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Cooperative Layered Wireless Video Multicast. Ozgu Alay, Thanasis Korakis, Yao Wang, Elza Erkip, Shivendra Panwar. Introduction. Video multicast over wireless channels Wireless video applications are emerging Multicast is effective Wireless video multicast is still a challenging problem
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Cooperative Layered Wireless Video Multicast Ozgu Alay, Thanasis Korakis, Yao Wang, Elza Erkip, Shivendra Panwar
Introduction • Video multicast over wireless channels • Wireless video applications are emerging • Multicast is effective • Wireless video multicast is still a challenging problem • High packet loss rate • Bandwidth variations • Cooperation is a natural solution • Higher spatial diversity • Adaptive to network conditions
Prior Work: Cooperation for Unicast • physical-layer cooperation for point-to-point video communication • Single-layer cooperation • layered cooperation • MAC-layer cooperation for point-to-point communication
Why Cooperative Multicasting ? • Each receiver has different channel quality • Conventional Multicast • Source transmits based on furthermost receiver • the receivers with a good channel quality unnecessarily suffer and see a lower quality video .
Extended Group 2 Group 2 Relay 1 Relay 4 AP Relay 2 Relay 3 Group 1 Why Cooperative Multicasting ? • Cooperative Multicast • Divide all the receivers into two groups such that receivers in Group 1 have better average channel quality than Group 2 • Sender targets receivers with good channel quality (Group1) • These receivers relay the video to other receivers (Group2) • It is likely that we achieve a larger coverage area (Extended Group 2). • Both groups see better quality
Received Video Rates T T1 T2 T2
Design Variables • Number of relays N • Sustainable rates (R1, R2) or transmission ranges (r1, r2) • Time partition (T1, T2) • N controls the tradeoff between R2 and T2 • How to optimize? • Maximize the average quality • All users have same quality • Group1 has better quality
Approach • For a particular (r1, r2) we determine the optimum (T1, T2) and N in two steps. • We first determine the user partition with a minimum number of relays. • Then for this user partition, we find the optimum T1 and T2 (time scheduling) that maximizes the system performance index • By repeating the above procedure for all possible (r1, r2) we find the optimum user partition and time scheduling that maximizes the performance criterion.
User Partition • Goal: Find minimum number of relays N that covers all the users • User partition is defined by (r1, r2) and the separation angle awhere, N = 2p/2a
User Partition • We define amaxas the maximum angle which satisfies the constraints below,
Optimum User Partition • a is maximum when • Then, using cosine theorem
Optimum User Partition • Then N is, • And rext can be computed as
Time Scheduling and Performance Metric • We use exhaustive search over a discretizied space of feasible T1 and T2, for each candidate T1 and T2, determine Rv1 and Rv2 and correspondingly D1 and D2. • Here D1(Rv1) is the distortion of Group 1 receivers and D2(Rv2) is the distortion for Group 2 receivers.
Minimum Average Distortion • N1 and N2 are the number of users in Group 1 and Group 2, respectively.
Equal Distortion at all users • We require all the receivers have the same distortion. • In other words, we find the optimum user partition and time scheduling that minimizes D1(Rv1) = D2(Rv2).
Best Quality at Group 1 users • Considering that relays are spending their own resources to help others, • We find the optimum user partition and time scheduling that minimizes D1(Rv1) while guaranteeing Rv2 = bRd
Sustainable Rates vs. Distance with IEEE 802.11b r1=61m, R1=11 Mbps r2=72m, R2=5.5 Mbps r3=100m, R3=1 Mbps
Example Scenario • 802.11b based WLAN • Uniformly distributed users within 100m radius (r=100m) • Achievable rate with direct transmission to all users, Rd = 1 Mbps • b=0.75 • Soccer • 704x576 resolution • 240 frames
Visual Quality 750 kbps ( 29.84 dB ) 1.178 Mbps ( 30.42 dB ) 3.75 Mbps ( 33.32 dB )
Conclusion • User cooperation can improve the quality of service in video multicast • Equal quality at all users • Better quality at selected users • All better than direct transmission • Optimization of relay selection, user partition, and transmission scheduling depends on the chosen multicast performance criterion