Wireless Video Multicast with Cooperative and Incremental Transmission of Parity Packets
This work addresses video quality enhancement in wireless multicast for users in networks, but it is incremental as it builds on prior cooperative transmission methods.
The paper tackles the problem of improving video multicast rates in wireless networks by proposing a cooperative scheme that uses one-hop transmission for both source and parity packets, maximizing sustainable video rates for all nodes. The result is significantly higher video rates and PSNR compared to prior approaches, with suboptimal methods outperforming previous full-information schemes.
In this paper, a cooperative multicast scheme that uses Randomized Distributed Space Time Codes (R-DSTC), along with packet level Forward Error Correction (FEC), is studied. Instead of sending source packets and/or parity packets through two hops using R-DSTC as proposed in our prior work, the new scheme delivers both source packets and parity packets using only one hop. After the source station (access point, AP) first sends all the source packets, the AP as well as all nodes that have received all source packets together send the parity packets using R-DSTC. As more parity packets are transmitted, more nodes can recover all source packets and join the parity packet transmission. The process continues until all nodes acknowledge the receipt of enough packets for recovering the source packets. For each given node distribution, the optimum transmission rates for source and parity packets are determined such that the video rate that can be sustained at all nodes is maximized. This new scheme can support significantly higher video rates, and correspondingly higher PSNR of decoded video, than the prior approaches. Three suboptimal approaches, which do not require full information about user distribution or the feedback, and hence are more feasible in practice are also presented. The proposed suboptimal scheme with only the node count information and without feedback still outperforms our prior approach that assumes full channel information and no feedback.