  Recently, soft video multicasting has gained a lot of attention, especially
in broadcast and mobile scenarios where the bit rate supported by the channel
may differ across receivers, and may vary quickly over time. Unlike the
conventional designs that force the source to use a single bit rate according
to the receiver with the worst channel quality, soft video delivery schemes
transmit the video such that the video quality at each receiver is commensurate
with its specific instantaneous channel quality. In this paper, we present a
soft video multicasting system using an adaptive block-based compressed sensing
(BCS) method. The proposed system consists of an encoder, a transmission
system, and a decoder. At the encoder side, each block in each frame of the
input video is adaptively sampled with a rate that depends on the texture
complexity and visual saliency of the block. The obtained BCS samples are then
placed into several packets, and the packets are transmitted via a
channel-aware OFDM (orthogonal frequency division multiplexing) transmission
system with a number of subchannels. At the decoder side, the received BCS
samples are first used to build an initial approximation of the transmitted
frame. To further improve the reconstruction quality, an iterative BCS
reconstruction algorithm is then proposed that uses an adaptive transform and
an adaptive soft-thresholding operator, which exploits the temporal similarity
between adjacent frames to achieve better reconstruction quality. The extensive
objective and subjective experimental results indicate the superiority of the
proposed system over the state-of-the-art soft video multicasting systems.
