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One-Size-Fits-All Wireless Video

One-Size-Fits-All Wireless Video. Szymon Jakubczak with Hariharan Rahul and Dina Katabi. Wireless Video Has Important Applications. Mobile TV Live streaming sports, concerts, conferences, lectures, … Broadcast TV. All involve multicast, and some involve mobility

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One-Size-Fits-All Wireless Video

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  1. One-Size-Fits-All Wireless Video SzymonJakubczak with HariharanRahul and Dina Katabi

  2. Wireless Video Has Important Applications • Mobile TV • Live streaming • sports, concerts, conferences, lectures, … • Broadcast TV All involve multicast, and some involve mobility Current design struggles with multicast and mobility

  3. Multicast Challenges Current Wireless Design • Currently, the sender has to pick a bitrate • But different receivers support different bitrates High bitrate Starves the far receiver 1Mb/s 6Mb/s

  4. Multicast Challenges Current Wireless Design • Currently, the sender has to pick a bitrate • But different receivers support different bitrates High bitrate Starves the far receiver Low bitrate  Reduces everyone to the worst receiver 1Mb/s 6Mb/s

  5. Mobility Makes Things Worse • Mobility causes fastunpredictable SNR variations High rate  Video stalls when SNR dips Low rate  Overall video quality is low Received Signal Level [dBm] 200ms Time [ms] • Successive frames may experience a different channel

  6. Common Problem Hard to pick a single rate that matches the channel Wrong bitrate video degrades drastically But …

  7. In principle, video quality should degrade smoothly with channel quality Sender should be able to simply transmit: Noisy channel  decoded pixels approximate original pixels Good channel  decoded pixels match originals

  8. Why Cannot Current Design Provide Smooth Degradation? • Compression and error protection convert real-valued pixels to bits • Bits destroy the numerical properties of original pixels 11110 and 11111 could refer to pixels as different as 5 and 149 • If all bit errors can be corrected all pixels are correct • Even one residual bit error arbitrary errors in pixels

  9. Analog TV Degraded Smoothly It did not convert pixels to bits Real-Valued Pixels2, 153, … Transmitted Values • 2α, 153α, … α Transmitted values are linearly related to pixel luminance Small perturbation in pixel values Small perturbation on channel But Analog TV was not efficient: • No compression • No error protection

  10. SoftCastCombines the Best of Both Worlds Like Digital TV, It codes for compression and error protection Like Analog TV, • It provides smooth degradation

  11. SoftCast Goal: transmitted signal is linearly related to the pixels • smooth degradation SoftCast uses a new coding technique that: • converts pixels to real-valued codewords, not bits • provides compression and error protection while preserving linearity between pixels and codewords • passes the codewords to the PHY, which transmits them directly on the channel

  12. How Does SoftCast Compress? Pixels in an image change gradually • In frequency domain, most high frequencies are zero • STEP1: Convert a frame to frequency domain using DCT • STEP2: Send only non-zero frequencies in the frame •  Compressing the frame DCT ofwhole frame Zeros

  13. Encoder needs to tell the decoder the location of zeros • Easy because zeros are clustered Divide into chunks and drop zero chunks • Use a bit map to tell receiver locations of zero chunks Drop Zero Chunks • DCT is a linear operator • Dropping zero chunks does not break linearity •  SoftCast’s compression preserves linearity

  14. How Does SoftCast Provide Error Protection? SoftCast protects real-valued codewords using magnitude-scaling After Rx Scale down Before Tx Scale up Channel Noise ±0.1 /10 x10 25.1 2.51 2.5 25 ±0.1 Transmitted Codeword Received Decoded ±0.01 24.9 2.49

  15. How Does SoftCast Provide Error Protection? SoftCast protects real-valued codewords using magnitude-scaling After Rx Scale down Before Tx Scale up Channel Noise ±0.1 /10 x10 25.1 2.51 Scaling the codeword up, scales down the effective noise on the channel by the same factor 2.5 25 ±0.1 Transmitted Codeword Received Decoded ±0.01 24.9 2.49

  16. But Can’t Scale All Codewords Up Scaled-up values are larger  take more power to transmit But hardware has limited power Theorem • Let λi be the variance of chunk i • The linearencoder that minimizes video errors scales the values xi in chunk i as follows: yi = gixiwheregi ~ λi-1/4 We find the optimal scaling factors that minimize video errors given hardware power Scaling is linear  SoftCast’s error protection preserves linearity

  17. How Does thePHY Transmit? Recall: Channel transmits pairs of real values (I and Q) I QAM modulation Traditional PHY maps bits to reals (I and Q) using modulation SoftCast PHY directly transmits the real-valued codewordsas I and Q Q …0011001 • y[1] • y[3]y[1] • …y[5] • …y[5]y[4]y[3] • …y[5]y[4]y[3]y[2]y[1] • y[2] • y[4]y[2] I Q SoftCast achieves its goal of ensuring that the transmitted signal is linearly related to the pixels

  18. Performance

  19. Compared Schemes • SoftCast • MPEG-4 (H.264) over 802.11 • Implemented in libx264 via ffmpeg • 2-Layer Video • A base layer and an enhancement layer • Implemented in libx264 via ffmpeg

  20. Test Setup • Collected channel traces with WARP between node in testbed Locations of trace collection WARP

  21. Test Setup • Collected channel traces with WARP between node in testbed • Extracted noise patterns as differences between transmitted and received soft values • Compare schemes for the same trace-driven channels Encoders Decoders MPEG4 MPEG4 Trace-Driven Channel (802.11 OFDM) 2-Layer Video 2-Layer Video SoftCast SoftCast

  22. Video Quality vs. Channel Quality

  23. Video Quality vs. Channel Quality

  24. Video Quality vs. Channel Quality

  25. Video Quality vs. Channel Quality MPEG degrades drastically when the bitrate does not match channel SNR

  26. Video Quality vs. Channel Quality SoftCast combines efficiency with smooth video degradation

  27. Multicast • Receiver 1 has SNR = 5dB – best bitrate 6Mb/s • Receiver 2 has SNR = 21dB – best bitrate 48Mb/s

  28. Multicast • Receiver 1 has SNR = 5dB – best bitrate 6Mb/s • Receiver 2 has SNR = 21dB – best bitrate 48Mb/s

  29. Multicast • Layered video: • Base layer at 6Mb/s, enhancement layer at 48 Mb/s • Have to divide medium time between the layers

  30. Multicast • Layered video: • Base layer at 6Mb/s, enhancement layer at 48 Mb/s • Have to divide medium time between the layers

  31. Multicast • Layered video: • Base layer at 6Mb/s, enhancement layer at 48 Mb/s • Have to divide medium time between the layers In 2-layer video, enhancement reduces transmission time of base Weak receiver becomes worse off

  32. Preliminary Mobility Results 7 6.5 6

  33. Preliminary Mobility Results 7 6.5 6 SNR variations cause major glitches in MPEG

  34. Preliminary Mobility Results 7 6.5 6 SoftCast reacts smoothly to changes in SNR

  35. Conclusion • Digital video can achieve smooth degradation • Key Idea: • Continue to compress and protect against errors • But make codewords linearly related to pixels • Experimental results show this approach is highly promising for multicast and mobile scenarios

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