James She, Ph.D. Research Fellow, Computer Laboratory

1. Coded Wireless Video Broadcast / Multicast:A Cross-layer Framework With Protections To Harvest The True Potential of 4G Access Networks James She, Ph.D. Research Fellow, Computer Laboratory Presentation @ The Chinese University of Hong Kong, Hong Kong – Jan 2011 1

2. Outline • Introduction & Background • A Preliminary Cross-layer Design • Coded Wireless Video Broadcast/Multicast • An Information-theoretical Bound of Expected Distortion • Conclusion & Future Work 2

3. 4G/Broadband Wireless Access and 1-to-many/all Video Applications

4. 1. Multi-user channel diversity: • Rate is limited to receiver with the worst channel  low video quality Wireless Broadcast/Multicast and Problems In a single-hop wireless network: • efficient use of spectrum • higher system scalability • 2. Error Control: • Retransmission  Not efficient or scalable 4

5. Research Objectives • Limitations of Existing Cross Layer Designs (CLDs): • Many for unicast are not applicable • Some for multicast/broadcast using erasure/network codings: • Some statistical number of receivers within a multi/broadcast group • Multi-hop wired/wireless infrastructure Research Objectives: Practical and generic cross-layer frameworks (advanced source + channel coding) for single-hop network Fundamental understanding of the proposed frameworks, using information theory Possible implementations 5

6. Outline • Introduction & Background • A Preliminary Cross-layer Design • Coded Wireless Video Broadcast/Multicast • An Information-theoretical Bound of Expected Distortion • Conclusion & Future Work 6

7. A preliminary cross-layer design -Superposition Coded Multicast e.g., 2 layered video data (basic + enh. qualities) layered broadcast signal layer 1 (BPSK) layer 2 (QPSK) Encoding: superimpose two modulated signals (i.e., vector additions: x1 + x2 x ) Decoding, y: decode the lower order signal (BPSK), y1, from received signal, y substract it from y for decoding y2.(QPSK)(i.e., y- y1 y2.) … 7 … … • Layered Channel (Superposition coding): • Multi-resolution modulated (layered) broadcast signals • Scalable Video Source (MPEG4/ H.264AVC): • Bitstream with successive refinable layers … …

8. Superposition Coded Multicast (SCM) Base station 2 quality layers (base & enhancement) Receiver(s) Novelty:exploits the layered properties in scalable source and multi-resolution channel BS only broadcasts/multicasts a single type of radio signals that contains all layers decodable by receivers at various channel levels for multiple rate of video delivery.

9. Simulation Results • Compare achievable video qualities (PSNR): • Normal Multicast vs. SCM • PS: ‘Normal’ uses the rate everyone supports poor receiver (low SNR avg.) good receiver (high SNR avg.) Conclusion: Higher video quality regardless of the avg. channel SNR of a receiver! 9

10. An limitaiton: • Video quality fluctuates with channel condition at a receiver regardless of the SNR avg.  Error control problem! SCM Summary • Two critical components identified: • Scalable video (source) • Multi-resolution modulation (channel) • Resolved multi-user channel diversity + video quality improvement. 10

11. Outline • Introduction & Background • A Preliminary Cross-layer Design • Coded Wireless Video Broadcast/Multicast • An Information-theoretical Bound of Distortion Bound • Conclusion & Future Works 11

12. Proposed - Coded Wireless Video Broadcast/Multicast • Deal with error control & multi-user channel diversity: • Introduced protectionsto each successive layer at the source • Achievable by modifying the Multiple Description Coding based on Reed Solomon RS(N, K) [18] Note: For any layer l, a smaller Klvalue, the higher robustness to tolerate fading duration for that layer. • Each MDC/protected packet (with multiple layers of bitstreams) is sent through SCM as a multi-resolution modulated signal [18] P. A. Chou, H. J. Wang, and V. N. Padmanabhan, “Layered multiple description coding,” Proc. PV 13th Int. Packet Video Workshop, Nantes, France, Apr. 2003. 12

13. Scalable Error Controls: Receiver recovers its own lost bitstreams of layer l when successfully received any Kl “partial” MDC packets of layer l. System Model And Error Control Advantages 13

14. A Quick Video (00:00:51-00:02:05)

15. Formulations For Analysis Performance/video quality measurement: Total received/recovered bitstreams, Tm, of a GoF by a receiver m. • Prob. of receiving/recovering a layer l by receiver m (i.e., receiving at least Kl partial packets of layer l by receiver m) • With the layers dependency, the amount of received/ recovered bitstreams of a layer l in a GoF: layer l Total received/recovered bitstream of a GoF: 15

16. SS-1 Optimized & Experimental Results • Compare layered broadcast w/o protection (e.g., SCM) and the proposed one: • 2 layers w/ optimized (searched) parameters • 2 different standard video sequences (Foreman and Paris) Note: SS-1: lowest SNR avg. SS-10: highest SNR avg. (Foreman) • Coded Wireless Video Broadcast/Multicast • better video quality even in a poorer channel • smaller quality difference between receivers with highest and lowest SNR avg. 16

17. poor receiver good receiver Layered source+channel (SCM) Layered source+channel with protection

18. Summary • Novelties: • Introduced protections on successive layers over layered broadcast • Utilized partial MDC (protected) packets (never discussed in wired infrastructure) • Modified existing MDC for practical implementation • An analytical model for analysis and optimization.  Resolved both multi-user channel diversity and error control problems which are not possible in all previous and recent works [1-4] [1] Chris T. K. Ng et al., “Recursive Power Allocation in Gaussian Layered Broadcast Coding with Successive Refinement,” IEEE Intl. Conf. on Comm. (ICC), Jun 24–27, 2007, Glasgow, Scotland, pp. 889–896. [2] C. Tian et al., “Successive Refinement Via Broadcast: Optimizing Expected Distortion of a Gaussian Source Over a Gaussian Fading Channel”, IEEE Trans. on Information Theory, vol. 54, no 7, pp.2903-2918, Jul. 2008. [3] Y. S. Chan et al., “An End-to-End Embedded Approach for Multicast/Broadcast of Scalable Video over Multiuser CDMA Wireless Networks”, IEEE Trans. on Multimedia, vol. 9, no. 3, pp. 655-667, Apr. 2007. [4] Murali R. Chari et al., “FLO Physical Layer: An Overview”, IEEE Trans. on Broadcasting, vol. 53, no. 3, pp. 145-160, Mar. 2007 18

19. Outline • Introduction & Background • A Preliminary Cross-layer Design • Coded Wireless Video Broadcast/Multicast • An Information-theoretical Bound of Expected Distortion • Conclusion & Future Works 19

20. Informaton-theoretical Bound of Expected Distortion Assume a successive refinable source with Gaussian distribution (i.e., L layers in each source symbol, S) Apply a generic (n, kl) protection code in a layer l: i.e. A source symbol, S n protected layered source symbol, Vi, where i=1,..., n. Recall: smaller kl value for layer l, more robustness, but less effective data sent • Did you realize that we send less video data? Costs of protections • If / whenthe proposed framework is better than a similar layered broadcastWITHOUT protections? • The expected distortion without layers [3] : where each source symbol is sent by a channel symbol under symbol error, perr. [3] X. Yu and En-hui Yang, “Optimal quantization for noisy channels with random index assignment", Proc. of the 2008 IEEE Intern. Symp. Inform. Theory, Toronto, Canada, July 6-11, 2008. 20

21. Bound of Expected Distortion protected layered source symbols, Vi x(i) • Each Vi a layered channel symbol, x(i), for each coded broad/multicast transmission: • A receiver collects n channel symbols, x(1), ... ..., x(n) over nchannel symbol durations. • Each x(i) is decoded into up to layer l with prob. upon the receiver`s instantaneous channel condition. 21

22. V1 ... ... Vn Bound of Expected Distortion After nchannel symbol durations (or ntransmissions), kL kl k1 • The Bound of Expected Distortion: • Applicable to a system without protection (i.e., kl =n) • The discreteness (i.e., binomial CDF terms) can be approximated by a normal CDF to determine optimal k values for optimization. 22

23. Numerical Anylysis -1 Fixed symbol error at layer 2 (a) higher pM,1 (k1*=5, k2*=2) (b) lower pM,1 (k1*=14, k2*=2) Fixed symbol error at layer 1 higher pM,2 (k1*=18, k2*=1) (b) lower pM,2(k1*=18, k2*=3) 23

24. Numerical Anlysis - 2 Expected distortions of two systems (with and without protections) under various pM,1 in layer 1 and pM,2 in layer 2.

25. Simulation Comparisons Layered broadcast without and with protections under optimized parameters: Fixed lower, pM,2, in layer 2 Fixed higher, pM,2, in layer 2 Systems with their optimized configurations . 25

26. Summary of Expected Distortion • Novelties: • A general closed-form formula for the bound of expected distortion • Generic to any (n, k) protection code and any number of layers (source/channel), useful for a new coding design • More accurate analysis/optimization, instead of using simply using throughput/bitstream amount.

27. Outline • Introduction & Background • A Preliminary Cross-layer Design • Coded Wireless Video Broadcast/Multicast • An Information-theoretical Bound of Expected Distortion • Conclusion & Future Works 27

28. Contributions • 1st framework using protections for tackling multi-user diversity and error control. • 1st realization through existing codings, as well as the associated analytical and optimization models. • 1st information-theoretical distortion bound for comparisons, and optimization through a simple search. Advanced the fields by introducing a new design dimension – protections, for cross-layer designs that was unapparent in the past literature. LESS is MORE sometimes! 28

29. Future Work • Extend into cooperative communications under multi-BSs wireless networks (e.g., optical-wireless hybrid network) by considering space-time coding • Promising results from preliminary investigations in EPON-WiMAX access networks Final Remark: a cross-layer design with protections is shown to be useful in cooperative networks for better video broadcast/multicast 29

30. On-gogin Research and Industrial Collaborations • WiMAX/LTE BS system and • cooperative broadcasting networks • (prototype and research) • SPC chipset and software-defined radio platform (research) Electrical & Computer Engineering (Taiwan) (Italy) • New scalable source coding with protection (research) (Saudi Arabia) Electrical & Computer Engineering (Ottawa) • Coded MIMO Broadcast/Multicast • (research) • WiFi platform (prototype) Electrical & Electronic Engineering

31. Acknowledgement Prof. Pin-Han Ho, University of Waterloo Prof. En-hui Yang, University of Waterloo Dr. Xiang Yu, Research-In-Motion Sponsors: IPMG Collaborators: 31

32. Collaborations and students • Looking for like-minded researchers and organizations/industries for collaborations and funs! • Looking for smart, creative and entrepreneurial students to join me as my research interns. • Email: james.she@cl.cam.ac.uk • Web: http://www.cl.cam.ac.uk/~js864 32

33. The End THANK YOU 33

34. Selected Publication From This Research SCM: [1] J. She, et al., “IPTV over WiMAX: Key Success Factors, Challenges and Solutions”, IEEE Communications Magazine, vol. 45, no. 8, pp.87-93, Aug. 2007. (Top 50 most accessed article in IEEE Xplore 2008, and cited in Wikipedia under MobileTV) Coded Wireless Video Broadcast/Multicast: [2] J. She, et al., “A Cross-Layer Design Framework for Robust IPTV Services over IEEE 802.16 Networks”, IEEE Journal of Selected Areas on Communications (JSAC), vol. 27, no. 2, Feb. 2009, pp. 235-245. [3] J. She, et al., “A Framework of Cross-Layer Superposition Coded Multicast for Robust IPTV Services over WiMAX”, Proceedings of the IEEE Wireless Communication and Networking Conference, pp. 3139-3144, Mar. 2008, Las Vegas, Nevada, USA. (Nominated for the Best Student Paper Award) Expected Distortion Comparison: [4] J. She, et al., “Distortion Comparisons For Protected Successive Refined Over Broadcast Channel ”, submitted to Trans. Multimedia, Jul. 2010. L-SPC: [5] J. She, et al., “Logical Superposition Coded Modulation”, submitted to Trans. Wireless Communication, Nov. 2010. 34