a new rate-

quality (R-Q) model is first proposed to represent the

coding characteristics of H.264 instead of rate-

distortion (R-D) model. Then, the end-to-end videotransmission distortion is analyzed and an adaptive

JSCC over wireless channel based on the R-Q model

of the H.264 and the error protection characteristics of

the Turbo code is proposed, which can optimize the

rate allocation of the available network bandwidth

between source coding and channel coding according

to the current status of the wireless channels, so as to

improve the robustness. The experiment results

indicate that, compared with the scheme using the

fixed channel coding rate, under the same channel

conditions, our proposed JSCC scheme can greatly

improve the transmission robustness and achieve

better reconstructed video quality at the receiver.

1. Introduction

Joint source channel coding (JSCC), an effective

coding method, can minimize the end-to-end

transmission distortion by optimizing the bit rate

allocation between source encoder and the channel

encoder or between different parts of source encoder.

JSCC has been studied for many years. Therefore,

there are a lot of literatures [1-3]: ZhiHai He et al

proposed a joint source channel rate-distortion (R-D)

analysis method [4], where an analytic solution for

adaptive intra mode selection and joint source-channelrate control based on the R-D model has been

developed. Zhang et al developed a MPEG-4 PFGS

coding method based power-optimized joint source-

channel coding method over wireless channel [5],

which reduces total power consumption based on the

proposed end-to-end power-optimized architecture.

Although those schemes adopted different source or

channel coding method, they all optimize the source

and channel rate allocation based on the source R-D

model and channel transmission distortion model in

essence.

In this paper, instead of using R-D model to

perform rate control as many existing methods do, we

propose a new rate-quality (R-Q) model. If use PSNR

(Peak Signal to Noise Ratio) as the measurementmetric, we find that there is a conic relationship

between video quality Q and log(R), QP and log(R),

no matter it is an I frame or a P frame. So we first set

up a novel R-Q model of H.264. Then the end-to-end

video transmission distortion is analyzed and an

adaptive JSCC over wireless channel based on the R-Q

model and the error protection characteristics of the

Turbo code is proposed, which can optimize the rate

allocation of the available network bandwidth between

source coding and channel coding adaptively

according to the actual condition of wireless channel,

so as to improve the robustness of the video

transmission. The experiment results indicate that ourproposed JSCC scheme can greatly improve the

transmission robustness and achieve better

reconstructed video quality compared with the JSCC

scheme using the fixed channel coding rate.

2. Proposed R-Q model of H.264 encoder

H.264 coding standard supports two kinds of

coding modes: Intra and Inter [6], which render quite

different R-Q behaviors. For the Inter coding mode,

the prediction of current coding MB will refer to one

or several previous frames, while the prediction for the

Intra coding mode only refers to the adjacent MBs inthe current frame.

To analyze the R-Q performance of the H.264

encoder, we performed a lot of experiments on various

video sequences with different motion characteristics

and different format. Each test video sequence includes

300 frames. While testing the R-Q behavior of I frame,

we set all frames as I frame. For the P frame, we adopt

GOP as the coding structure. That is, the first frame of

International Conference on Intelligent Information Hiding and Multimedia Signal Processing

978-0-7695-3278-3/08 $25.00 2008 IEEE

DOI 10.1109/IIH-MSP.2008.30

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prediction coding mode, channel bit error will cause

error propagation. Therefore, error concealment

methods are usually exploited to restrict error

propagation. LetPebe the channel bit error rate (BER),

the expected average ofDS+C(n)is defined as:

)n(DP)n(D)P()n(D ereSeCS +=+ 1 (3)

where DS(n) represents the distortion between thereconstructed picture and the original picture without

bit error, Der(n) represents the distortion between the

reconstructed picture after error concealment and the

original picture if the channel errors occur. In terms of

the characteristic of Turbo code,Pecan be formulated

as follows [7]:

0

02

1 NEr

be

b

eNr

E

r

P =

(4)

Note that Eb is the power of every signal, N0 is yawp

power of channel and ris bit rate of channel coding.

If we assumeF(n,i)to be the original value of pixel

i in the nth frame, inF , the construction value of

pixel i at the encoder side and i,nF~ the

reconstructed pixel i at the decoder side, then DS(n)

andDer(n)can be given respectively:2

)i,n(F)i,n(FE)n(DS =

2

)i,n(F~

)i,n(FE)n(Der = (5)

Due to the different coding mode of I frame and P

frame, we need to analyze them separately. For I frame,

if there are bit errors occurred, we use the MB at the

same position in the n-1 th frame to replace the

corrupted one. Then we will have:2

1 )i,n(F~

)i,n(F)n(Der =

2

1 )i,n(F~)i,n(F)i,n(F)i,n(FE += (6)

Because of the uncorrelated characteristics of

source distortion and channel distortion, (6) can be

changed into:

}|)i,n(F~

)i,n(F{|E}|)i,n(F)i,n(F{|E)n(D 22er 1+=

}|)i,n(F~

)i,n(F{|E)n(D 2S 1+= (7)

Then the expected average ofDS+C(n)of I frame is:

}|)i,n(F~

)i,n(F{|EP

}|)i,n(F)i,n(F{|EP)n(D)n(D

2

e

2

eSCS

11

1

+

+=+ (8)

Note that DS(n) can be obtained from the R-Q

model of (1), 21 )i,n(F)i,n(FE represents the mean

square error of the construction picture between the

nth frame and the n-1th frame at the encoder side and2

11 )i,n(F~

)i,n(FE which describes the source

distortion of the n-1th frame, can be obtained in

reference [4].

For P frame, if there are no bit errors, the

construction value at the receiver can be described

as )n(e)j,n(F~

i,nF~

1 , where j is the position

of pixel i in the n-1 th frame according to the motion

vector (MV) and )n(e is the quantization value of

prediction error. Otherwise, if there are bit errors, we

use the same error concealment method as I frame.

Then the expected average of DS+C(n) of P frame is

given by:

{ } { }222

11

111

)i,n(F)i,n(FEP)i,n(F)i,n(FEP

)j,n(F~

)j,n(FE)P()n(D)n(D

ee

eSCS

++

+=+ (9)

Note that { })j,n(F 1 represents the reference frameof motion compensation and

2

11 )j,n(F~

)j,n(FE

the mean square error of reference frames of motion

compensation between the encoder end and the

decoder end, which can be obtained in reference [4].

3.2. The optimal rate allocation of JSCC

If we assume the frame rate of H.264 encoder is F(fps) and use second as the basic rate allocation unit,

theDS+Cin (2) can be given by:

=

++ =

F

n

CSCS nDF

D1

)(1 (10)

We can obtainDS+C(n)from (8) or (9) according to

different coding mode. Apparently, (2) is an

optimization problem with the restriction conditions,

whose optimal answers areRS*andRC*. Let Rbe the

total bit rate of channel bandwidth. If consider the

relationship among the coding rate r of Turbo code,RS

and R : r=RS/R , then RrRS = RrRC = 1 .

Therefore, (2) is transformed to find only one optimalr* to minimize the DS+C, which can use Lagrange

optimization algorithm to search.

4. Experiment results and analysis

To illustrate the effectiveness of our proposed JSCC

scheme, we performed experiments on a lot of

different video sequences (both CIF and QCIF format)

under various channel condition. The compared

method is fixed channel coding rate (r=1/2) method. In

this paper, the channel coding rates of Turbo code

include r={2/3,1/2,1/3}. Each test video sequence

includes 300 frames using GOP as the codingstructure. Each GOP includes 15 frames with a

structure of {I,P,P,P...}.

Figure 4 shows the comparison results with

different channel bandwidth and BER. Figure 5 shows

the comparison results of the reconstructed quality of

two sequences under different channel bandwidth and

BER. It can be seen clearly from Figure 4 and Figure 5

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(a) Adaptive rate allocation JSCC method

(b) Fix rate allocation JSCC method

Figure 6. The reconstructed pictures

(a) BER 10

-4, foreman QCIF format sequence

(b) BER 10-5

, news CIF format sequence

Figure 4. Comparison of reconstructedquality with different total bit rate

(a) BER 10-5

, total bit rate 240kbps, akiyo sequence

(b) BER 10-4

, total bit rate 450kbps, mobile sequence

Figure 5. Comparison of reconstructed quality

that compared with the fixed channel coding rate

scheme, our proposed one can achieve a higher

reconstructed quality of 1~2dB at the receiver side.

Figure 6 shows the reconstructed pictures of different

sequences (CIF format), where BER is 10-3 and

available channel bandwidth is 150kbps. Figure 6

illustrates that our proposed method can also achieve abetter reconstructed video quality. Tests over other

video sequences yielded similar results.

5. Conclusion

In this paper, we first propose a novel R-Q model of

H.264. Then, the end-to-end video transmission

distortion is analyzed and an adaptive JSCC over

wireless channel based on the R-Q model and the error

protection characteristics Turbo code is proposed,

which can optimize the rate allocation of the available

bandwidth between source coding and channel coding

adaptively according to the actual condition of currentwireless channel. The experiment results indicate that

the proposed JSCC scheme can greatly improve the

transmission robustness and achieve better

reconstructed video quality.

6. Acknowledgments

This work was supported by NSFC (60772069), the

Beijing Novel Program (2005B08).

7. Reference

[1] Robert E. Van Dyck, David J, Transport of WirelessVideo Using Separate, Concatenated and Joint Source-

Channel Coding,Proceedings of the IEEE, VOL. 87, NO.10,

Oct. 1999, pp.1734-1750.

[2] Fang Zhijun, Xu Shenghua, et al, Joint Source-Channel

Coding for MPEG-4 Streams Transmission Over 3G

Networks, Wireless Communications, Networking and

Mobile Computing, 2005. Proceedings, Volume 2, 23-26

Sept. 2005 Volume: 2, pp.1261-1264.

[3] Feng Wang, Guangxi Zhu, Zhenming Zhang, et al, Joint

Source-Channel Rate Allocation and Unequal Error

Protection for Dependent Video Transmission, Wireless

Communications, Networking and Mobile Computing, 2005.

Proceedings, Volume 2, 23-26 Sept. 2005, pp.1275 -1280.

[4] Zhihai He,Jianfei Cai, Chang Wen Chen,Joint SourceChannel Rate-Distortion Analysis for Adaptive Mode

Selection and Rate Control in Wireless Video Coding,IEEE

Transactions on circuits and systems for video

technology,VOL.12,NO.6,June. 2002, pp. 511-523.

[5] Qian Zhang, Wen Wu Zhu et al, A power-optimized

joint source-channel coding for scalable video streaming

over wireless channel, IEEE International Symposium on

Circuits & Systems, Sydney, Australia, 2001, pp. 510-513.

[6] Thomaswiegand, Gary J. Sullivan, Gisle bjntegaard, et

al, Overview of the H.264/AVC Video Coding Standard

IEEE Transactions on circuits and systems for video

technology, VOL. 13, NO.7, JULY .2003, pp. 560-576.

[7] Liu Donghua, Theory and application of Turbo code,

Publishing House of Electronics Industry, Beijing, Jan. 2004

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A H.264 Based Joint Source Channel Coding Scheme Over Wireless Channels