CHANNEL ALLOCATION FOR SMOOTH VIDEO DELIVERY OVER COGNITIVE RADIO NETWORKS Globecom 2010, FL, USA 1 Sanying Li, Tom H. Luan, Xuemin (Sherman) Shen Department of Electrical and Computer Engineering University of Waterloo, Waterloo, ON, Canada, N2L 3G1 Outline 2 Introduction Proposed channel allocation algorithm for smooth video delivery over CR networks System model Optimization framework Heuristic algorithm Simulation results Conclusion and future works Video Streaming System 3 Video streaming demands stringent QoS support from the network work Low delay High throughput Low network dynamics Cognitive radio network Highly dynamic due to random behaviour of primal users Spotted wireless communication with time varying channel status How to address the extraordinary network dynamics on provisioning guaranteed video quality to users? 4 Users need guarantee on the smoothness of playback. Playout buffer is deployed to address the issue of network dynamics. Video Quality for VoD Playback frozen Motivation: How to provide guaranteed QoS for VoD within the dynamic and resource-limited CR networks ? Research Motivation and Goal 5 Dynamic nature of CR Unpredictable PU behavior Contention among SU for channel Time varying channel throughput V.S. Approach: Exploit the playout buffer to accommodate network dynamic and conduct channel resource allocation. Users of different playout buffer storage can tolerate different levels of dynamics QoS Smooth playback without interruptions Sensitive to dynamics Outline 6 Introduction Proposed channel allocation algorithm for smooth video delivery over CR networks System model Optimization framework Heuristic algorithm Simulation results Conclusion and future works (Video Source) An infrastructure-based, single-hop CR network N OFDM channels, N primary users CR base station s allocates idle channels to M secondary users (CR users). In total VoD users and best-effort (BE) users, and The CR base station s delivers video flows to VoD users using OFDM downlink. Network Architecture 7 (Video Source) Protocol Description 8 System works on a time-slot basis. is the minimum spectrum sensing and transmission unit. Channel allocation operates interactively at the interval of channel allocation epoch Each epoch is composed of two phases: beacon period and transmission period. Time slot allocation based on the estimation of the availability of future spectrum resources and the current buffer storage of users. QoS requirements of VoD users: Represented by the smoothness of video playback The probability of playback frozen depends on [4] : Mean and variance of the inter-arrival time of packets Mean and variance of the inter-departure time of packets Buffer storage 9 [4] Tom H. Luan, L. X. Cai, and X. Shen, "Impact of network dynamics on users' video quality: analytical framework and QoS provision", IEEE Transaction on Multimedia, 2010 QoS Requirements of VoD Users : The probability of playback frozen of VoD user m in T seconds: QoS Requirements of Users 10 The QoS of VoD user m is guaranteed by: The QoS of BE user m is guaranteed by: (Guaranteed Throughput) (Guaranteed Playback Smoothness) Formulate the channel allocation as an optimization problem: Optimization Framework 11 if channel n is allocated to user m, otherwise. (Maximize the overall throughput) (QoS of VoD users) (QoS of BE users) (One user allocated to one channel) Decision variable: How to represent and by ? On-OFF model of the CR channel The occupancy of channel n (n = 1, 2,... N ) follows a discrete-time Markov process. p-persistent MAC of secondary users Constant transmission rate of user m on channel n over channel allocation epoch T Solution 12 Where represents the SNR of user m on channel n Heuristic Algorithm 13 Channel 1 Channel 2 VoD User 1 VoD User 2 VoD User 3 BE User 1 BE User 2 BE User The allocation guarantees the performance of VoD users. Simulation Results M (Number of SUs)50 (Number of VoD users)20 (Number of BE users)30 N (Number of channels)5 (Channel availability)0.3, 0.4, 0.5, 0.6, 0.7 (Transmission rate)[1000, 2000] pkts/sec (Length of one slot)10 ms L (Number of slots in each channel allocation epoch)50 (Upper bound of frozen probability)0.05 (Lower bound of BE users mean transmission rate)30 pkts/sec r (Mean of video playback rate) pkts/sec (Variance of video playback rate)102 Initial buffer storage50 pkts Life time of VoD user[10, 30] secs 14 Compare with two schemes 15 Random allocation: SUs are randomly allocated to each channel every allocation epoch. Greedy allocation: SUs are allocated to the channel with the largest throughput: Transmission rate of user m on channel n Availability of channel n (not used by primary user) Change Channel Capacity 16 Frozen probability of VoD users: Increasing the channel capacity would decrease the frozen probability of VoD users. Change Channel Capacity 17 Percentage of satisfied BE users: Overall throughput: The performance of BE users is represented by the percentage of BE users whose throughput are larger than 30 pkts/sec. Increasing the channel capacity would increase the percentage of satisfied BE users. Increasing the channel capacity would increase the overall throughput. Change the Population of VoD Users 18 Frozen probability of VoD users: Increasing the number of VoD users does not change the frozen probability of VoD users. 19 Percentage of satisfied BE users: Overall throughput: Change the Population of VoD Users Increasing the number of VoD users would decrease the overall throughput. The performance of BE users is represented by the percentage of BE users whose throughput are larger than 30 pkts/sec. Increasing the number of VoD users would decrease the percentage of satisfied BE users. Change the Length of Allocation Epoch 20 Frozen probability of VoD users: Increasing L would increase the frozen probability of VoD users. Conclusion and Future Works 21 Future work Investigate the optimal solution with guaranteed performance; Distributed channel allocation algorithm. Optimal channel allocation framework Exploit the user diversity in terms of the tolerance to the network dynamics; Propose a heuristic algorithm which has low time complexity; Simulation results show the heuristic algorithm outperforms the conventional schemes. 22