Random network coding based on adaptive sliding window in wireless multicast networks

Network coding offers a promising platform for multicast transmission to improve the throughput. However, the users may not collect a full set of the encoded packets to recover the useful information because of its block processing property, leading to the low throughput under wireless fading channel. While the schemes that using feedback from all the receivers to cover the problem above always causes the huge feedback overhead in large network. Accordingly, in this paper we proposed an adaptive sliding window random network coding(ASWRNC) that introduce RNC with lower triangular coefficient matrix and sliding window to achieve higher network throughput and lower feedback overhead. Particularly, we introduce an adaptive encoding scheme that can let the user decode out partial original packets without collecting the full set of encoded packets. On the other hand, the window sliding scheduling helps the user with better channel decode out more original packets. Further, we discuss in detail the feedback-compete mechanism to decline the feedback overhead.