Wireless multicasting of video signals based on distributed compressed sensing

Abstract

Multicasting of video signals over wireless networks has recently become a very popular application. Here, one major challenge is to accommodate heterogeneous users who have different channel characteristics and therefore will receive different noise-corrupted video packets of the same video source that is multicasted over the wireless network. This paper proposes a distributed compressed sensing based multicast scheme (DCS-cast), where a block-wise compressed sensing (BCS) is applied on video frames to obtain measurement data. The measurement data are then packed in an interleaved fashion and transmitted over OFDM channels. At the decoder side, users with different channel characteristics receive a certain number of packets and then reconstruct video frames by exploiting motion-based information. Due to the fact that the CS-measuring and interleaved packing together produce equally-important packets, users with good channel conditions will receive more packets so as to recover a better quality, which guarantees our DCS-cast scheme with a very graceful degradation rather than cliff effects. As compared to the benchmark SoftCast scheme, our DCS-cast is able to provide a better performance when some packets are lost during the transmission.