A Layered Hybrid ARQ Scheme for Scalable Video Multicast over Wireless Networks

1. A Layered Hybrid ARQ Scheme for Scalable Video Multicast over Wireless Networks Zhengye Liu, Joint work with Zhenyu Wu

2. Outline • Motivations & challenges • Review of error protection approaches • Layered hybrid ARQ • Operating point selection in multiple user scenario • A general game theoretic framework in operating point selection • Layered hybrid ARQ in video multicast • Conclusion

3. Motivations & Challenges • Motivation of video multicast over WLANs • Utilize bandwidth efficiently • Challenges • Error protection mechanisms are needed • Fading, channel interference, … • Heterogeneity of channel conditions • Different channel conditions • Overall system performance • Individual user fairness S S R R R R C C C C C C multicast unicast

4. Packet Loss Pattern • Burst packet losses • Difficult to predict

5. Review of error protection approaches • Retransmission • Inappropriate in multicast scenario • FEC • Constant throughput and bounded delay • Throughput is reduced in the good state • Adaptive FEC • Prediction of channel conditions in the future • Hybrid ARQ • [Majumdar 02]

6. Hybrid ARQ Scheme • Generate parity packets • Send source packets • Send parity packets until all lost source packets can be recovered S 1 2 3 4 5 1 2 3 C ACK

7. Hybrid ARQ Scheme • Use bandwidth efficiently • Should have sufficient bandwidth

8. Layered Hybrid ARQ Scheme • Encode a video into multiple layers • Temporal scalability • Transmit packets from more important layers to less important layers • For each layer, transmit source packets first and then parity packets, based on hybrid ARQ • Given a total transmission bandwidth, provide unequal protection • Protect more important layers • Selectively drop source packets from less important layers • No overall rate expansion

9. An Illustration S C

10. Performance Evaluation • Single user scenario • Only one user in the multicast group • Comparison • Hybrid ARQ with single layer video (single hybrid ARQ) • Layered hybrid ARQ

11. Simulation Setup (1) • H.264 codec JM11 • Football (720x480, 30 frame/sec) • Average bitrate: 1400 kbps • Fix QPs • Temporal scalability in H.264 Layer 3 Layer 1 Layer 2

12. Simulation Setup (2) • RS coding (255, k) for each layer • Frame copy in decoder • Total transmission bandwidth: 2200 kbps • Packet loss pattern: two-state Markov model

13. Packet Receive Ratio • Percentage of received/recovered source packets over the total encoded source packets • Layered hybrid ARQ can provide unequal protection for different layers • All packets from I and P frames can be received • Most packets from Bs frames can be received

14. Average Channel Induced MSE • Layered hybrid ARQ can outperform hybrid ARQ significantly in received video quality

15. MSE Frame by Frame (p=30%)

16. Demo • Packet loss rate: 30% • Single hybrid ARQ vs. Layered hybrid ARQ

17. Layered Hybrid ARQ in Multiple User Scenario • Heterogeneity of channel conditions • Different preferred configurations (operating points) of video multicast ? S C1 C2

18. How to Select Operating Point? • Worst case • Based on the user with the worst channel condition • Play a game • Play “lottery” among users Parity packet from layer 1 Source packet from layer 2 C1 C2 Parity packet from layer 1 Source packet from layer 2 C1 C2 50% 50%

19. Is This Game Fair? • Two players, each owning a car, play lottery with each other • If a player wins the game, he/she can win the car from the other player Player 2 Player 1 50% vs. 50%? 99% vs. 1% Source packet from layer 2 Parity packet from layer 1 C1 C2 λ1 vs. λ2 ? What are the probabilities for a fair game?

20. Nash Bargaining Game • Proposed by John Nash in 1950 • A cooperative game • Players have perfect knowledge of each other • Proved the existence of Nash bargaining solution (NBS) for this game • Unique solution • Pareto optimal • No other solution produces better utility for one player without hurting another player • Fair in the sense of cooperative game • Satisfy the axioms of fairness

21. Formulation of Nash Bargaining Game • Player: • N users in a multicast group • Strategy: • M operating points, sm • Mixed game with mixed strategy S = λ1s1 + λ2s2 +,…,+ λMsM • Preference: • The utility of each strategy for user i, ui(sm). • Mixed utility Ui = λ1ui(s1) + λ2ui(s2) +,…,+ λMui(sM) • Initial utility: • di, user would like to at least achieve if they enter the game • Ui>di, otherwise user i will not enter the game • Nash bargaining solution (NBS): • λ*=(λ1, λ2,…, λM) • Users consider it as a fair setting of the lottery

22. An Example Source packet from layer 2 Parity packet from layer 1 • Player: • Two users • Strategy: • Three operating points, sm=“transmit a packet from layer m” • Mixed game with mixed strategy, pm is the probability that a packet from layer m will be chosen S = λ1s1 + λ2s2 + λ3s3 • Preference: • ui(sm):how much payoff user i can get when a packet from layer m will be sent • The anticipation of payoff from the lottery (mixed game) Ui = λ1ui(s1) + λ2ui(s2) + λ3ui(s3) • Initial utility: • di C1 C2

23. Utility • If user i is requesting layer m, then only a packet from layer m is useful. • wm should represent the importance of a packet from layer m on video quality • Use a channel distortion model to obtain wm Parity packet from layer 1 u1(s1) = w1, u1(s2) = 0, u1(s3) =0 C1 Source packet from layer 2 C2 u2(s1) = 0, u2(s2) = w2, u2(s3) =0

24. Channel Distortion Model of Temporal Scalable Video • Channel distortion model of single layer video • Channel distortion model of temporal scalable video w1=1400, w2=650, w3=150

25. Initial Utility • Guarantee that the expected Ui>di • A flexible control parameter • Select a higher di, if the “system” gives more protection to user i • User i subscribes more premium service • It is more urgent for user i to win the game • If user i is requesting a packet from layer m d1>d2 Parity packet from layer 1 Source packet from layer 2 C1 C2 α=2 d1=w1/2, d2=w2/4

26. Obtain NBS • A Nash bargaining game • Player, strategy, preference (utility), and initial utility • Solve an optimization problem • Exhaustive search for small M • Convex programming for a large M

27. Procedure of operating point selection • Trace the state for each user • From which layer the user is requesting a packet • Based on the ACKs sent from the receivers • Play Nash bargaining game • Obtain ui(sm) and di • Obtain the NBS λ*=(λ1, λ2,…, λm) • Given λ*, play lottery to select a packet for sending

28. Performance Evaluation (1) • Lead to NBS optimality and fairness in microscopic view (packet level) • The macroscopic affect of a strategy on received video qualities • Overall performance: The majority of users are more likely to obtain their preferred operating points than the minority of users • Individual fairness: No individual user is denied access to the multicasting system or overly penalized • Flexibility: Can be tuned to satisfy different requirements.

29. Performance Evaluation (2) • Comparison • Worst case • Nash bargaining game • Investigate the impact of initial utility di on system performance • Higher di leads to more protection to user i • α=2, 4, and 100 • By using a smaller α, guarantee a better basic video quality for bad channel users

30. Simulation Setup • N users totally • N-1 users are in a good channel condition (p=1%) • One user is in a bad channel condition (p=30%) • N=2, 4, 8, 16, 32

31. Average MSE (b) Bad channel user (a) Good channel user

32. Summery

33. Conclusion • Propose a layered hybrid ARQ scheme for video delivery over WLANs • Propose a game theoretic framework in operating point selection for video mulitcast • Examine the game theoretic framework with the proposed layered hybrid ARQ

34. Thanks!