Convolutional codes in two-way relay networks with rate diverse network coding
Ping Shou Cheng, Jianjun Hao, Yijun Guo · 2012
In two-way relay networks (TWRNs) with physical-layer network coding (PNC), introduction of convolutional codes is able to enhance the overall system reliability. In addition, the relay node has to determine a particular broadcast rate for coded packets transmission as the selected rate should be supported on the worst quality links to the intended receivers. Thus, the throughput gain brought by network coding is limited by capacity of the worst link in TWRNs. In this paper, a novel symbol-level rate diverse network coding (RDNC) scheme and reduced-state decoding scheme for convolutional codes are proposed to address the two problems. In this setup, for a given memory length constraint, two source nodes can adopt convolutional codes of different lengths and use reduced-state trellis to reduce decoding complexity. In this work, it is shown that the proposed approach is able to improve system throughput significantly, offer increased reliability, and reduce the complexity of convolutional codes decoding at the same time.