University, California, USA. ABSTRACT ... gain in PSNR is obtained with an overall rate of ½ over ... new UEP scheme that uses equal rate convolutional.
AN UNEQUAL ERROR PROTECTION SCHEME EMPLOYING CONVOLUTIONAL CODES AND ASYMMETRIC 8PSK MODULATION FOR ROBUST TRANSMISSION OF H.264/AVC VIDEO IN WIRELESS CHANNELS M.A. Hosany* *
S. Kumar**
S. Nagaraj**
Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Mauritius, Mauritius
**
Department of Electrical and Computer Engineering, School of Engineering, San Diego State University, California, USA
ABSTRACT In this paper, it is proposed to design and implement a physical layer Unequal Error Protection (UEP) scheme based on convolutional codes and asymmetric 8PSK modulation. This scheme is combined with the UEP schemes at the application layer that is, multi-level unequal importance of compressed H.264/AVC video data. The proposed scheme takes the prioritized H.264 video data and encodes them with equal coderate convolutional codes as well as maps them to the asymmetric 8PSK constellation. In the mapping process, the Most Significant Bit (MSB) is given to the highest importance of the H.264 video data whilst the Least Significant Bit (LSB) is mapped to the lowest importance of the video. It is shown through simulation results that this proposed UEP scheme outperform the Equal Error Protection (EEP) scheme employing equal convolutional codes and symmetric 8PSK modulation. A 7 dB coding gain in PSNR is obtained with an overall rate of ½ over the uncoded modulation, both at a value of beta =0.48 and CNR = 18dB. 1. INTRODUCTION The increasing demand in multimedia services requires new robust transmission schemes to be designed for video data over wireless channels. Transmission errors in the compressed video bitstream may result in an undecodable string of bits due to the extensive use of variable length coding. Moreover, these transmission errors may result in severely degraded or even non decodable video due to error propagation within the frames directly hit by these errors and also in the subsequent predicted frames [1]. Thus, different types of error resiliency schemes are used in video compression to reduce the effect of transmission. Examples of such schemes include data partitioning, layered coding, reference frame selection, Flexible Macroblock Ordering (FMO) in H.264/AVC video coding standard [2,3]. In order to minimize the effects of transmission errors on the reconstructed video image quality, Unequal Error Protection (UEP) schemes can be used [4]. UEP is based on the idea that the more important video data is given higher protection at the cost of the less important data. For example, the picture header and motion vectors are much more important than the texture data. The reconstructed video quality will be severely degraded
when errors occur on the important bits. Thus, these important bits should have a higher protection order than the rest of the video bit-stream. At the physical layer, UEP is achieved by using Forward Error Correction codes with different coderates and hierarchical modulation where each mapped symbol is represented by the Most Significant Bit (MSB) and the Least Significant Bit (LSB), thus creating unequal error protection at bit level [5]. In [6], Chang et al. used hierarchical QAM in UEP for robust transmission of H.264/AVC video data and another hierarchical modulation was also proposed in terrestrial video broadcasting [7]. The transmission of H.264 video data was done by applying Trellis-Coded Modulation (TCM) and hierarchical QAM in [8]. Major focus has been laid on using hierarchical QAM for the transmission of H.264/AVC video data. However, QAM has differential gain in mutli-path fading and high Bit Error Rates (BER). Digital phase modulation or PSK modulations have constant envelopes and do not require the knowledge of channel gains for optimal demodulation. Thus PSK is more robust than QAM in multipath fading environment. In [9], Lu et al. designed an asymmetric 8-PSK scheme, and mapped the image and audio data to different bits of asymmetric 8-PSK based on differential priority over fading channels. In [10], UEP is established both at the application layer and physical layer by using H.264 source data priorities according to their relative importance and asymmetric 8- PSK modulation. It is shown that this combination provides graceful degradation of reconstructed data during short deep fades in a point to point wireless communication system. In this paper, we propose a new UEP scheme that uses equal rate convolutional codes and asymmetric 8PSK modulation at the physical layer as an extension to the work done by Anuj [10]. The unequal levels of importance of H.264/AVC video data are applied to equal rate convolutional codes and mapped onto the unequally protected asymmetric 8-PSK signal constellation such that the MSB have a lower probability of being in error than the LSB. This paper is organized as follows. Section 2 briefly introduces the H.264/AVC standard with its UEP property. Section 3 outlines the use of convolutional codes and asymmetric 8-PSK modulation in UEP. In section 4, we describe fully the
processes involved in the design and implementation associated with our work. Section 5 presents the experimental set-up and simulation results as well as discussions for various convolutional code rates with asymmetric 8 PSK modulation applied to the prioritized H.264/AVC video data in UEP and section 6 concludes the paper. 2. H.264 Advanced Video Coding (AVC) in Unequal Error Protection The H.264/AVC video coding standard [2,11], proposed by the Joint Video Team (JVT) of ITU-T and ISO/IEC, achieves a significant improvement in the compression efficiency over the other existing standards. This makes H.264 AVC a favorable candidate for all future multimedia applications. The H.264/AVC standard is composed of two layers namely the Video Coding Layer (VCL) for video compression and Network Abstraction Layer (NAL) for transport of compressed video data over networks [11]. NAL works in two kinds of mode: Single Slice mode and Data Partition mode. When using Data Partition mode, H.264 puts all variable length codes with the same data type together in each frame [11]. Head information includes head information, macroblock type, frame type, predicted residual of motion vectors, frame flag and this part is called Data Partition A (DP A), which is the most important part. Intra-frame segmentation is called Data Partition (DP B). It loads the coding mode and the correlation coefficient in intra frame blocks. Compared with information of inter-frame data partitions, intra-frame information can prevent further drift, thus it is more effective than inter-frame data partitions. Inter-frame segmentation is called Data Partition C (DP C). It only includes the coding mode and the correlation coefficient in inter-frame block; it is the biggest segmentation in the video stream. Without receiving the DPA data of a slice correctly, DP B and DP C packets cannot be decoded, thereby discarding the whole slice data. Whereas if a DP C is lost, then the slice can be decoded using the received DP A and DP B information [2,10,11]. The output of the H.264/AVC source can be organized in packets of varying importance, depending on the frame type, DP type and slice group. Therefore we can exploit the unequal importance of video data at the application layer by packetizing all the important data together, prioritizing them accordingly and give more protection to them [10]. 3. Convolutional modulation
Codes and Asymmetric 8PSK
A binary convolutional encoder takes a stream of information bits and converts it into a stream of transmitted bits using a shift register bank. A (n,k,m) convolutional code can be implemented with k-input information bit, n-output sequential circuit of input memory m. The n encoder outputs at a given time unit depends not only on the k input bits at that time but also on the m previous input block. Typically, n and k are
small integers with k 0.46 perform better than the corresponding schemes with beta =0.5. Figs. 6 and 7 illustrate the PSNR curves against beta for the UEP schemes employing different overall rates at a high value of CNR of 28 dB. Again here, it can be seen that the UEP schemes, based on overall rates of 1/2, 2/3, 3/4 and 4/5, at beta values > 0.46 perform better than the corresponding scheme at beta =0.5. PSNR v/s beta for BUS CIF sequence 18.5 18
Asymmetric
Symmetric
17.5 PSNR (dB)
Table 4: PSNR values for overall coderate 3/4 and 8PSK modulation
17 16.5
CNR (dB)
0.44
0.46
0.48
0.5
10dB
14.6
14.5
14.4
14.0
16
12dB
15.7
15.8
15.6
15.3
15.5
14dB
16.9
17.0
16.9
16.7
16dB
18.4
18.9
18.4
18.2
18dB
19.8
19.8
19.8
19.7
20dB
21.5
21.5
21.4
21.4
22dB
23.3
23.4
23.5
23.4
24dB
25.2
25.4
25.5
25.7
26dB
26.8
27.1
27.3
27.3
28dB
27.9
28.1
28.2
28.2
15 0.42
0.44
0.46
0.48
0.5 beta
CNR =10dB, overall rate 1/2 CNR =10 dB, overall rate 2/3
Fig. 4: PSNR curves against beta for overall coderates 1/2 and 2/3 at CNR 10 dB.
PSNR v/s beta for BUS CIF sequence
15 14.8 14.6
PSNR (dB)
14.4 14.2 14 13.8 13.6 13.4 13.2 13 0.42
0.44
0.46
0.48
0.5
beta
CNR =10dB, Overall rate 3/4 CNR =10dB, overall rate 4/5
Fig. 5: PSNR curves against beta for overall coderates 3/4 and 4/5 at CNR 10dB. Fig. 7: PSNR curves against beta for overall coderate 3/4 and 4/5 at CNR 28 dB.
PSNR curves for Bus (CIF) sequence (NAL 200 bytes) 30 28 26 24 PSNR (dB) 22 20 18 16
Fig. 6: PSNR curves against beta for overall coderate 1/2 and 2/3 at CNR 28dB.
14 12 10 12 14 16 18 20 22 24 26 28 30
Fig. 8 shows the performance curves, at beta =0.48, for various coderates employing equal rate convolutional codes as well as for the uncoded case, which is without the use of FECs. It can be clearly seen that the overall rate ½, based on equal ½ rate convolutional code, gives significant coding gain of around 7 dB over the uncoded asymmetric modulation at a CNR of 18 dB. The coding gains for the overall coderates of 2/3 and ¾ are approximately 5 and 3 dB respectively at the same value of CNR. This reduction in coding gain can be explained by the fact that the convolutional coderate is increased and hence the UEP scheme becomes less powerful.
CNR (dB) Overall coderate 1/2
Overall coderate 2/3
Overall coderate 3/4
Uncoded
Fig. 8: PSNR curves for various coderates and uncoded asymmetric 8PSK modulation at beta=0.48 in Rayleigh and AWGN channels
6. CONCLUSIONS An unequal error protection scheme employing convolutional codes and asymmetric 8PSK modulation has been designed and implemented and UEP is exploited through the asymmetric modulator. This scheme is combined with the H.264 prioritized video data at the application layer. It has been shown through simulation
results that the UEP scheme performs better than an EEP scheme employing equal rate convolutional code and symmetric 8PSK modulation. Significant coding gain of around 7 dB is obtained for a UEP scheme employing equal ½ rate convolutional code and asymmetric 8PSK over the uncoded case at beta =0.48 and CNR =18 dB.
REFERENCES [1]
Abdul H Sadka, Compressed Video Communications, John Wiley and Sons, 2002. pp 121-172. [2] “Draft ITU-T recommendation and final draft international standard of joint video specification (ITU-T Rec. H.264/ISO/IEC 14 496-10 AVC,” in Joint Video Team (JVT) of ISO/IEC MPEG and ITU-T VCEG, JVTG050r1, 2003. [3] T. Wiegand, G. J. Sullivan, G. Bjøntegaard and A. Luthra, “Overview of the H.264/AVC video coding standard,” IEEE Trans. Cir. Syst. Video Technol., vol. 13, pp. 560–576, July 2003. [4] W. H. Heinzelman and R. Talluri, “Unequal error protection of MPEG-4 compressed video,” Proc. International Conference of Image Processing, Vol. 2, pp 530-534, 1999. [5] L.-F. Wei, “Coded modulation with unequal error protection,” IEEE Trans. Communications, Vol 41(10), Oct 1993, pp. 1439-1449 [6] Y. C. Chang, S. W. Lee and R. Komiya, “A low complexity unequal error protection of H.264/AVC video using adaptive hierarchical QAM,” IEEE Trans. Consumer Electronics, Vol. 52(4), Nov 2006, pp. 1153-1158 [7] K. Ramchandran, A. Ortega, K.M. Uz and M. Vitterli, “Multiresolution broadcast for Digital HDTV using Joint Source/Channel Coding”, IEEE Journal on Selected Areas in Communications, vol. 11(1), Jan 1993, pp. 6-23. [8] Songchar Jiang, Lin, H, Tsou S.K,” A new unequal error protection scheme for wireless multimedia transmissions”, TENCON 2007 – 2007 IEEE Region 10 Conference, Oct. 30 2007, pp. 1-4. [9] J. Lu, A. Annamalai Jr., and D. R. Vaman, “Reducing Signal Distortion Due to Transmission Error via Multi-resolution Digital Modulations”, Wireless Telecommunications Symposium, April 2008, pp 360- 369. [10] A. Bhatnagar, “Multi-level unequal protection scheme for robust H.264 video transmission over wireless channels”, M.S.E.E Thesis, Department of Electrical and Computer Engineering, College of Engineering, San Diego State University, August 2009, California, USA. [11] S. Kumar, L. Xu, M. K. Mandal and S. Panchanathan, “Error Resiliency Schemes in H.264/AVC Video Coding Standard,” Elsevier Journal of Visual Communication and Image Representation (Special issue on Emerging H.264/AVC Video Coding Standard), Vol. 17(2), pp. 425-450, April 2006.
[12] A. Viterbi, "Convolutional Codes and Their Performance in Communication Systems," IEEE Transactions on Communication Technology, Volume 19, Issue 5, Part 1, pp. 751-772, Oct. 1971. [13] Lin S., Costello D., “Error Control Coding: Fundamentals and Applications” Prentice-Hall, Englewood Cliffs, N.J., 1983. [14] P.Vitthaladevuni and M. Alouini, “Exact BER computation of generalized hierarchical PSK constellations,” IEEE Transactions on Communications ,Vol. 51, pp. 2030-2037, Dec. 2003. [15] J. Hagenauer, "Rate-compatible punctured convolutional codes (RCPC codes) and their applications," IEEE Transactions on Communications, Volume 36, Issue 4, pp. 389-400, Apr. 1988. [16] L. H. C. Lee, "New rate-compatible punctured convolutional codes for Viterbi decoding," IEEE Transactions on Communications, Volume 42, Issue 12, pp. 3073-3079, Dec. 1994.
