A cross-layer design for scalable mobile video

Abstract

Today's mobile video suffers from two limitations: 1) it cannot reduce bandwidth consumption by leveraging wireless broadcast to multicast popular content to interested receivers, and 2) it lacks robustness to wireless interference and errors. This paper presents SoftCast, a cross-layer design for mobile video that addresses both limitations. To do so, SoftCast changes the network stack to act like a linear transform. As a result, the transmitted video signal becomes linearly related to the pixels' luminance. Thus, when noise perturbs the transmitted signal samples, the perturbation naturally translates into approximation in the original video pixels. This enables a video source to multicast a single stream that each receiver decodes to a video quality commensurate with its channel quality. It also increases robustness to interference and errors which now reduce the sharpness of the received pixels but do not cause the video to glitch or stall. We have implemented SoftCast and evaluated it in a testbed of software radios. Our results show that it improves the average video quality for multicast users by 5.5 dB, eliminates video glitches caused by mobility, and increases robustness to packet loss by an order of magnitude.

Video Transmission Over Lossy Wireless Networks: A Cross-Layer Perspective

“…As a result, without perfect adaptation of transmission schemes (which is not easy to achieve because of the unpredictability of the time-varying wireless channel quality), wireless video streaming may suffer from severe cliff effects and be rather choppy. In [58], [62], [63], [64], the authors address this challenge by proposing soft video coding and decoding, which, roughly speaking, leverage soft physical-layer information like bit-level probability belief (instead of only the hard binary channel-decoding-results), or use linear analog coding (instead of variable-length digital coding) for video compression and channel error protection. Next, we discuss FlexCast [58] as an example.…”

“…The idea of exploiting "soft information" to enable noise (error) resilience has also been leveraged in SoftCast [62], its MIMO-OFDM extension ParCast [63], and also in D-Cast designed for distributed video coding [64]. There, the available transmission power budget is allocated among DCT coefficients proportionally to their magnitude levels, e.g., through magnitude scaling and DCT-chunk transformation in [62].…”

“…There, the available transmission power budget is allocated among DCT coefficients proportionally to their magnitude levels, e.g., through magnitude scaling and DCT-chunk transformation in [62]. The authors in [58], [62], [63], [64] show that soft video streaming enables the reception video quality to scale gracefully with wireless channel quality, and in practice be higher than that of non-soft ones; this graceful reception characteristic can also be achieved using the CVS encoder introduced in Section III-D.…”

“…There, the available transmission power budget is allocated among DCT coefficients proportionally to their magnitude levels, e.g., through magnitude scaling and DCT-chunk transformation in [62]. The authors in [58], [62], [63], [64] show that soft video streaming enables the reception video quality to scale gracefully with wireless channel quality, and in practice be higher than that of non-soft ones; this graceful reception characteristic can also be achieved using the CVS encoder introduced in Section III-D. Hence, soft video streaming may provide a promising solution for those mobility-rich video applications where the channel quality may change very fast, like VoD on smart phones and in-vehicle VoD, and video broadcasting and multicasting applications where video terminals may experience different wireless channels hence having different decoding capabilities.…”

User-Centric Energy-Efficient Multimedia Multicast/Broadcast Solutions: A Survey

“…Several other studied dimensions are: resource utilization maximization [94], user-level fairness and multicast efficiency [95], transmission efficiency [96], cooperative transmission of layered video using randomized distributed space-time code [97], and cross-layer design for reducing bandwidth requirement and increasing robustness to channel errors [98].…”