Joint Design Of Physical-Layer Network Coding And Convolutional Coding

Network coding can improve network throughput by allowing the coding operate on intermediate node. It has been always applied in wired network. With the development of wireless network in recent years, how to apply network coding to wireless environment has received much attention. By making use of the mixing of superimposed EM waves that occurs in nature and the broadcast property in wireless system, physical-layer network coding can furture improve throughput.This thesis considers the joint design of PNC(Physical-layer network coding) and convolutional coding and more with the modulation based on the two-way relay channel. The main work of this thesis is given as follows:(1) In connection with BER performance in wireless channel when applying PNC, we try to make use of channel coding and make a joint design of PNC and convolutional coding. We consider the factors of reliability and complexity of the transmition system, and focus on the channel-decoding-network-coding strategy on relay node. The simulation results show that the proposed link-by-link coded PNC with low-complexity modified viterbi algorithm on relay node outperforms the PNC-viterbi algorithm with the same complexity.(2) We add the modulation into the joint design of PNC and convolutional coding and try to match these three techniques. We design the convolutional coding and8PSK modulation together to form TCM (Trellis coded modulation), and take advantage of the linear property of concolutional code, apply the TCM-viterbi-decoding scheme on relay node. The simulation results show that the proposed scheme improves the channel capacity while the BER performance is still not bad.