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.

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