{"id":168037,"date":"2014-11-01T00:00:00","date_gmt":"2014-11-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/parcast-parallel-video-unicast-in-mimo-ofdm-wlans\/"},"modified":"2018-10-16T21:07:09","modified_gmt":"2018-10-17T04:07:09","slug":"parcast-parallel-video-unicast-in-mimo-ofdm-wlans","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/parcast-parallel-video-unicast-in-mimo-ofdm-wlans\/","title":{"rendered":"ParCast+: Parallel Video Unicast in MIMO-OFDM WLANs"},"content":{"rendered":"

We have observed two trends, growing wireless capability at the physical layer powered by MIMO-OFDM and growing video traffic as the dominant application traffic. Both the video source and MIMO-OFDM channel components exhibit nonuniform energy distribution. This has motivated us to leverage the source data redundancy at the channel to achieve high video recovery performance. We propose ParCast+ that first separates the source and the channel into independent components, matches the more important source components with higher-gain channel components, allocates power weights with joint consideration to the source and the channel, and uses pseudo-analog modulation for transmission. Such a scheme achieves fine-grained unequal error protection across source components. We implemented ParCast+ in Matlab and on Sora. Extensive evaluation has shown that our scheme outperforms competing schemes by notable margins, sometimes up to 6.4 dB in PSNR for challenging scenarios.<\/p>\n","protected":false},"excerpt":{"rendered":"

We have observed two trends, growing wireless capability at the physical layer powered by MIMO-OFDM and growing video traffic as the dominant application traffic. Both the video source and MIMO-OFDM channel components exhibit nonuniform energy distribution. This has motivated us to leverage the source data redundancy at the channel to achieve high video recovery performance. 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